format of review research paper

Review Paper Format: How To Write A Review Article Fast

This guide aims to demystify the review paper format, presenting practical tips to help you accelerate the writing process. 

From understanding the structure to synthesising literature effectively, we’ll explore how to create a compelling review article swiftly, ensuring your work is both impactful and timely.

Whether you’re a seasoned researcher or a budding scholar, these insights will streamline your writing journey.

Research Paper, Review Paper Format

What is a review paper.

Diving into the realm of scholarly communication, you might have stumbled upon a research review article.

This unique genre serves to synthesise existing data, offering a panoramic view of the current state of knowledge on a particular topic. 

Unlike a standard research article that presents original experiments, a review paper delves into published literature, aiming to: 

• clarify, and
• evaluate previous findings.

Imagine you’re tasked to write a review article. The starting point is often a burning research question. Your mission? To scour various journals, piecing together a well-structured narrative that not only summarises key findings but also identifies gaps in existing literature.

This is where the magic of review writing shines – it’s about creating a roadmap for future research, highlighting areas ripe for exploration.

Review articles come in different flavours, with systematic reviews and meta-analyses being the gold standards. The methodology here is meticulous, with a clear protocol for selecting and evaluating studies.

This rigorous approach ensures that your review is more than just an overview; it’s a critical analysis that adds depth to the understanding of the subject.

Crafting a good review requires mastering the art of citation. Every claim or observation you make needs to be backed by relevant literature. This not only lends credibility to your work but also provides a treasure trove of information for readers eager to delve deeper.

Types Of Review Paper

Not all review articles are created equal. Each type has its methodology, purpose, and format, catering to different research needs and questions.

Systematic Review Paper

First up is the systematic review, the crème de la crème of review types. It’s known for its rigorous methodology, involving a detailed plan for:

• identifying,
• selecting, and
• critically appraising relevant research. 

The aim? To answer a specific research question. Systematic reviews often include meta-analyses, where data from multiple studies are statistically combined to provide more robust conclusions. This review type is a cornerstone in evidence-based fields like healthcare.

Literature Review Paper

Then there’s the literature review, a broader type you might encounter.

Here, the goal is to give an overview of the main points and debates on a topic, without the stringent methodological framework of a systematic review.

Literature reviews are great for getting a grasp of the field and identifying where future research might head. Often reading literature review papers can help you to learn about a topic rather quickly.

Narrative Reviews

Narrative reviews allow for a more flexible approach. Authors of narrative reviews draw on existing literature to provide insights or critique a certain area of research.

This is generally done with a less formal structure than systematic reviews. This type is particularly useful for areas where it’s difficult to quantify findings across studies.

Scoping Reviews

Scoping reviews are gaining traction for their ability to map out the existing literature on a broad topic, identifying:

• key concepts,
• theories, and

Unlike systematic reviews, scoping reviews have a more exploratory approach, which can be particularly useful in emerging fields or for topics that haven’t been comprehensively reviewed before.

Each type of review serves a unique purpose and requires a specific skill set. Whether you’re looking to summarise existing findings, synthesise data for evidence-based practice, or explore new research territories, there’s a review type that fits the bill. 

Knowing how to write, read, and interpret these reviews can significantly enhance your understanding of any research area.

What Are The Parts In A Review Paper

A review paper has a pretty set structure, with minor changes here and there to suit the topic covered. The format not only organises your thoughts but also guides your readers through the complexities of your topic.

Title & Abstract

Starting with the title and abstract, you set the stage. The title should be a concise indicator of the content, making it easier for others to quickly tell what your article content is about.

As for the abstract, it should act as a descriptive summary, offering a snapshot of your review’s scope and findings. 

Introduction

The introduction lays the groundwork, presenting the research question that drives your review. It’s here you:

• justify the importance of your review,
• delineating the current state of knowledge and
• highlighting gaps.

This section aims to articulate the significance of the topic and your objective in exploring it.

Methodology

The methodology section is the backbone of systematic reviews and meta-analyses, detailing the research methods employed to select, assess, and synthesise studies. 

This transparency allows readers to gauge the rigour and reproducibility of your review. It’s a testament to the integrity of your work, showing how you’ve minimised bias.

The heart of your review lies in the body, where you:

• analyse, and
• critique existing literature.

This is where you synthesise evidence, draw connections, and present both sides of any argument. Well-structured paragraphs and clear subheadings guide readers through your analysis, offering insights and fostering a deeper understanding of the subject.

Discussion & Conclusion

The discussion or conclusion section is where you weave together the main points, reflecting on what your findings mean for the field.

It’s about connecting the dots, offering a synthesis of evidence that answers your initial research question. This part often hints at future research directions, suggesting areas that need further exploration due to gaps in existing knowledge.

Lastly, the citation list is your nod to the scholarly community, acknowledging the contributions of others. Each citation is a thread in the larger tapestry of academic discourse, enabling readers to delve deeper into the research that has shaped your review.

Tips To Write An Review Article Fast

Writing a review article quickly without sacrificing quality might seem like a tall order, but with the right approach, it’s entirely achievable. 

Clearly Define Your Research Question

Clearly define your research question. A focused question not only narrows down the scope of your literature search but also keeps your review concise and on track.

By honing in on a specific aspect of a broader topic, you can avoid the common pitfall of becoming overwhelmed by the vast expanse of available literature. This specificity allows you to zero in on the most relevant studies, making your review more impactful.

Efficient Literature Searching

Utilise databases specific to your field and employ advanced search techniques like Boolean operators. This can drastically reduce the time you spend sifting through irrelevant articles.

Additionally, leveraging citation chains—looking at who has cited a pivotal paper in your area and who it cites—can uncover valuable sources you might otherwise miss.

Organise Your Findings Systematically

Developing a robust organisation strategy is key. As you gather sources, categorize them based on themes or methodologies. This not only aids in structuring your review but also in identifying areas where research is lacking or abundant.

Tools like citation management software can be invaluable here, helping you keep track of your sources and their key points. We list out some of the best AI tools for academic research here. 

Build An Outline Before Writing

Don’t underestimate the power of a well-structured outline. A clear blueprint of your article can guide your writing process, ensuring that each section flows logically into the next.

This roadmap not only speeds up the writing process by providing a clear direction but also helps maintain coherence, ensuring your review article delivers a compelling narrative that advances understanding in your field.

Start Writing With The Easiest Sections

When it’s time to write, start with sections you find easiest. This might be the methodology or a particular thematic section where you feel most confident.

Getting words on the page can build momentum, making it easier to tackle more challenging sections later.

Remember, your first draft doesn’t have to be perfect; the goal is to start articulating your synthesis of the literature.

Learn How To Write An Article Review

Mastering the review paper format is a crucial step towards efficient academic writing. By adhering to the structured components outlined, you can streamline the creation of a compelling review article.

Embracing these guidelines not only speeds up the writing process but also enhances the clarity and impact of your work, ensuring your contributions to scholarly discourse are both valuable and timely.

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

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How to Write a Best Review Paper to Get More Citation

Review Paper Writing Guide

Are you new to academia? Do you want to learn how to write a good review paper to get in-depth knowledge about your domain? you are at the right place. In this article, you will learn how to write the best review paper in a step-by-step systematic procedure with a sample review article format to get more Citation.

What is a Review Paper?

A review paper, or a literature review , is a thorough, analytical examination of previously published literature. It also provides an overview of current research works on a particular topic in chronological order.

• The main objective of writing a review paper is to evaluate the existing data or results, which can be done through analysis, modeling, classification, comparison, and summary.  
• Review papers can help to identify the research gaps, to explore potential areas in a particular field.
• It helps to come out with new conclusions from already published works.
• Any scholar or researcher or scientist who wants to carry out research on a specific theme, first read the review articles relevant to that research area to understand the research gap for arriving at the problem statement.
• Writing a review article provides clarity, novelty, and contribution to the area of research and it demands a great level of in-depth understanding of the subject and a well-structured arrangement of discussions and arguments.
• Some journals publish only review papers, and they do not accept research articles. It is important to check the journal submission guidelines.

Difference Between a Review Paper and a Research Paper

The difference between a review paper and a research paper is presented below.

6 T ypes of Review Papers

The review papers are classified in to six main categories based on the theme and it is presented in the figure below.

Purpose of Review Paper

The purpose of a review paper is to assess a particular research question, theoretical or practical approach which provides readers with in-depth knowledge and state-of-the-art understanding of the research area.

The purpose of the review paper can vary based on their specific type and research needs.

• Provide a unified, collective overview of the current state of knowledge on a specific research topic and provide an inclusive foundation on a research theme.
• Identify ambiguity, and contradictions in existing results or data.
• Highlight the existing methodological approaches, research techniques, and unique perceptions.
• Develop theoretical outlines to resolve and work on published research.
• Discuss research gaps and future perspectives.

Criteria for Good Review Paper

A good review paper needs to achieve three important criteria. ( Palmatier et al 2017 ).

• First, the area of research should be suitable for writing a review paper so that the author finds sufficient published literature.
• The review paper should be written with suitable literature, detailed discussion, sufficient data/results to support the interpretation, and persuasive language style.
• A completed review paper should provide substantial new innovative ideas to the readers based on the comparison of published works.

Review papers are widely read by many researchers and it helps to get more citations for author. So, it is important to learn how to write a review paper and find a journal to publish .

Step-by-Step Systematic Procedure to Write a Review Paper

Time needed:  20 days and 7 hours

The systematic procedural steps to write the best review paper are as follows:

Select a suitable area in your research field formulate clear objectives, and prepare the specific research hypotheses that are to be explored.

Designing your research work is an important step for any researcher. Based on the objectives, develop a clear methodology or protocol to review a review paper.

Thorough analysis and understanding of different published works help the author to identify suitable and relevant data/results that will be used to write the paper.

The degree of analysis to evaluate the collected data varies by extensive review. The examination of trends, patterns, ideas, comparisons, and relationships in the study provides deeper knowledge on that area of research .

Interpretation of results is very important for a good review paper. The author should present the discussion systematically without any ambiguity. The results can be presented in descriptive form, tables, and figures. The new insights should have an in-depth discussion of the topic in line with fundamentals. Finally, the author is expected to present the limitations of the existing study with future perspectives.

Sample Review Article Format

Title, abstract, keywords.

Write an effective and suitable title, abstract, and keywords relevant to your review paper. This will maximize the visibility of your paper online for the readers to find your work. Your title and abstract should be clear, concise, appropriate, and informative.

Introduction

Present a detailed introduction to your research which is published in chronological order in your own words. Don’t summarize the published literature. The introduction should encourage the readers to read your paper.

Various topics to discuss the critical issues

Make sure you present a critical discussion, not a descriptive summary of the topic. If there is contradictory research in your area of research, verify to include an element of debate and present both sides of the argument. A good review paper can resolve the conflict between contradictory works.

Conclusion and Future Perspectives

The written review paper should achieve your objectives. Hence, the review paper should leave the reader with a clear understanding of the following questions:

What they can understand from the review paper?

What still remains a requirement of further investigation in the research area?

This can include making suggestions for future scope on the theme as part of your conclusion.

Acknowledgment       

The authors can submit a brief acknowledgment of any financial, instrumentation, and academic support received about research work.

Citing references at appropriate places in the article is necessary and important to avoid plagiarism. Each journal has its referencing style. Therefore, the references need to be listed at the end of the manuscript. The number of references in the review paper is usually higher than in a research paper .

I hope this article will give you a clear idea of how to write a review paper. Please give your valuable comments.

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How to Write a Peer Review

When you write a peer review for a manuscript, what should you include in your comments? What should you leave out? And how should the review be formatted?

This guide provides quick tips for writing and organizing your reviewer report.

Review Outline

Use an outline for your reviewer report so it’s easy for the editors and author to follow. This will also help you keep your comments organized.

Think about structuring your review like an inverted pyramid. Put the most important information at the top, followed by details and examples in the center, and any additional points at the very bottom.

Here’s how your outline might look:

1. Summary of the research and your overall impression

In your own words, summarize what the manuscript claims to report. This shows the editor how you interpreted the manuscript and will highlight any major differences in perspective between you and the other reviewers. Give an overview of the manuscript’s strengths and weaknesses. Think about this as your “take-home” message for the editors. End this section with your recommended course of action.

2. Discussion of specific areas for improvement

It’s helpful to divide this section into two parts: one for major issues and one for minor issues. Within each section, you can talk about the biggest issues first or go systematically figure-by-figure or claim-by-claim. Number each item so that your points are easy to follow (this will also make it easier for the authors to respond to each point). Refer to specific lines, pages, sections, or figure and table numbers so the authors (and editors) know exactly what you’re talking about.

Major vs. minor issues

What’s the difference between a major and minor issue? Major issues should consist of the essential points the authors need to address before the manuscript can proceed. Make sure you focus on what is  fundamental for the current study . In other words, it’s not helpful to recommend additional work that would be considered the “next step” in the study. Minor issues are still important but typically will not affect the overall conclusions of the manuscript. Here are some examples of what would might go in the “minor” category:

• Missing references (but depending on what is missing, this could also be a major issue)
• Technical clarifications (e.g., the authors should clarify how a reagent works)
• Data presentation (e.g., the authors should present p-values differently)
• Typos, spelling, grammar, and phrasing issues

3. Any other points

Confidential comments for the editors.

Some journals have a space for reviewers to enter confidential comments about the manuscript. Use this space to mention concerns about the submission that you’d want the editors to consider before sharing your feedback with the authors, such as concerns about ethical guidelines or language quality. Any serious issues should be raised directly and immediately with the journal as well.

This section is also where you will disclose any potentially competing interests, and mention whether you’re willing to look at a revised version of the manuscript.

Do not use this space to critique the manuscript, since comments entered here will not be passed along to the authors.  If you’re not sure what should go in the confidential comments, read the reviewer instructions or check with the journal first before submitting your review. If you are reviewing for a journal that does not offer a space for confidential comments, consider writing to the editorial office directly with your concerns.

Get this outline in a template

Giving Feedback

Giving feedback is hard. Giving effective feedback can be even more challenging. Remember that your ultimate goal is to discuss what the authors would need to do in order to qualify for publication. The point is not to nitpick every piece of the manuscript. Your focus should be on providing constructive and critical feedback that the authors can use to improve their study.

If you’ve ever had your own work reviewed, you already know that it’s not always easy to receive feedback. Follow the golden rule: Write the type of review you’d want to receive if you were the author. Even if you decide not to identify yourself in the review, you should write comments that you would be comfortable signing your name to.

In your comments, use phrases like “ the authors’ discussion of X” instead of “ your discussion of X .” This will depersonalize the feedback and keep the focus on the manuscript instead of the authors.

General guidelines for effective feedback

• Justify your recommendation with concrete evidence and specific examples.
• Be specific so the authors know what they need to do to improve.
• Be thorough. This might be the only time you read the manuscript.
• Be professional and respectful. The authors will be reading these comments too.
• Remember to say what you liked about the manuscript!

Don’t

• Recommend additional experiments or  unnecessary elements that are out of scope for the study or for the journal criteria.
• Tell the authors exactly how to revise their manuscript—you don’t need to do their work for them.
• Use the review to promote your own research or hypotheses.
• Focus on typos and grammar. If the manuscript needs significant editing for language and writing quality, just mention this in your comments.
• Submit your review without proofreading it and checking everything one more time.

Before and After: Sample Reviewer Comments

Keeping in mind the guidelines above, how do you put your thoughts into words? Here are some sample “before” and “after” reviewer comments

✗ Before

“The authors appear to have no idea what they are talking about. I don’t think they have read any of the literature on this topic.”

✓ After

“The study fails to address how the findings relate to previous research in this area. The authors should rewrite their Introduction and Discussion to reference the related literature, especially recently published work such as Darwin et al.”

“The writing is so bad, it is practically unreadable. I could barely bring myself to finish it.”

“While the study appears to be sound, the language is unclear, making it difficult to follow. I advise the authors work with a writing coach or copyeditor to improve the flow and readability of the text.”

“It’s obvious that this type of experiment should have been included. I have no idea why the authors didn’t use it. This is a big mistake.”

“The authors are off to a good start, however, this study requires additional experiments, particularly [type of experiment]. Alternatively, the authors should include more information that clarifies and justifies their choice of methods.”

Suggested Language for Tricky Situations

You might find yourself in a situation where you’re not sure how to explain the problem or provide feedback in a constructive and respectful way. Here is some suggested language for common issues you might experience.

What you think : The manuscript is fatally flawed. What you could say: “The study does not appear to be sound” or “the authors have missed something crucial”.

What you think : You don’t completely understand the manuscript. What you could say : “The authors should clarify the following sections to avoid confusion…”

What you think : The technical details don’t make sense. What you could say : “The technical details should be expanded and clarified to ensure that readers understand exactly what the researchers studied.”

What you think: The writing is terrible. What you could say : “The authors should revise the language to improve readability.”

What you think : The authors have over-interpreted the findings. What you could say : “The authors aim to demonstrate [XYZ], however, the data does not fully support this conclusion. Specifically…”

What does a good review look like?

Check out the peer review examples at F1000 Research to see how other reviewers write up their reports and give constructive feedback to authors.

Time to Submit the Review!

Be sure you turn in your report on time. Need an extension? Tell the journal so that they know what to expect. If you need a lot of extra time, the journal might need to contact other reviewers or notify the author about the delay.

Tip: Building a relationship with an editor

You’ll be more likely to be asked to review again if you provide high-quality feedback and if you turn in the review on time. Especially if it’s your first review for a journal, it’s important to show that you are reliable. Prove yourself once and you’ll get asked to review again!

• Getting started as a reviewer
• Responding to an invitation
• Reading a manuscript
• Writing a peer review

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

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• CAREER FEATURE
• 04 December 2020
• Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed   Google Scholar

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

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doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

Article   Google Scholar  

Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

Article   PubMed   Google Scholar  

Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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How to write a good scientific review article

Affiliation.

• 1 The FEBS Journal Editorial Office, Cambridge, UK.
• PMID: 35792782
• DOI: 10.1111/febs.16565

Literature reviews are valuable resources for the scientific community. With research accelerating at an unprecedented speed in recent years and more and more original papers being published, review articles have become increasingly important as a means to keep up to date with developments in a particular area of research. A good review article provides readers with an in-depth understanding of a field and highlights key gaps and challenges to address with future research. Writing a review article also helps to expand the writer's knowledge of their specialist area and to develop their analytical and communication skills, amongst other benefits. Thus, the importance of building review-writing into a scientific career cannot be overstated. In this instalment of The FEBS Journal's Words of Advice series, I provide detailed guidance on planning and writing an informative and engaging literature review.

© 2022 Federation of European Biochemical Societies.

Publication types

• Review Literature as Topic*

COMMUNICATION IN THE BIOLOGICAL SCIENCES Department of Biology

LITERATURE REVIEW PAPER

WHAT IS A REVIEW PAPER?

CHOOSING A TOPIC

RESEARCHING A TOPIC

HOW TO WRITE THE PAPER    

The purpose of a review paper is to succinctly review recent progress in a particular topic. Overall, the paper summarizes the current state of knowledge of the topic. It creates an understanding of the topic for the reader by discussing the findings presented in recent research papers .

A review paper is not a "term paper" or book report . It is not merely a report on some references you found. Instead, a review paper synthesizes the results from several primary literature papers to produce a coherent argument about a topic or focused description of a field.

Examples of scientific reviews can be found in:

                Current Opinion in Cell Biology

                Current Opinion in Genetics & Development

                Annual Review of Plant Physiology and Plant Molecular Biology

                Annual Review of Physiology

                Trends in Ecology & Evolution

You should read articles from one or more of these sources to get examples of how your paper should be organized.

Scientists commonly use reviews to communicate with each other and the general public. There are a wide variety of review styles from ones aimed at a general audience (e.g., Scientific American ) to those directed at biologists within a particular subdiscipline (e.g., Annual Review of Physiology ).

A key aspect of a review paper is that it provides the evidence for a particular point of view in a field. Thus, a large focus of your paper should be a description of the data that support or refute that point of view. In addition, you should inform the reader of the experimental techniques that were used to generate the data.

The emphasis of a review paper is interpreting the primary literature on the subject.  You need to read several original research articles on the same topic and make your own conclusions about the meanings of those papers.

Click here for advice on choosing a topic.  

Click here for advice on doing research on your topic.  

HOW TO WRITE THE PAPER

Overview of the Paper: Your paper should consist of four general sections:

Review articles contain neither a materials and methods section nor an abstract.

Organizing the Paper: Use topic headings. Do not use a topic heading that reads, "Body of the paper." Instead the topic headings should refer to the actual concepts or ideas covered in that section.

Example  

What Goes into Each Section:

Home  

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

13.1 Formatting a Research Paper

Learning objectives.

• Identify the major components of a research paper written using American Psychological Association (APA) style.
• Apply general APA style and formatting conventions in a research paper.

In this chapter, you will learn how to use APA style , the documentation and formatting style followed by the American Psychological Association, as well as MLA style , from the Modern Language Association. There are a few major formatting styles used in academic texts, including AMA, Chicago, and Turabian:

• AMA (American Medical Association) for medicine, health, and biological sciences
• APA (American Psychological Association) for education, psychology, and the social sciences
• Chicago—a common style used in everyday publications like magazines, newspapers, and books
• MLA (Modern Language Association) for English, literature, arts, and humanities
• Turabian—another common style designed for its universal application across all subjects and disciplines

While all the formatting and citation styles have their own use and applications, in this chapter we focus our attention on the two styles you are most likely to use in your academic studies: APA and MLA.

If you find that the rules of proper source documentation are difficult to keep straight, you are not alone. Writing a good research paper is, in and of itself, a major intellectual challenge. Having to follow detailed citation and formatting guidelines as well may seem like just one more task to add to an already-too-long list of requirements.

Following these guidelines, however, serves several important purposes. First, it signals to your readers that your paper should be taken seriously as a student’s contribution to a given academic or professional field; it is the literary equivalent of wearing a tailored suit to a job interview. Second, it shows that you respect other people’s work enough to give them proper credit for it. Finally, it helps your reader find additional materials if he or she wishes to learn more about your topic.

Furthermore, producing a letter-perfect APA-style paper need not be burdensome. Yes, it requires careful attention to detail. However, you can simplify the process if you keep these broad guidelines in mind:

• Work ahead whenever you can. Chapter 11 “Writing from Research: What Will I Learn?” includes tips for keeping track of your sources early in the research process, which will save time later on.
• Get it right the first time. Apply APA guidelines as you write, so you will not have much to correct during the editing stage. Again, putting in a little extra time early on can save time later.
• Use the resources available to you. In addition to the guidelines provided in this chapter, you may wish to consult the APA website at http://www.apa.org or the Purdue University Online Writing lab at http://owl.english.purdue.edu , which regularly updates its online style guidelines.

General Formatting Guidelines

This chapter provides detailed guidelines for using the citation and formatting conventions developed by the American Psychological Association, or APA. Writers in disciplines as diverse as astrophysics, biology, psychology, and education follow APA style. The major components of a paper written in APA style are listed in the following box.

These are the major components of an APA-style paper:

Body, which includes the following:

• Headings and, if necessary, subheadings to organize the content
• In-text citations of research sources
• References page

All these components must be saved in one document, not as separate documents.

The title page of your paper includes the following information:

• Title of the paper
• Author’s name
• Name of the institution with which the author is affiliated
• Header at the top of the page with the paper title (in capital letters) and the page number (If the title is lengthy, you may use a shortened form of it in the header.)

List the first three elements in the order given in the previous list, centered about one third of the way down from the top of the page. Use the headers and footers tool of your word-processing program to add the header, with the title text at the left and the page number in the upper-right corner. Your title page should look like the following example.

The next page of your paper provides an abstract , or brief summary of your findings. An abstract does not need to be provided in every paper, but an abstract should be used in papers that include a hypothesis. A good abstract is concise—about one hundred fifty to two hundred fifty words—and is written in an objective, impersonal style. Your writing voice will not be as apparent here as in the body of your paper. When writing the abstract, take a just-the-facts approach, and summarize your research question and your findings in a few sentences.

In Chapter 12 “Writing a Research Paper” , you read a paper written by a student named Jorge, who researched the effectiveness of low-carbohydrate diets. Read Jorge’s abstract. Note how it sums up the major ideas in his paper without going into excessive detail.

Write an abstract summarizing your paper. Briefly introduce the topic, state your findings, and sum up what conclusions you can draw from your research. Use the word count feature of your word-processing program to make sure your abstract does not exceed one hundred fifty words.

Depending on your field of study, you may sometimes write research papers that present extensive primary research, such as your own experiment or survey. In your abstract, summarize your research question and your findings, and briefly indicate how your study relates to prior research in the field.

Margins, Pagination, and Headings

APA style requirements also address specific formatting concerns, such as margins, pagination, and heading styles, within the body of the paper. Review the following APA guidelines.

Use these general guidelines to format the paper:

• Set the top, bottom, and side margins of your paper at 1 inch.
• Use double-spaced text throughout your paper.
• Use a standard font, such as Times New Roman or Arial, in a legible size (10- to 12-point).
• Use continuous pagination throughout the paper, including the title page and the references section. Page numbers appear flush right within your header.
• Section headings and subsection headings within the body of your paper use different types of formatting depending on the level of information you are presenting. Additional details from Jorge’s paper are provided.

Begin formatting the final draft of your paper according to APA guidelines. You may work with an existing document or set up a new document if you choose. Include the following:

• Your title page
• The abstract you created in Note 13.8 “Exercise 1”
• Correct headers and page numbers for your title page and abstract

APA style uses section headings to organize information, making it easy for the reader to follow the writer’s train of thought and to know immediately what major topics are covered. Depending on the length and complexity of the paper, its major sections may also be divided into subsections, sub-subsections, and so on. These smaller sections, in turn, use different heading styles to indicate different levels of information. In essence, you are using headings to create a hierarchy of information.

The following heading styles used in APA formatting are listed in order of greatest to least importance:

• Section headings use centered, boldface type. Headings use title case, with important words in the heading capitalized.
• Subsection headings use left-aligned, boldface type. Headings use title case.
• The third level uses left-aligned, indented, boldface type. Headings use a capital letter only for the first word, and they end in a period.
• The fourth level follows the same style used for the previous level, but the headings are boldfaced and italicized.
• The fifth level follows the same style used for the previous level, but the headings are italicized and not boldfaced.

Visually, the hierarchy of information is organized as indicated in Table 13.1 “Section Headings” .

Table 13.1 Section Headings

A college research paper may not use all the heading levels shown in Table 13.1 “Section Headings” , but you are likely to encounter them in academic journal articles that use APA style. For a brief paper, you may find that level 1 headings suffice. Longer or more complex papers may need level 2 headings or other lower-level headings to organize information clearly. Use your outline to craft your major section headings and determine whether any subtopics are substantial enough to require additional levels of headings.

Working with the document you developed in Note 13.11 “Exercise 2” , begin setting up the heading structure of the final draft of your research paper according to APA guidelines. Include your title and at least two to three major section headings, and follow the formatting guidelines provided above. If your major sections should be broken into subsections, add those headings as well. Use your outline to help you.

Because Jorge used only level 1 headings, his Exercise 3 would look like the following:

Citation Guidelines

In-text citations.

Throughout the body of your paper, include a citation whenever you quote or paraphrase material from your research sources. As you learned in Chapter 11 “Writing from Research: What Will I Learn?” , the purpose of citations is twofold: to give credit to others for their ideas and to allow your reader to follow up and learn more about the topic if desired. Your in-text citations provide basic information about your source; each source you cite will have a longer entry in the references section that provides more detailed information.

In-text citations must provide the name of the author or authors and the year the source was published. (When a given source does not list an individual author, you may provide the source title or the name of the organization that published the material instead.) When directly quoting a source, it is also required that you include the page number where the quote appears in your citation.

This information may be included within the sentence or in a parenthetical reference at the end of the sentence, as in these examples.

Epstein (2010) points out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Here, the writer names the source author when introducing the quote and provides the publication date in parentheses after the author’s name. The page number appears in parentheses after the closing quotation marks and before the period that ends the sentence.

Addiction researchers caution that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (Epstein, 2010, p. 137).

Here, the writer provides a parenthetical citation at the end of the sentence that includes the author’s name, the year of publication, and the page number separated by commas. Again, the parenthetical citation is placed after the closing quotation marks and before the period at the end of the sentence.

As noted in the book Junk Food, Junk Science (Epstein, 2010, p. 137), “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive.”

Here, the writer chose to mention the source title in the sentence (an optional piece of information to include) and followed the title with a parenthetical citation. Note that the parenthetical citation is placed before the comma that signals the end of the introductory phrase.

David Epstein’s book Junk Food, Junk Science (2010) pointed out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Another variation is to introduce the author and the source title in your sentence and include the publication date and page number in parentheses within the sentence or at the end of the sentence. As long as you have included the essential information, you can choose the option that works best for that particular sentence and source.

Citing a book with a single author is usually a straightforward task. Of course, your research may require that you cite many other types of sources, such as books or articles with more than one author or sources with no individual author listed. You may also need to cite sources available in both print and online and nonprint sources, such as websites and personal interviews. Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.2 “Citing and Referencing Techniques” and Section 13.3 “Creating a References Section” provide extensive guidelines for citing a variety of source types.

Writing at Work

APA is just one of several different styles with its own guidelines for documentation, formatting, and language usage. Depending on your field of interest, you may be exposed to additional styles, such as the following:

• MLA style. Determined by the Modern Languages Association and used for papers in literature, languages, and other disciplines in the humanities.
• Chicago style. Outlined in the Chicago Manual of Style and sometimes used for papers in the humanities and the sciences; many professional organizations use this style for publications as well.
• Associated Press (AP) style. Used by professional journalists.

References List

The brief citations included in the body of your paper correspond to the more detailed citations provided at the end of the paper in the references section. In-text citations provide basic information—the author’s name, the publication date, and the page number if necessary—while the references section provides more extensive bibliographical information. Again, this information allows your reader to follow up on the sources you cited and do additional reading about the topic if desired.

The specific format of entries in the list of references varies slightly for different source types, but the entries generally include the following information:

• The name(s) of the author(s) or institution that wrote the source
• The year of publication and, where applicable, the exact date of publication
• The full title of the source
• For books, the city of publication
• For articles or essays, the name of the periodical or book in which the article or essay appears
• For magazine and journal articles, the volume number, issue number, and pages where the article appears
• For sources on the web, the URL where the source is located

The references page is double spaced and lists entries in alphabetical order by the author’s last name. If an entry continues for more than one line, the second line and each subsequent line are indented five spaces. Review the following example. ( Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.3 “Creating a References Section” provides extensive guidelines for formatting reference entries for different types of sources.)

In APA style, book and article titles are formatted in sentence case, not title case. Sentence case means that only the first word is capitalized, along with any proper nouns.

Key Takeaways

• Following proper citation and formatting guidelines helps writers ensure that their work will be taken seriously, give proper credit to other authors for their work, and provide valuable information to readers.
• Working ahead and taking care to cite sources correctly the first time are ways writers can save time during the editing stage of writing a research paper.
• APA papers usually include an abstract that concisely summarizes the paper.
• APA papers use a specific headings structure to provide a clear hierarchy of information.
• In APA papers, in-text citations usually include the name(s) of the author(s) and the year of publication.
• In-text citations correspond to entries in the references section, which provide detailed bibliographical information about a source.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Page Content

Overview of the review report format, the first read-through, first read considerations, spotting potential major flaws, concluding the first reading, rejection after the first reading, before starting the second read-through, doing the second read-through, the second read-through: section by section guidance, how to structure your report, on presentation and style, criticisms & confidential comments to editors, the recommendation, when recommending rejection, additional resources, step by step guide to reviewing a manuscript.

When you receive an invitation to peer review, you should be sent a copy of the paper's abstract to help you decide whether you wish to do the review. Try to respond to invitations promptly - it will prevent delays. It is also important at this stage to declare any potential Conflict of Interest.

The structure of the review report varies between journals. Some follow an informal structure, while others have a more formal approach.

" Number your comments!!! " (Jonathon Halbesleben, former Editor of Journal of Occupational and Organizational Psychology)

Informal Structure

Many journals don't provide criteria for reviews beyond asking for your 'analysis of merits'. In this case, you may wish to familiarize yourself with examples of other reviews done for the journal, which the editor should be able to provide or, as you gain experience, rely on your own evolving style.

Formal Structure

Other journals require a more formal approach. Sometimes they will ask you to address specific questions in your review via a questionnaire. Or they might want you to rate the manuscript on various attributes using a scorecard. Often you can't see these until you log in to submit your review. So when you agree to the work, it's worth checking for any journal-specific guidelines and requirements. If there are formal guidelines, let them direct the structure of your review.

In Both Cases

Whether specifically required by the reporting format or not, you should expect to compile comments to authors and possibly confidential ones to editors only.

Following the invitation to review, when you'll have received the article abstract, you should already understand the aims, key data and conclusions of the manuscript. If you don't, make a note now that you need to feedback on how to improve those sections.

The first read-through is a skim-read. It will help you form an initial impression of the paper and get a sense of whether your eventual recommendation will be to accept or reject the paper.

Keep a pen and paper handy when skim-reading.

Try to bear in mind the following questions - they'll help you form your overall impression:

• What is the main question addressed by the research? Is it relevant and interesting?
• How original is the topic? What does it add to the subject area compared with other published material?
• Is the paper well written? Is the text clear and easy to read?
• Are the conclusions consistent with the evidence and arguments presented? Do they address the main question posed?
• If the author is disagreeing significantly with the current academic consensus, do they have a substantial case? If not, what would be required to make their case credible?
• If the paper includes tables or figures, what do they add to the paper? Do they aid understanding or are they superfluous?

While you should read the whole paper, making the right choice of what to read first can save time by flagging major problems early on.

Editors say, " Specific recommendations for remedying flaws are VERY welcome ."

Examples of possibly major flaws include:

• Drawing a conclusion that is contradicted by the author's own statistical or qualitative evidence
• The use of a discredited method
• Ignoring a process that is known to have a strong influence on the area under study

If experimental design features prominently in the paper, first check that the methodology is sound - if not, this is likely to be a major flaw.

You might examine:

• The sampling in analytical papers
• The sufficient use of control experiments
• The precision of process data
• The regularity of sampling in time-dependent studies
• The validity of questions, the use of a detailed methodology and the data analysis being done systematically (in qualitative research)
• That qualitative research extends beyond the author's opinions, with sufficient descriptive elements and appropriate quotes from interviews or focus groups

Major Flaws in Information

If methodology is less of an issue, it's often a good idea to look at the data tables, figures or images first. Especially in science research, it's all about the information gathered. If there are critical flaws in this, it's very likely the manuscript will need to be rejected. Such issues include:

• Insufficient data
• Unclear data tables
• Contradictory data that either are not self-consistent or disagree with the conclusions
• Confirmatory data that adds little, if anything, to current understanding - unless strong arguments for such repetition are made

If you find a major problem, note your reasoning and clear supporting evidence (including citations).

After the initial read and using your notes, including those of any major flaws you found, draft the first two paragraphs of your review - the first summarizing the research question addressed and the second the contribution of the work. If the journal has a prescribed reporting format, this draft will still help you compose your thoughts.

The First Paragraph

This should state the main question addressed by the research and summarize the goals, approaches, and conclusions of the paper. It should:

• Help the editor properly contextualize the research and add weight to your judgement
• Show the author what key messages are conveyed to the reader, so they can be sure they are achieving what they set out to do
• Focus on successful aspects of the paper so the author gets a sense of what they've done well

The Second Paragraph

This should provide a conceptual overview of the contribution of the research. So consider:

• Is the paper's premise interesting and important?
• Are the methods used appropriate?
• Do the data support the conclusions?

After drafting these two paragraphs, you should be in a position to decide whether this manuscript is seriously flawed and should be rejected (see the next section). Or whether it is publishable in principle and merits a detailed, careful read through.

Even if you are coming to the opinion that an article has serious flaws, make sure you read the whole paper. This is very important because you may find some really positive aspects that can be communicated to the author. This could help them with future submissions.

A full read-through will also make sure that any initial concerns are indeed correct and fair. After all, you need the context of the whole paper before deciding to reject. If you still intend to recommend rejection, see the section "When recommending rejection."

Once the paper has passed your first read and you've decided the article is publishable in principle, one purpose of the second, detailed read-through is to help prepare the manuscript for publication. You may still decide to recommend rejection following a second reading.

" Offer clear suggestions for how the authors can address the concerns raised. In other words, if you're going to raise a problem, provide a solution ." (Jonathon Halbesleben, Editor of Journal of Occupational and Organizational Psychology)

Preparation

To save time and simplify the review:

• Don't rely solely upon inserting comments on the manuscript document - make separate notes
• Try to group similar concerns or praise together
• If using a review program to note directly onto the manuscript, still try grouping the concerns and praise in separate notes - it helps later
• Note line numbers of text upon which your notes are based - this helps you find items again and also aids those reading your review

Now that you have completed your preparations, you're ready to spend an hour or so reading carefully through the manuscript.

As you're reading through the manuscript for a second time, you'll need to keep in mind the argument's construction, the clarity of the language and content.

With regard to the argument’s construction, you should identify:

• Any places where the meaning is unclear or ambiguous
• Any factual errors
• Any invalid arguments

You may also wish to consider:

• Does the title properly reflect the subject of the paper?
• Does the abstract provide an accessible summary of the paper?
• Do the keywords accurately reflect the content?
• Is the paper an appropriate length?
• Are the key messages short, accurate and clear?

Not every submission is well written. Part of your role is to make sure that the text’s meaning is clear.

Editors say, " If a manuscript has many English language and editing issues, please do not try and fix it. If it is too bad, note that in your review and it should be up to the authors to have the manuscript edited ."

If the article is difficult to understand, you should have rejected it already. However, if the language is poor but you understand the core message, see if you can suggest improvements to fix the problem:

• Are there certain aspects that could be communicated better, such as parts of the discussion?
• Should the authors consider resubmitting to the same journal after language improvements?
• Would you consider looking at the paper again once these issues are dealt with?

On Grammar and Punctuation

Your primary role is judging the research content. Don't spend time polishing grammar or spelling. Editors will make sure that the text is at a high standard before publication. However, if you spot grammatical errors that affect clarity of meaning, then it's important to highlight these. Expect to suggest such amendments - it's rare for a manuscript to pass review with no corrections.

A 2010 study of nursing journals found that 79% of recommendations by reviewers were influenced by grammar and writing style (Shattel, et al., 2010).

1. The Introduction

A well-written introduction:

• Sets out the argument
• Summarizes recent research related to the topic
• Highlights gaps in current understanding or conflicts in current knowledge
• Establishes the originality of the research aims by demonstrating the need for investigations in the topic area
• Gives a clear idea of the target readership, why the research was carried out and the novelty and topicality of the manuscript

Originality and Topicality

Originality and topicality can only be established in the light of recent authoritative research. For example, it's impossible to argue that there is a conflict in current understanding by referencing articles that are 10 years old.

Authors may make the case that a topic hasn't been investigated in several years and that new research is required. This point is only valid if researchers can point to recent developments in data gathering techniques or to research in indirectly related fields that suggest the topic needs revisiting. Clearly, authors can only do this by referencing recent literature. Obviously, where older research is seminal or where aspects of the methodology rely upon it, then it is perfectly appropriate for authors to cite some older papers.

Editors say, "Is the report providing new information; is it novel or just confirmatory of well-known outcomes ?"

It's common for the introduction to end by stating the research aims. By this point you should already have a good impression of them - if the explicit aims come as a surprise, then the introduction needs improvement.

2. Materials and Methods

Academic research should be replicable, repeatable and robust - and follow best practice.

Replicable Research

This makes sufficient use of:

• Control experiments
• Repeated analyses
• Repeated experiments

These are used to make sure observed trends are not due to chance and that the same experiment could be repeated by other researchers - and result in the same outcome. Statistical analyses will not be sound if methods are not replicable. Where research is not replicable, the paper should be recommended for rejection.

Repeatable Methods

These give enough detail so that other researchers are able to carry out the same research. For example, equipment used or sampling methods should all be described in detail so that others could follow the same steps. Where methods are not detailed enough, it's usual to ask for the methods section to be revised.

Robust Research

This has enough data points to make sure the data are reliable. If there are insufficient data, it might be appropriate to recommend revision. You should also consider whether there is any in-built bias not nullified by the control experiments.

Best Practice

During these checks you should keep in mind best practice:

• Standard guidelines were followed (e.g. the CONSORT Statement for reporting randomized trials)
• The health and safety of all participants in the study was not compromised
• Ethical standards were maintained

If the research fails to reach relevant best practice standards, it's usual to recommend rejection. What's more, you don't then need to read any further.

3. Results and Discussion

This section should tell a coherent story - What happened? What was discovered or confirmed?

Certain patterns of good reporting need to be followed by the author:

• They should start by describing in simple terms what the data show
• They should make reference to statistical analyses, such as significance or goodness of fit
• Once described, they should evaluate the trends observed and explain the significance of the results to wider understanding. This can only be done by referencing published research
• The outcome should be a critical analysis of the data collected

Discussion should always, at some point, gather all the information together into a single whole. Authors should describe and discuss the overall story formed. If there are gaps or inconsistencies in the story, they should address these and suggest ways future research might confirm the findings or take the research forward.

4. Conclusions

This section is usually no more than a few paragraphs and may be presented as part of the results and discussion, or in a separate section. The conclusions should reflect upon the aims - whether they were achieved or not - and, just like the aims, should not be surprising. If the conclusions are not evidence-based, it's appropriate to ask for them to be re-written.

5. Information Gathered: Images, Graphs and Data Tables

If you find yourself looking at a piece of information from which you cannot discern a story, then you should ask for improvements in presentation. This could be an issue with titles, labels, statistical notation or image quality.

Where information is clear, you should check that:

• The results seem plausible, in case there is an error in data gathering
• The trends you can see support the paper's discussion and conclusions
• There are sufficient data. For example, in studies carried out over time are there sufficient data points to support the trends described by the author?

You should also check whether images have been edited or manipulated to emphasize the story they tell. This may be appropriate but only if authors report on how the image has been edited (e.g. by highlighting certain parts of an image). Where you feel that an image has been edited or manipulated without explanation, you should highlight this in a confidential comment to the editor in your report.

6. List of References

You will need to check referencing for accuracy, adequacy and balance.

Where a cited article is central to the author's argument, you should check the accuracy and format of the reference - and bear in mind different subject areas may use citations differently. Otherwise, it's the editor’s role to exhaustively check the reference section for accuracy and format.

You should consider if the referencing is adequate:

• Are important parts of the argument poorly supported?
• Are there published studies that show similar or dissimilar trends that should be discussed?
• If a manuscript only uses half the citations typical in its field, this may be an indicator that referencing should be improved - but don't be guided solely by quantity
• References should be relevant, recent and readily retrievable

Check for a well-balanced list of references that is:

• Helpful to the reader
• Fair to competing authors
• Not over-reliant on self-citation
• Gives due recognition to the initial discoveries and related work that led to the work under assessment

You should be able to evaluate whether the article meets the criteria for balanced referencing without looking up every reference.

7. Plagiarism

By now you will have a deep understanding of the paper's content - and you may have some concerns about plagiarism.

Identified Concern

If you find - or already knew of - a very similar paper, this may be because the author overlooked it in their own literature search. Or it may be because it is very recent or published in a journal slightly outside their usual field.

You may feel you can advise the author how to emphasize the novel aspects of their own study, so as to better differentiate it from similar research. If so, you may ask the author to discuss their aims and results, or modify their conclusions, in light of the similar article. Of course, the research similarities may be so great that they render the work unoriginal and you have no choice but to recommend rejection.

"It's very helpful when a reviewer can point out recent similar publications on the same topic by other groups, or that the authors have already published some data elsewhere ." (Editor feedback)

Suspected Concern

If you suspect plagiarism, including self-plagiarism, but cannot recall or locate exactly what is being plagiarized, notify the editor of your suspicion and ask for guidance.

Most editors have access to software that can check for plagiarism.

Editors are not out to police every paper, but when plagiarism is discovered during peer review it can be properly addressed ahead of publication. If plagiarism is discovered only after publication, the consequences are worse for both authors and readers, because a retraction may be necessary.

For detailed guidelines see COPE's Ethical guidelines for reviewers and Wiley's Best Practice Guidelines on Publishing Ethics .

8. Search Engine Optimization (SEO)

After the detailed read-through, you will be in a position to advise whether the title, abstract and key words are optimized for search purposes. In order to be effective, good SEO terms will reflect the aims of the research.

A clear title and abstract will improve the paper's search engine rankings and will influence whether the user finds and then decides to navigate to the main article. The title should contain the relevant SEO terms early on. This has a major effect on the impact of a paper, since it helps it appear in search results. A poor abstract can then lose the reader's interest and undo the benefit of an effective title - whilst the paper's abstract may appear in search results, the potential reader may go no further.

So ask yourself, while the abstract may have seemed adequate during earlier checks, does it:

• Do justice to the manuscript in this context?
• Highlight important findings sufficiently?
• Present the most interesting data?

Editors say, " Does the Abstract highlight the important findings of the study ?"

If there is a formal report format, remember to follow it. This will often comprise a range of questions followed by comment sections. Try to answer all the questions. They are there because the editor felt that they are important. If you're following an informal report format you could structure your report in three sections: summary, major issues, minor issues.

• Give positive feedback first. Authors are more likely to read your review if you do so. But don't overdo it if you will be recommending rejection
• Briefly summarize what the paper is about and what the findings are
• Try to put the findings of the paper into the context of the existing literature and current knowledge
• Indicate the significance of the work and if it is novel or mainly confirmatory
• Indicate the work's strengths, its quality and completeness
• State any major flaws or weaknesses and note any special considerations. For example, if previously held theories are being overlooked

Major Issues

• Are there any major flaws? State what they are and what the severity of their impact is on the paper
• Has similar work already been published without the authors acknowledging this?
• Are the authors presenting findings that challenge current thinking? Is the evidence they present strong enough to prove their case? Have they cited all the relevant work that would contradict their thinking and addressed it appropriately?
• If major revisions are required, try to indicate clearly what they are
• Are there any major presentational problems? Are figures & tables, language and manuscript structure all clear enough for you to accurately assess the work?
• Are there any ethical issues? If you are unsure it may be better to disclose these in the confidential comments section

Minor Issues

• Are there places where meaning is ambiguous? How can this be corrected?
• Are the correct references cited? If not, which should be cited instead/also? Are citations excessive, limited, or biased?
• Are there any factual, numerical or unit errors? If so, what are they?
• Are all tables and figures appropriate, sufficient, and correctly labelled? If not, say which are not

Your review should ultimately help the author improve their article. So be polite, honest and clear. You should also try to be objective and constructive, not subjective and destructive.

You should also:

• Write clearly and so you can be understood by people whose first language is not English
• Avoid complex or unusual words, especially ones that would even confuse native speakers
• Number your points and refer to page and line numbers in the manuscript when making specific comments
• If you have been asked to only comment on specific parts or aspects of the manuscript, you should indicate clearly which these are
• Treat the author's work the way you would like your own to be treated

Most journals give reviewers the option to provide some confidential comments to editors. Often this is where editors will want reviewers to state their recommendation - see the next section - but otherwise this area is best reserved for communicating malpractice such as suspected plagiarism, fraud, unattributed work, unethical procedures, duplicate publication, bias or other conflicts of interest.

However, this doesn't give reviewers permission to 'backstab' the author. Authors can't see this feedback and are unable to give their side of the story unless the editor asks them to. So in the spirit of fairness, write comments to editors as though authors might read them too.

Reviewers should check the preferences of individual journals as to where they want review decisions to be stated. In particular, bear in mind that some journals will not want the recommendation included in any comments to authors, as this can cause editors difficulty later - see Section 11 for more advice about working with editors.

You will normally be asked to indicate your recommendation (e.g. accept, reject, revise and resubmit, etc.) from a fixed-choice list and then to enter your comments into a separate text box.

Recommending Acceptance

If you're recommending acceptance, give details outlining why, and if there are any areas that could be improved. Don't just give a short, cursory remark such as 'great, accept'. See Improving the Manuscript

Recommending Revision

Where improvements are needed, a recommendation for major or minor revision is typical. You may also choose to state whether you opt in or out of the post-revision review too. If recommending revision, state specific changes you feel need to be made. The author can then reply to each point in turn.

Some journals offer the option to recommend rejection with the possibility of resubmission – this is most relevant where substantial, major revision is necessary.

What can reviewers do to help? " Be clear in their comments to the author (or editor) which points are absolutely critical if the paper is given an opportunity for revisio n." (Jonathon Halbesleben, Editor of Journal of Occupational and Organizational Psychology)

Recommending Rejection

If recommending rejection or major revision, state this clearly in your review (and see the next section, 'When recommending rejection').

Where manuscripts have serious flaws you should not spend any time polishing the review you've drafted or give detailed advice on presentation.

Editors say, " If a reviewer suggests a rejection, but her/his comments are not detailed or helpful, it does not help the editor in making a decision ."

In your recommendations for the author, you should:

• Give constructive feedback describing ways that they could improve the research
• Keep the focus on the research and not the author. This is an extremely important part of your job as a reviewer
• Avoid making critical confidential comments to the editor while being polite and encouraging to the author - the latter may not understand why their manuscript has been rejected. Also, they won't get feedback on how to improve their research and it could trigger an appeal

Remember to give constructive criticism even if recommending rejection. This helps developing researchers improve their work and explains to the editor why you felt the manuscript should not be published.

" When the comments seem really positive, but the recommendation is rejection…it puts the editor in a tough position of having to reject a paper when the comments make it sound like a great paper ." (Jonathon Halbesleben, Editor of Journal of Occupational and Organizational Psychology)

Visit our Wiley Author Learning and Training Channel for expert advice on peer review.

Watch the video, Ethical considerations of Peer Review

Get science-backed answers as you write with Paperpal's Research feature

What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 
• How to write a good literature review 
• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

• Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 
• Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 
• Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 
• Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 
• Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 
• Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

How to write a good literature review

Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. 

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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Types of APA Papers

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

Note:  This page reflects the latest version of the APA Publication Manual (i.e., APA 7), which released in October 2019. The equivalent resource for the older APA 6 style  can be found here .

There are two common types of papers written in fields using APA Style: the literature review and the experimental report. Each has unique requirements concerning the sections that must be included in the paper.

Literature review

A literature review is a critical summary of what the scientific literature says about your specific topic or question. Often student research in APA fields falls into this category. Your professor might ask you to write this kind of paper to demonstrate your familiarity with work in the field pertinent to the research you hope to conduct.

A literature review typically contains the following sections:

• Introduction section
• List of references

Some instructors may also want you to write an abstract for a literature review, so be sure to check with them when given an assignment. Also, the length of a literature review and the required number of sources will vary based on course and instructor preferences.

NOTE: A literature review and an annotated bibliography are not synonymous. If you are asked to write an annotated bibliography, you should consult the Publication Manual of the American Psychological Association for the APA Format for Annotated Bibliographies.

Experimental report

In many of the social sciences, you will be asked to design and conduct your own experimental research. If so, you will need to write up your paper using a structure that is more complex than that used for just a literature review. We have a complete resource devoted to writing an experimental report in the field of psychology here .

This structure follows the scientific method, but it also makes your paper easier to follow by providing those familiar cues that help your reader efficiently scan your information for:

• Why the topic is important (covered in your introduction)
• What the problem is (also covered in your introduction)
• What you did to try to solve the problem (covered in your methods section)
• What you found (covered in your results section)
• What you think your findings mean (covered in your discussion section)

Thus an experimental report typically includes the following sections.

• Introduction
• Appendices(if necessary)
• Tables and/or figures (if necessary)

Make sure to check the guidelines for your assignment or any guidelines that have been given to you by an editor of a journal before you submit a manuscript containing the sections listed above.

As with the literature review, the length of this report may vary by course or by journal, but most often it will be determined by the scope of the research conducted.

Other papers

If you are writing a paper that fits neither of these categories, follow the guidelines about General Format , consult your instructor, or look up advice in the Publication Manual of the American Psychological Association .

When submitting a manuscript to a journal, make sure you follow the guidelines described in the submission policies of that publication, and include as many sections as you think are applicable to presenting your material. Remember to keep your audience in mind as you are making this decision. If certain information is particularly pertinent for conveying your research, then ensure that there is a section of your paper that adequately addresses that information.

• Open access
• 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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This paper is in the following e-collection/theme issue:

Published on 29.4.2024 in Vol 8 (2024)

Attributes, Quality, and Downloads of Dementia-Related Mobile Apps for Patients With Dementia and Their Caregivers: App Review and Evaluation Study

Authors of this article:

Original Paper

• Tzu Han Chen 1   ; 
• Shin-Da Lee 2 , PhD   ; 
• Wei-Fen Ma 3, 4 , PhD  

1 PhD Program for Health Science and Industry, China Medical University, Taichung, Taiwan

2 PhD Program in Healthcare Science, Department of Physical Therapy, China Medical University, Taichung, Taiwan

3 PhD Program in Healthcare Science, School of Nursing, China Medical University, Taichung, Taiwan

4 Department of Nursing, China Medical University Hospital, Taichung, Taiwan

Corresponding Author:

Wei-Fen Ma, PhD

PhD Program in Healthcare Science

School of Nursing

China Medical University

No 100, Sec 1, Jingmao Road

Beitun District

Taichung, 406040

Phone: 886 4 22053366 ext 7107

Fax:886 4 22053748

Email: [email protected]

Background: The adoption of mobile health (mHealth) apps among older adults (>65 years) is rapidly increasing. However, use of such apps has not been fully effective in supporting people with dementia and their caregivers in their daily lives. This is mainly attributed to the heterogeneous quality of mHealth apps, highlighting the need for improved app quality in the development of dementia-related mHealth apps.

Objective: The aims of this study were (1) to assess the quality and content of mobile apps for dementia management and (2) to investigate the relationship between app quality and download numbers.

Methods: We reviewed dementia-related mHealth apps available in the Google Play Store and Apple App Store in Taiwan. The identified mobile apps were stratified according to a random sampling approach and evaluated by five independent reviewers with sufficient training and proficiency in the field of mHealth and the related health care sector. App quality was scored according to the user version of the Mobile Application Rating Scale. A correlation analysis was then performed between the app quality score and number of app downloads.

Results: Among the 17 apps that were evaluated, only one was specifically designed to provide dementia-related education. The mean score for the overall app quality was 3.35 (SD 0.56), with the engagement (mean 3.04, SD 0.82) and information (mean 3.14, SD 0.88) sections of the scale receiving the lowest ratings. Our analyses showed clear differences between the top three– and bottom three–rated apps, particularly in the entertainment and interest subsections of the engagement category where the ratings ranged from 1.4 to 5. The top three apps had a common feature in their interface, which included memory, attention, focus, calculation, and speed-training games, whereas the apps that received lower ratings were found to be deficient in providing adequate information. Although there was a correlation between the number of downloads (5000 or more) and app quality (t 15 =4.087, P <.001), this may not be a significant determinant of the app’s perceived impact.

Conclusions: The quality of dementia-related mHealth apps is highly variable. In particular, our results show that the top three quality apps performed well in terms of engagement and information, and they all received more than 5000 downloads. The findings of this study are limited due to the small sample size and possibility of disregarding exceptional occurrences. Publicly available expert ratings of mobile apps could help people with dementia and their caregivers choose a quality mHealth app.

Introduction

The global aging population is experiencing an astonishing surge, which will inevitably result in a significant rise in the prevalence of dementia [ 1 ]. Consequently, it has become crucial to identify efficacious strategies to support people affected by dementia and enhance the well-being of their caregivers [ 2 ]. In addition, numerous studies have shown that mobile health (mHealth) apps can effectively reduce medical costs and improve quality of life for middle-aged and older adults, especially after COVID-19 [ 3 , 4 ].

The use of technology among older adults (aged >65 years) has triggered noteworthy transformations in health care provision [ 5 ]. An area where technology has proven especially valuable is in the realm of dementia management, with mHealth apps dominating the forefront of this field [ 6 ]. In addition, the UK government has shown support for the advancement of intelligent assistive technology for individuals with dementia [ 7 ]. This includes endorsing the development of mHealth apps specifically tailored to patients with early-stage dementia and their caregivers [ 8 ]. These apps are believed to have significant potential in aiding cognitive function and facilitating self-care among those living with dementia [ 9 ].

However, the constant emergence of mHealth apps has made it challenging for both patients with dementia and their caregivers to differentiate, evaluate, and use mHealth apps that promote healthy behaviors [ 10 , 11 ]. Therefore, information pertaining to dementia-related mHealth apps and their functionalities should be effectively evaluated and made publicly available.

There is significant heterogeneity in the quality of dementia-related mHealth apps [ 12 ], and most studies assessing app quality have used criteria that focused on general characteristics that could be assessed without downloading or using the app itself [ 13 , 14 ]. Therefore, there is a need for a human-centered, multidimensional measure that includes usability components and relatively more domains to identify high-quality mHealth apps [ 15 ]. Ideally, better features and functionality would drive high-quality apps; however, efforts to identify the differences between high- and low-quality apps have been hampered by scarce research.

Moreover, the factors that contribute to the popularity of specific mHealth apps remain largely unknown, although there is some evidence of a relationship between an app’s star rating and its number of downloads [ 16 ]. However, few studies have evaluated dementia-related mHealth apps to date. Therefore, the specific metrics of app quality that are likely to be associated with a higher number of downloads remain to be identified.

This study had several goals. The first goal was to analyze the content of mobile apps for people with dementia and their caregivers across different categories. The second goal was to assess the quality of individual apps using the user version of the Mobile Application Rating Scale (uMARS). The third objective was to perform a comparative analysis of the highest- and lowest-quality dementia-related mHealth apps, with the broader goal of establishing guidelines to facilitate future app development. Finally, the study aimed to explore the correlation between app quality and downloads. This was done to help identify the gaps in the currently available dementia-related mHealth apps and to provide recommendations for patients with dementia and their caregivers on how to select high-quality apps.

Search Strategy and Inclusion Criteria

Apps were identified from the Taiwan Apple App Store and Google Play Store. Between July 2022 and November 2022, the following search terms (in Mandarin and English) were used in the app stores: dementia, cognitive dysfunction, dementia caregiver, Alzheimer disease, dementia care, cognitive games, and memory games. The screening criteria and process are illustrated in Figure 1 .

Apps were included if they met all of the following inclusion criteria: (1) exists in the Google Play Store for Android mobile devices and the App Store for Apple mobile devices; (2) addresses daily-life topics related to neurocognitive disorders [ 17 ], and (3) was purposefully developed with the primary goal of supporting patients or caregivers (including health care workers) with the topic of mild cognitive impairment; (4) can be downloaded and used for free; (5) mainly uses Mandarin or the English version can be translated into Mandarin and is easy to understand; and (6) has been updated within the last 5 years.

Stratified Random Sampling of Apps by Average Download Numbers

In November 2022, searches were conducted on the two platforms to find apps that met the above criteria. Of the 407 apps found, 332 were deemed ineligible after screening ( Figure 1 ). The remaining 75 apps were thoroughly screened, resulting in 52 apps included for preliminary evaluation. Since the length of time an app has been available on a platform can affect its number of downloads, we calculated the ratio of download numbers with respect to time on the platform. Additionally, to consider uneven allocation and lack of continuity in stratification, the apps were sorted according to the ratio of downloads relative to the number of days since the release date on the platform. Thus, the average number of downloads was calculated as the total number of downloads/number of days on platform since the release date. The apps were then ranked according to the average number of downloads in ascending order, and we randomly selected 1 out of every 3 apps for a total of 17 apps that were subject to detailed quality assessment and review.

General Characteristics and Classification

Each app was used by two authors (THC and WFM) independently. According to their content subcategory, the selected apps were categorized into four different types using the guidelines provided by the National Institute for Health and Care Excellence and the National Health Service in the United Kingdom [ 18 , 19 ]. Any conflicts in app classification were adjudicated by discussion between the two reviewers regarding each domain within the extraction form to reach consensus. Details on the main characteristics and comments of the included apps are provided in Multimedia Appendix 1 .

mHealth App Quality Evaluation

The uMARS is a tool that can be used to evaluate the quality of mHealth apps, including four objective subdomains: engagement, functionality, esthetics, and information. There is also a domain for subjective quality and another for perceived impact. Stoyanov et al [ 20 ] developed the uMARS in 2016, which showed excellent internal consistency (Cronbach α=0.90). The uMARS scores are rated on a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”).

The objective quality score is calculated as the average of the scores of the four dimensions. Engagement is defined as fun, interesting, customizable, interactive, and has prompts (eg, sends alerts, messages, reminders, feedback, allows sharing). Functionality refers to overall app functioning, easy to learn, navigation, flow logic, and gestural design of the app. Esthetics refers to the graphic design, overall visual appeal, color scheme, and stylistic consistency. Finally, the information domain assesses whether the app contains high-quality information (eg, text, feedback, measures, and references from a credible source). The subjective quality score reflects the rater’s personal interest in the app. The final uMARS subscale includes 6 items designed to assess the perceived impact of the app on the user’s awareness, knowledge, attitude, intention to change, help-seeking, and likelihood to change the target health behavior.

Reviewer Recruitment and Selection

Reviewers recruited for this study were required to have a professional background in clinical treatment, the health care industry, or information engineering. Additionally, they were required to have at least 3 years of work experience in elderly health care or health technology–related fields, as well as experience using digital mobile devices. Exclusion criteria included no relevant work experience in elderly health care or health technology–related fields in the past 5 years.

Five reviewers were recruited as an interdisciplinary group of experts. The initial reviewer possessed knowledge and had experience in creating a content management system for a dementia management app. The second reviewer was a health informatics researcher with sufficient training and expertise in the relevant health care technology fields focused on dementia. The third reviewer also had extensive experience in dementia and in the mHealth industry. The fourth reviewer was a psychiatric nurse with experience in caring for older adults along with clinical experience in dementia. The final reviewer was a nurse practitioner who has been providing care for older adults and patients with dementia for over a decade.

Evaluation Process

Each of the apps was assessed by the five reviewers and the evaluation process was conducted between December 17, 2022, and January 3, 2023. All 17 apps can be found on the Android platform; hence, the apps were reviewed when running on the same Android tablet. The experts were blinded to the download numbers, year, and country of development of the apps, and they were not allowed to discuss their assessments with each other to ensure independence in their ratings. We ensured an equal distribution of app assessments in each round by applying a ratio that took into account the download-to-time axis. Furthermore, each reviewer allocated a minimum of 30 minutes and a maximum of 1 hour to thoroughly evaluate the included apps.

Ethical Considerations

The study received ethical approval from the ethics committee of China Medical Hospital, Taiwan, on November 8, 2022 (approval number: CMUH111-REC2-151) and was conducted according to the guidelines of the Declaration of Helsinki.

The experts in this study were not compelled to take part and had the freedom to determine their involvement. Additionally, they possessed the ability to discontinue their participation at any juncture, without being required to supply a justification for their decision.

This study utilized legally obtained publicly available information, and it was ensured that the use of information aligns with its intended public knowledge purpose. Furthermore, data collected from research and expert evaluations are stored on a hard drive and encrypted. The evaluation process was fully anonymous, with no face-to-face interactions among experts, and the evaluation of the app was a non-nominal, noninteractive, and noninvasive study. Relevant original data regarding this research will be preserved for at least 3 years after the execution period, securely locked in the principal investigator’s office cabinet.

The clinical trial protocol developed by the research institute stipulates that in the event of adverse reactions resulting in damages, China Medical University Hospital is responsible for providing compensation. Nonetheless, adverse reactions explicitly disclosed in the informed consent form signed by the experts are not eligible for compensation. This study was not covered by liability insurance and the per-expert evaluation cost was US $170.

Statistical Analysis

The number and proportion of information displayed in the apps, including the country of app development, download number, and app type, were summarized using descriptive statistics. The uMARS scores, along with the scores for each domain and subscale, are presented as the mean and SD. The t test was used to examine the association between downloads and each domain of the uMARS. Statistical analyses were conducted using IBM SPSS Statistics v28 (IBM Corp). We considered P <.05 to indicate statistical significance in all analyses.

App Attributes

The apps were primarily developed in the United States, and 11 out of the 17 dementia-related mobile apps were downloaded less than 5000 times. Among the 17 apps, 8 were classified as those designed to improve clinical outcomes from established treatment pathways through behavior change, and for enhancement of patient adherence and compliance with treatment; 5 were designed as standalone digital game therapeutics; 3 were classified for supporting clinical diagnosis and/or decision-making; and 1 app was primarily designed to provide disease-related education ( Table 1 ).

App Quality Assessment by Interdisciplinary Experts

There was a notable level of agreement or correlation among the reviewers in their app evaluations, as indicated by the Kendall W statistic of 0.143, which was significant at P =.05.

Overall, the mean app quality score was 3.35 (SD 0.56), which ranged from 2.25 (worst-rated app) to 4.07 (best-rated app). For engagement, the mean score was 3.04 (SD 0.81). Furthermore, functionality had the highest mean score of 3.76 (SD 0.38) and showed the smallest variation in minimum and maximum scores among the apps evaluated. In other words, these apps were considered to have relatively high levels of functionality and usability by the interdisciplinary expert reviewers. The esthetic quality of the interface received a mean score of 3.45 (SD 0.65), indicating that visual design elements such as button size, icon clarity, and content arrangement were perceived as being well organized. Additionally, the information domain received a mean score of 3.14 (SD 0.88), suggesting that the presentation and accessibility of information on the screen could be improved. Multimedia Appendix 2 provides the complete details of app quality scores.

Top Three and Bottom Three Performers in App Quality Score

The apps ranked in the top three positions according to app quality scores included Memorado Brain Games, NeuroNation-Brain Training & Brain Games, and Brain Track. The common characteristic among these apps is that their interface consists of training games focused on memory, attention, concentration, calculation, and speed. Conversely, Alz Test, American Caregiver Association, and Dementia and Me ranked in the bottom three; these three apps performed poorly on both engagement and information.

The overall scores for each item for the top three and bottom three apps are provided in Table 2 . The functionality domain received the highest average ratings, particularly for gestural design, navigation, and performance. The largest discrepancies in app quality ratings between the top three and bottom three apps were found in the areas of entertainment and interest, where the scores ranged from 1.4 (worst-rated app) to 5 (best-rated app). Similarly, in the subscale of perceived impact, there was a significant difference in attitude, with ratings ranging from 1.2 (worst-rated app) to 4.2 (best-rated app).

a N/A: not applicable.

Association Between Downloads and Quality of Mobile Apps

The Connectivity in Digital Health survey of global mHealth apps reported that 55% of the apps available on the Google Play store, Apple App Store, Windows Phone Store, Amazon Appstore, and Blackberry World had fewer than 5000 total downloads [ 21 ]. Therefore, the 17 apps included in our study were divided into two subgroups based on the total number of downloads. The first subset consisted of 6 apps with more than 5000 total downloads, representing 35.3% of all apps. The mean app quality score for this subgroup was significantly higher than that of the group of apps with less than 5000 downloads ( Table 3 ). In addition, apps with more than 5000 downloads generally had higher scores for each domain. However, neither information nor perceived impact scores were significantly correlated with the number of downloads ( Table 3 ).

a uMARS: user version of the Mobile Application Rating Scale.

Principal Findings

According to our results, there was only one included app that primarily focused on delivering dementia-related education. Furthermore, the top three quality apps were all classified as the main app type, as they all served as standalone digital game therapeutics. In general, the dementia-related mHealth apps were of moderate quality with a common characteristic of high functionality. Nonetheless, these apps exhibited poor performance in engagement and the credibility of information domain. Although we found a correlation between the number of downloads and app quality, this may not be a significant determinant of the information provided and the app’s perceived impact.

Comparison With Prior Work

mHealth apps offer a new way to support people with dementia and their caregivers [ 22 ]. However, previous studies have pointed out that the scientific literature on the design and evaluation of web- and mobile-based health apps remains scarce [ 23 , 24 ]. To address this issue, our study directly assessed the app type in a practical setting and found the lack of a dementia management app that delivers disease-related education. A randomized controlled trial indicated that mHealth apps can be of educational value to patients by providing structured disease and treatment-related education; therefore, future app developers can focus on increasing the availability of this app type with educational value [ 25 ].

A previous study suggested that research collaboration between health care and software engineering experts could help advance our knowledge of app functionality and effectiveness [ 16 ]. Therefore, we established a panel of experts to obtain accurate results on the quality of currently available dementia-related mHealth apps and further identified their subjective quality and perceived impact. The pattern of high functionality and low information quality is in accordance with the findings of other studies on mobile apps designed for older adults [ 26 ]. Additionally, the inadequacy of credibility was associated with several risks, particularly in the areas of self-diagnosis, prevention, and health promotion [ 27 ].

High-quality mHealth apps offer self-management features, relaxation, recreation, and trustworthy information [ 28 , 29 ]. The uMARS consists of elements of usability and a broader range of areas that are used in the assessment of mHealth apps with superior quality. Notably, a consensus was reached among the reviewers in both the engagement and esthetics domains. However, there was no correlation or similarity among reviewers with respect to assessments on functionality and information of the apps. This discrepancy may be due to the different backgrounds of the reviewers [ 30 ]; health care providers may perceive the app’s information as inadequate, whereas experienced developers of dementia apps may find its functionality to be lacking.

Currently, little is known about why some health apps become popular and others do not, and researchers have demonstrated that the number of downloads on app marketplaces does not correlate with clinical utility or validity for mental health apps [ 31 ]. A study from the Netherlands and Portugal identified the predictors that might influence the number of downloads for urology apps [ 32 ]. However, there is little research on the predictors of app downloads for dementia-related mHealth apps in the PubMed database. Hence, to gain a more comprehensive understanding, the apps were stratified using a random sampling approach. Due to the different themes of mHealth apps, our study found a positive relationship between app quality and number of downloads. Finally, the download number does only seem to be a limited orientation aid for the selection of an mHealth app, and future studies should consider this aspect.

Limitations

This study has several limitations. Initially, the search for mobile apps was conducted within a limited time frame and focused on apps that had been updated within the last 5 years. As such, the study fell short with respect to establishing causal relationships. In addition, rapidly expanding and ever-changing mobile app marketplaces are facing significant challenges in keeping pace with the dynamic landscape; hence, some of the apps evaluated in this study may have since changed or new alternatives may have been developed. Furthermore, the search for mobile apps was confined to app stores in Taiwan, which may not accurately represent app offerings in other countries due to regional disparities in developers’ decisions regarding app availability.

Previous research indicated that the cost associated with using mHealth apps acts as a major obstacle for older individuals when it comes to embracing mobile technologies [ 9 , 33 ]. Furthermore, a recent study discovered that 96% of mHealth apps that are accessible on the Chinese market can be downloaded without cost [ 34 ]. Consequently, one-quarter of the apps would have been overlooked if they required payment. Nonetheless, it is possible that within this group of paid apps, there may have been some high-quality apps that were unintentionally excluded from consideration.

Additionally, the stratification method represents both less popular and highly downloaded apps, mirroring real-world data [ 21 ]. However, this method resulted in a smaller sample size, which could potentially lead to some superior apps being overlooked by chance. With only 17 apps remaining for evaluation, it is possible that there may not have been sufficient statistical power to establish a significant relationship between app quality and download frequency.

Finally, to ensure a rigorous evaluation of the app content, experts from different fields were recruited to review the apps. However, the limited number of reviewers could potentially influence the results of the study, and the degree of agreement may not be strong given that the reviewers are from different disciplines and the time they allocated to evaluate each app could potentially impact the reliability of agreement.

Despite these limitations, this study helps to fill the gap in the evaluation of dementia-related mobile apps. The results can still be used to guide the selection of such apps in Taiwan and possibly other regions with similar app marketplaces, while also highlighting the need for ongoing evaluation of mobile apps for dementia care.

Conclusions

This study set out to gain a better understanding of the characteristics, quality, and downloads of dementia-related mHealth apps. In particular, the top three quality apps were all offered as standalone digital game therapeutics, which scored well on both engagement and information quality, and received more than 5000 total downloads. Nevertheless, the findings of our investigation do not offer a comprehensive solution due to the restricted scale of the sample and the potential for overlooking extraordinary instances. Consequently, annual reviews and publicly available expert ratings of mobile apps could help people with dementia and their caregivers choose a high-quality mobile app.

Acknowledgments

The authors acknowledge all staff and participants for their contributions to the study. This study was supported by the Ministry of Science and Technology (MOST 110-2314-B-039-041-MY2; NSTC112-2314-B-039-015) and China Medical University (CMU111-MF-108), Taiwan. The funders reviewed the study as part of the grant application but had no further role in study design; data collection, analysis, and interpretation; manuscript preparation; and paper publication.

Data Availability

The study data are identified participant data. The data that support the findings of this study will be available beginning 12 months and ending 36 months following the article publication from the corresponding author (WFM) upon reasonable request.

Authors' Contributions

THC and WFM designed the study and were responsible for data collection and analysis. THC, SDL, and WFM all contributed to manuscript preparation and critical revisions.

Conflicts of Interest

None declared.

Description, classification, and overall comments of reviewers after using the selected dementia-related mobile health apps.

User version of Mobile App Rating Scale scoring of the dementia-related mHealth apps.

CONSORT-EHEALTH checklist (V 1.6.1).

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Abbreviations

Edited by A Mavragani, H LaMonica; submitted 24.07.23; peer-reviewed by A Kaplin, A Ranerup; comments to author 10.10.23; revised version received 09.11.23; accepted 03.04.24; published 29.04.24.

©Tzu Han Chen, Shin-Da Lee, Wei-Fen Ma. Originally published in JMIR Formative Research (https://formative.jmir.org), 29.04.2024.

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