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• What Is Peer Review? | Types & Examples

What Is Peer Review? | Types & Examples

Published on December 17, 2021 by Tegan George . Revised on June 22, 2023.

Peer review, sometimes referred to as refereeing , is the process of evaluating submissions to an academic journal. Using strict criteria, a panel of reviewers in the same subject area decides whether to accept each submission for publication.

Peer-reviewed articles are considered a highly credible source due to the stringent process they go through before publication.

There are various types of peer review. The main difference between them is to what extent the authors, reviewers, and editors know each other’s identities. The most common types are:

• Single-blind review
• Double-blind review
• Triple-blind review

Collaborative review

Open review.

Relatedly, peer assessment is a process where your peers provide you with feedback on something you’ve written, based on a set of criteria or benchmarks from an instructor. They then give constructive feedback, compliments, or guidance to help you improve your draft.

Table of contents

What is the purpose of peer review, types of peer review, the peer review process, providing feedback to your peers, peer review example, advantages of peer review, criticisms of peer review, other interesting articles, frequently asked questions about peer reviews.

Many academic fields use peer review, largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the manuscript. For this reason, academic journals are among the most credible sources you can refer to.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

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Depending on the journal, there are several types of peer review.

Single-blind peer review

The most common type of peer review is single-blind (or single anonymized) review . Here, the names of the reviewers are not known by the author.

While this gives the reviewers the ability to give feedback without the possibility of interference from the author, there has been substantial criticism of this method in the last few years. Many argue that single-blind reviewing can lead to poaching or intellectual theft or that anonymized comments cause reviewers to be too harsh.

Double-blind peer review

In double-blind (or double anonymized) review , both the author and the reviewers are anonymous.

Arguments for double-blind review highlight that this mitigates any risk of prejudice on the side of the reviewer, while protecting the nature of the process. In theory, it also leads to manuscripts being published on merit rather than on the reputation of the author.

Triple-blind peer review

While triple-blind (or triple anonymized) review —where the identities of the author, reviewers, and editors are all anonymized—does exist, it is difficult to carry out in practice.

Proponents of adopting triple-blind review for journal submissions argue that it minimizes potential conflicts of interest and biases. However, ensuring anonymity is logistically challenging, and current editing software is not always able to fully anonymize everyone involved in the process.

In collaborative review , authors and reviewers interact with each other directly throughout the process. However, the identity of the reviewer is not known to the author. This gives all parties the opportunity to resolve any inconsistencies or contradictions in real time, and provides them a rich forum for discussion. It can mitigate the need for multiple rounds of editing and minimize back-and-forth.

Collaborative review can be time- and resource-intensive for the journal, however. For these collaborations to occur, there has to be a set system in place, often a technological platform, with staff monitoring and fixing any bugs or glitches.

Lastly, in open review , all parties know each other’s identities throughout the process. Often, open review can also include feedback from a larger audience, such as an online forum, or reviewer feedback included as part of the final published product.

While many argue that greater transparency prevents plagiarism or unnecessary harshness, there is also concern about the quality of future scholarship if reviewers feel they have to censor their comments.

In general, the peer review process includes the following steps:

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to the author, or
• Send it onward to the selected peer reviewer(s)
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
• Lastly, the edited manuscript is sent back to the author. They input the edits and resubmit it to the editor for publication.

In an effort to be transparent, many journals are now disclosing who reviewed each article in the published product. There are also increasing opportunities for collaboration and feedback, with some journals allowing open communication between reviewers and authors.

It can seem daunting at first to conduct a peer review or peer assessment. If you’re not sure where to start, there are several best practices you can use.

Summarize the argument in your own words

Summarizing the main argument helps the author see how their argument is interpreted by readers, and gives you a jumping-off point for providing feedback. If you’re having trouble doing this, it’s a sign that the argument needs to be clearer, more concise, or worded differently.

If the author sees that you’ve interpreted their argument differently than they intended, they have an opportunity to address any misunderstandings when they get the manuscript back.

Separate your feedback into major and minor issues

It can be challenging to keep feedback organized. One strategy is to start out with any major issues and then flow into the more minor points. It’s often helpful to keep your feedback in a numbered list, so the author has concrete points to refer back to.

Major issues typically consist of any problems with the style, flow, or key points of the manuscript. Minor issues include spelling errors, citation errors, or other smaller, easy-to-apply feedback.

Tip: Try not to focus too much on the minor issues. If the manuscript has a lot of typos, consider making a note that the author should address spelling and grammar issues, rather than going through and fixing each one.

The best feedback you can provide is anything that helps them strengthen their argument or resolve major stylistic issues.

Give the type of feedback that you would like to receive

No one likes being criticized, and it can be difficult to give honest feedback without sounding overly harsh or critical. One strategy you can use here is the “compliment sandwich,” where you “sandwich” your constructive criticism between two compliments.

Be sure you are giving concrete, actionable feedback that will help the author submit a successful final draft. While you shouldn’t tell them exactly what they should do, your feedback should help them resolve any issues they may have overlooked.

As a rule of thumb, your feedback should be:

• Easy to understand
• Constructive

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Below is a brief annotated research example. You can view examples of peer feedback by hovering over the highlighted sections.

Influence of phone use on sleep

Studies show that teens from the US are getting less sleep than they were a decade ago (Johnson, 2019) . On average, teens only slept for 6 hours a night in 2021, compared to 8 hours a night in 2011. Johnson mentions several potential causes, such as increased anxiety, changed diets, and increased phone use.

The current study focuses on the effect phone use before bedtime has on the number of hours of sleep teens are getting.

For this study, a sample of 300 teens was recruited using social media, such as Facebook, Instagram, and Snapchat. The first week, all teens were allowed to use their phone the way they normally would, in order to obtain a baseline.

The sample was then divided into 3 groups:

• Group 1 was not allowed to use their phone before bedtime.
• Group 2 used their phone for 1 hour before bedtime.
• Group 3 used their phone for 3 hours before bedtime.

All participants were asked to go to sleep around 10 p.m. to control for variation in bedtime . In the morning, their Fitbit showed the number of hours they’d slept. They kept track of these numbers themselves for 1 week.

Two independent t tests were used in order to compare Group 1 and Group 2, and Group 1 and Group 3. The first t test showed no significant difference ( p > .05) between the number of hours for Group 1 ( M = 7.8, SD = 0.6) and Group 2 ( M = 7.0, SD = 0.8). The second t test showed a significant difference ( p < .01) between the average difference for Group 1 ( M = 7.8, SD = 0.6) and Group 3 ( M = 6.1, SD = 1.5).

This shows that teens sleep fewer hours a night if they use their phone for over an hour before bedtime, compared to teens who use their phone for 0 to 1 hours.

Peer review is an established and hallowed process in academia, dating back hundreds of years. It provides various fields of study with metrics, expectations, and guidance to ensure published work is consistent with predetermined standards.

• Protects the quality of published research

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. Any content that raises red flags for reviewers can be closely examined in the review stage, preventing plagiarized or duplicated research from being published.

• Gives you access to feedback from experts in your field

Peer review represents an excellent opportunity to get feedback from renowned experts in your field and to improve your writing through their feedback and guidance. Experts with knowledge about your subject matter can give you feedback on both style and content, and they may also suggest avenues for further research that you hadn’t yet considered.

• Helps you identify any weaknesses in your argument

Peer review acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process. This way, you’ll end up with a more robust, more cohesive article.

While peer review is a widely accepted metric for credibility, it’s not without its drawbacks.

• Reviewer bias

The more transparent double-blind system is not yet very common, which can lead to bias in reviewing. A common criticism is that an excellent paper by a new researcher may be declined, while an objectively lower-quality submission by an established researcher would be accepted.

• Delays in publication

The thoroughness of the peer review process can lead to significant delays in publishing time. Research that was current at the time of submission may not be as current by the time it’s published. There is also high risk of publication bias , where journals are more likely to publish studies with positive findings than studies with negative findings.

• Risk of human error

By its very nature, peer review carries a risk of human error. In particular, falsification often cannot be detected, given that reviewers would have to replicate entire experiments to ensure the validity of results.

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

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Thematic analysis
• Discourse analysis
• Cohort study
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

Peer review is a process of evaluating submissions to an academic journal. Utilizing rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication. For this reason, academic journals are often considered among the most credible sources you can use in a research project– provided that the journal itself is trustworthy and well-regarded.

In general, the peer review process follows the following steps: 

• Reject the manuscript and send it back to author, or 
• Send it onward to the selected peer reviewer(s) 
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made. 
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure. 

A credible source should pass the CRAAP test  and follow these guidelines:

• The information should be up to date and current.
• The author and publication should be a trusted authority on the subject you are researching.
• The sources the author cited should be easy to find, clear, and unbiased.
• For a web source, the URL and layout should signify that it is trustworthy.

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George, T. (2023, June 22). What Is Peer Review? | Types & Examples. Scribbr. Retrieved August 26, 2024, from https://www.scribbr.com/methodology/peer-review/

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Find Resources for Your Midterms or Finals: Scholarly (Peer-reviewed) Journal Articles

• Scholarly (Peer-reviewed) Journal Articles
• Popular Sources
• Getting Research Help

What is Peer Review?

Peer review is the formal process scholarly journals employ to ensure that a manuscript's writing, methodology, arguments, and conclusions are sound. Peer review has long been a marker of quality that sets scholarly articles apart from popular articles (like those you would find in a magazine or newspaper).

Check out the video below for more information on peer review!

Tutorial: Peer Review

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• Peer Review

Library Databases

You'll want to use the Pfau Library's databases to access peer-reviewed scholarly journal articles. The library subscribes to these databases, which give you (as a student) FREE access. If you don't use a library database and try to locate articles through a Google Search or by going directly to a journal's website, for example, you'll often hit a paywall and be asked to pay.

• Starter Databases for Finding Articles Try these recommended databases for locating scholarly articles.
• Explore our Databases by Subject Find databases for particular subjects, from anthropology and geography to nursing and world languages.

Getting a Copy of the Actual Article

Library databases often include complete copies of the articles themselves, or full text .  On your results list, look for a link or an icon indicating that full text is available.

If the article is available in any of Pfau Library's databases, or is free on the Web, you'll be given a link to get it.

If the article might be in the library's hard-copy journals, this will be indicated.

If the article isn't available, you'll get a chance to request a copy through Interlibrary Loan.

Database Search Tips

Think of keywords, or important words describing each aspect of your topic, such as:

food insecurity college students

If you are not getting the results you want, think of synonyms or related terms that might get at your topic. For example:

hunger university students

You can search related terms at the same time. To do so, put OR between the related terms, then bracket them off with parentheses like this:

(hunger OR food insecurity)(university students OR college students)

Keep track of the keywords you use! You will want to try the same searches in different databases.

* Be sure to limit your results to peer-reviewed articles .  To do so, select the Scholarly (Peer Reviewed) Journals  or Peer Reviewed  box – most databases have this option. If you're not sure whether what you're seeing is peer-reviewed or not, contact a librarian or your professor. 

Citation Chasing

When you find an article that's on point, check out its citations/references/works cited list. This will likely lead you to other relevant articles. If you have the name of an article you want, the easiest way to get it is to enter the full title in OneSearch.

• OneSearch Try a search in our online catalog!
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The Savvy Scientist

Experiences of a London PhD student and beyond

My Complete Guide to Academic Peer Review: Example Comments & How to Make Paper Revisions

Once you’ve submitted your paper to an academic journal you’re in the nerve-racking position of waiting to hear back about the fate of your work. In this post we’ll cover everything from potential responses you could receive from the editor and example peer review comments through to how to submit revisions.

My first first-author paper was reviewed by five (yes 5!) reviewers and since then I’ve published several others papers, so now I want to share the insights I’ve gained which will hopefully help you out!

This post is part of my series to help with writing and publishing your first academic journal paper. You can find the whole series here: Writing an academic journal paper .

The Peer Review Process

When you submit a paper to a journal, the first thing that will happen is one of the editorial team will do an initial assessment of whether or not the article is of interest. They may decide for a number of reasons that the article isn’t suitable for the journal and may reject the submission before even sending it out to reviewers.

If this happens hopefully they’ll have let you know quickly so that you can move on and make a start targeting a different journal instead.

Handy way to check the status – Sign in to the journal’s submission website and have a look at the status of your journal article online. If you can see that the article is under review then you’ve passed that first hurdle!

When your paper is under peer review, the journal will have set out a framework to help the reviewers assess your work. Generally they’ll be deciding whether the work is to a high enough standard.

Interested in reading about what reviewers are looking for? Check out my post on being a reviewer for the first time. Peer-Reviewing Journal Articles: Should You Do It? Sharing What I Learned From My First Experiences .

Once the reviewers have made their assessments, they’ll return their comments and suggestions to the editor who will then decide how the article should proceed.

How Many People Review Each Paper?

The editor ideally wants a clear decision from the reviewers as to whether the paper should be accepted or rejected. If there is no consensus among the reviewers then the editor may send your paper out to more reviewers to better judge whether or not to accept the paper.

If you’ve got a lot of reviewers on your paper it isn’t necessarily that the reviewers disagreed about accepting your paper.

You can also end up with lots of reviewers in the following circumstance:

• The editor asks a certain academic to review the paper but doesn’t get a response from them
• The editor asks another academic to step in
• The initial reviewer then responds

Next thing you know your work is being scrutinised by extra pairs of eyes!

As mentioned in the intro, my first paper ended up with five reviewers!

Potential Journal Responses

Assuming that the paper passes the editor’s initial evaluation and is sent out for peer-review, here are the potential decisions you may receive:

• Reject the paper. Sadly the editor and reviewers decided against publishing your work. Hopefully they’ll have included feedback which you can incorporate into your submission to another journal. I’ve had some rejections and the reviewer comments were genuinely useful.
• Accept the paper with major revisions . Good news: with some more work your paper could get published. If you make all the changes that the reviewers suggest, and they’re happy with your responses, then it should get accepted. Some people see major revisions as a disappointment but it doesn’t have to be.
• Accept the paper with minor revisions. This is like getting a major revisions response but better! Generally minor revisions can be addressed quickly and often come down to clarifying things for the reviewers: rewording, addressing minor concerns etc and don’t require any more experiments or analysis. You stand a really good chance of getting the paper published if you’ve been given a minor revisions result.
• Accept the paper with no revisions . I’m not sure that this ever really happens, but it is potentially possible if the reviewers are already completely happy with your paper!

Keen to know more about academic publishing? My series on publishing is now available as a free eBook. It includes my experiences being a peer reviewer. Click the image below for access.

Example Peer Review Comments & Addressing Reviewer Feedback

If your paper has been accepted but requires revisions, the editor will forward to you the comments and concerns that the reviewers raised. You’ll have to address these points so that the reviewers are satisfied your work is of a publishable standard.

It is extremely important to take this stage seriously. If you don’t do a thorough job then the reviewers won’t recommend that your paper is accepted for publication!

You’ll have to put together a resubmission with your co-authors and there are two crucial things you must do:

• Make revisions to your manuscript based off reviewer comments
• Reply to the reviewers, telling them the changes you’ve made and potentially changes you’ve not made in instances where you disagree with them. Read on to see some example peer review comments and how I replied!

Before making any changes to your actual paper, I suggest having a thorough read through the reviewer comments.

Once you’ve read through the comments you might be keen to dive straight in and make the changes in your paper. Instead, I actually suggest firstly drafting your reply to the reviewers.

Why start with the reply to reviewers? Well in a way it is actually potentially more important than the changes you’re making in the manuscript.

Imagine when a reviewer receives your response to their comments: you want them to be able to read your reply document and be satisfied that their queries have largely been addressed without even having to open the updated draft of your manuscript. If you do a good job with the replies, the reviewers will be better placed to recommend the paper be accepted!

By starting with your reply to the reviewers you’ll also clarify for yourself what changes actually have to be made to the paper.

So let’s now cover how to reply to the reviewers.

1. Replying to Journal Reviewers

It is so important to make sure you do a solid job addressing your reviewers’ feedback in your reply document. If you leave anything unanswered you’re asking for trouble, which in this case means either a rejection or another round of revisions: though some journals only give you one shot! Therefore make sure you’re thorough, not just with making the changes but demonstrating the changes in your replies.

It’s no good putting in the work to revise your paper but not evidence it in your reply to the reviewers!

There may be points that reviewers raise which don’t appear to necessitate making changes to your manuscript, but this is rarely the case. Even for comments or concerns they raise which are already addressed in the paper, clearly those areas could be clarified or highlighted to ensure that future readers don’t get confused.

How to Reply to Journal Reviewers

Some journals will request a certain format for how you should structure a reply to the reviewers. If so this should be included in the email you receive from the journal’s editor. If there are no certain requirements here is what I do:

• Copy and paste all replies into a document.
• Separate out each point they raise onto a separate line. Often they’ll already be nicely numbered but sometimes they actually still raise separate issues in one block of text. I suggest separating it all out so that each query is addressed separately.
• Form your reply for each point that they raise. I start by just jotting down notes for roughly how I’ll respond. Once I’m happy with the key message I’ll write it up into a scripted reply.
• Finally, go through and format it nicely and include line number references for the changes you’ve made in the manuscript.

By the end you’ll have a document that looks something like:

Reviewer 1 Point 1: [Quote the reviewer’s comment] Response 1: [Address point 1 and say what revisions you’ve made to the paper] Point 2: [Quote the reviewer’s comment] Response 2: [Address point 2 and say what revisions you’ve made to the paper] Then repeat this for all comments by all reviewers!

What To Actually Include In Your Reply To Reviewers

For every single point raised by the reviewers, you should do the following:

• Address their concern: Do you agree or disagree with the reviewer’s comment? Either way, make your position clear and justify any differences of opinion. If the reviewer wants more clarity on an issue, provide it. It is really important that you actually address their concerns in your reply. Don’t just say “Thanks, we’ve changed the text”. Actually include everything they want to know in your reply. Yes this means you’ll be repeating things between your reply and the revisions to the paper but that’s fine.
• Reference changes to your manuscript in your reply. Once you’ve answered the reviewer’s question, you must show that you’re actually using this feedback to revise the manuscript. The best way to do this is to refer to where the changes have been made throughout the text. I personally do this by include line references. Make sure you save this right until the end once you’ve finished making changes!

Example Peer Review Comments & Author Replies

In order to understand how this works in practice I’d suggest reading through a few real-life example peer review comments and replies.

The good news is that published papers often now include peer-review records, including the reviewer comments and authors’ replies. So here are two feedback examples from my own papers:

Example Peer Review: Paper 1

Quantifying 3D Strain in Scaffold Implants for Regenerative Medicine, J. Clark et al. 2020 – Available here

This paper was reviewed by two academics and was given major revisions. The journal gave us only 10 days to get them done, which was a bit stressful!

• Reviewer Comments
• My reply to Reviewer 1
• My reply to Reviewer 2

One round of reviews wasn’t enough for Reviewer 2…

• My reply to Reviewer 2 – ROUND 2

Thankfully it was accepted after the second round of review, and actually ended up being selected for this accolade, whatever most notable means?!

Nice to see our recent paper highlighted as one of the most notable articles, great start to the week! Thanks @Materials_mdpi 😀 #openaccess & available here: https://t.co/AKWLcyUtpC @ICBiomechanics @julianrjones @saman_tavana pic.twitter.com/ciOX2vftVL — Jeff Clark (@savvy_scientist) December 7, 2020

Example Peer Review: Paper 2

Exploratory Full-Field Mechanical Analysis across the Osteochondral Tissue—Biomaterial Interface in an Ovine Model, J. Clark et al. 2020 – Available here

This paper was reviewed by three academics and was given minor revisions.

• My reply to Reviewer 3

I’m pleased to say it was accepted after the first round of revisions 🙂

Things To Be Aware Of When Replying To Peer Review Comments

• Generally, try to make a revision to your paper for every comment. No matter what the reviewer’s comment is, you can probably make a change to the paper which will improve your manuscript. For example, if the reviewer seems confused about something, improve the clarity in your paper. If you disagree with the reviewer, include better justification for your choices in the paper. It is far more favourable to take on board the reviewer’s feedback and act on it with actual changes to your draft.
• Organise your responses. Sometimes journals will request the reply to each reviewer is sent in a separate document. Unless they ask for it this way I stick them all together in one document with subheadings eg “Reviewer 1” etc.
• Make sure you address each and every question. If you dodge anything then the reviewer will have a valid reason to reject your resubmission. You don’t need to agree with them on every point but you do need to justify your position.
• Be courteous. No need to go overboard with compliments but stay polite as reviewers are providing constructive feedback. I like to add in “We thank the reviewer for their suggestion” every so often where it genuinely warrants it. Remember that written language doesn’t always carry tone very well, so rather than risk coming off as abrasive if I don’t agree with the reviewer’s suggestion I’d rather be generous with friendliness throughout the reply.

2. How to Make Revisions To Your Paper

Once you’ve drafted your replies to the reviewers, you’ve actually done a lot of the ground work for making changes to the paper. Remember, you are making changes to the paper based off the reviewer comments so you should regularly be referring back to the comments to ensure you’re not getting sidetracked.

Reviewers could request modifications to any part of your paper. You may need to collect more data, do more analysis, reformat some figures, add in more references or discussion or any number of other revisions! So I can’t really help with everything, even so here is some general advice:

• Use tracked-changes. This is so important. The editor and reviewers need to be able to see every single change you’ve made compared to your first submission. Sometimes the journal will want a clean copy too but always start with tracked-changes enabled then just save a clean copy afterwards.
• Be thorough . Try to not leave any opportunity for the reviewers to not recommend your paper to be published. Any chance you have to satisfy their concerns, take it. For example if the reviewers are concerned about sample size and you have the means to include other experiments, consider doing so. If they want to see more justification or references, be thorough. To be clear again, this doesn’t necessarily mean making changes you don’t believe in. If you don’t want to make a change, you can justify your position to the reviewers. Either way, be thorough.
• Use your reply to the reviewers as a guide. In your draft reply to the reviewers you should have already included a lot of details which can be incorporated into the text. If they raised a concern, you should be able to go and find references which address the concern. This reference should appear both in your reply and in the manuscript. As mentioned above I always suggest starting with the reply, then simply adding these details to your manuscript once you know what needs doing.

Putting Together Your Paper Revision Submission

• Once you’ve drafted your reply to the reviewers and revised manuscript, make sure to give sufficient time for your co-authors to give feedback. Also give yourself time afterwards to make changes based off of their feedback. I ideally give a week for the feedback and another few days to make the changes.
• When you’re satisfied that you’ve addressed the reviewer comments, you can think about submitting it. The journal may ask for another letter to the editor, if not I simply add to the top of the reply to reviewers something like:

“Dear [Editor], We are grateful to the reviewer for their positive and constructive comments that have led to an improved manuscript.  Here, we address their concerns/suggestions and have tracked changes throughout the revised manuscript.”

Once you’re ready to submit:

• Double check that you’ve done everything that the editor requested in their email
• Double check that the file names and formats are as required
• Triple check you’ve addressed the reviewer comments adequately
• Click submit and bask in relief!

You won’t always get the paper accepted, but if you’re thorough and present your revisions clearly then you’ll put yourself in a really good position. Remember to try as hard as possible to satisfy the reviewers’ concerns to minimise any opportunity for them to not accept your revisions!

Best of luck!

I really hope that this post has been useful to you and that the example peer review section has given you some ideas for how to respond. I know how daunting it can be to reply to reviewers, and it is really important to try to do a good job and give yourself the best chances of success. If you’d like to read other posts in my academic publishing series you can find them here:

Blog post series: Writing an academic journal paper

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How to Write and Publish a Research Paper for a Peer-Reviewed Journal

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• Published: 30 April 2020
• Volume 36 , pages 909–913, ( 2021 )

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Communicating research findings is an essential step in the research process. Often, peer-reviewed journals are the forum for such communication, yet many researchers are never taught how to write a publishable scientific paper. In this article, we explain the basic structure of a scientific paper and describe the information that should be included in each section. We also identify common pitfalls for each section and recommend strategies to avoid them. Further, we give advice about target journal selection and authorship. In the online resource 1 , we provide an example of a high-quality scientific paper, with annotations identifying the elements we describe in this article.

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Introduction

Writing a scientific paper is an important component of the research process, yet researchers often receive little formal training in scientific writing. This is especially true in low-resource settings. In this article, we explain why choosing a target journal is important, give advice about authorship, provide a basic structure for writing each section of a scientific paper, and describe common pitfalls and recommendations for each section. In the online resource 1 , we also include an annotated journal article that identifies the key elements and writing approaches that we detail here. Before you begin your research, make sure you have ethical clearance from all relevant ethical review boards.

Select a Target Journal Early in the Writing Process

We recommend that you select a “target journal” early in the writing process; a “target journal” is the journal to which you plan to submit your paper. Each journal has a set of core readers and you should tailor your writing to this readership. For example, if you plan to submit a manuscript about vaping during pregnancy to a pregnancy-focused journal, you will need to explain what vaping is because readers of this journal may not have a background in this topic. However, if you were to submit that same article to a tobacco journal, you would not need to provide as much background information about vaping.

Information about a journal’s core readership can be found on its website, usually in a section called “About this journal” or something similar. For example, the Journal of Cancer Education presents such information on the “Aims and Scope” page of its website, which can be found here: https://www.springer.com/journal/13187/aims-and-scope .

Peer reviewer guidelines from your target journal are an additional resource that can help you tailor your writing to the journal and provide additional advice about crafting an effective article [ 1 ]. These are not always available, but it is worth a quick web search to find out.

Identify Author Roles Early in the Process

Early in the writing process, identify authors, determine the order of authors, and discuss the responsibilities of each author. Standard author responsibilities have been identified by The International Committee of Medical Journal Editors (ICMJE) [ 2 ]. To set clear expectations about each team member’s responsibilities and prevent errors in communication, we also suggest outlining more detailed roles, such as who will draft each section of the manuscript, write the abstract, submit the paper electronically, serve as corresponding author, and write the cover letter. It is best to formalize this agreement in writing after discussing it, circulating the document to the author team for approval. We suggest creating a title page on which all authors are listed in the agreed-upon order. It may be necessary to adjust authorship roles and order during the development of the paper. If a new author order is agreed upon, be sure to update the title page in the manuscript draft.

In the case where multiple papers will result from a single study, authors should discuss who will author each paper. Additionally, authors should agree on a deadline for each paper and the lead author should take responsibility for producing an initial draft by this deadline.

Structure of the Introduction Section

The introduction section should be approximately three to five paragraphs in length. Look at examples from your target journal to decide the appropriate length. This section should include the elements shown in Fig.  1 . Begin with a general context, narrowing to the specific focus of the paper. Include five main elements: why your research is important, what is already known about the topic, the “gap” or what is not yet known about the topic, why it is important to learn the new information that your research adds, and the specific research aim(s) that your paper addresses. Your research aim should address the gap you identified. Be sure to add enough background information to enable readers to understand your study. Table 1 provides common introduction section pitfalls and recommendations for addressing them.

The main elements of the introduction section of an original research article. Often, the elements overlap

Methods Section

The purpose of the methods section is twofold: to explain how the study was done in enough detail to enable its replication and to provide enough contextual detail to enable readers to understand and interpret the results. In general, the essential elements of a methods section are the following: a description of the setting and participants, the study design and timing, the recruitment and sampling, the data collection process, the dataset, the dependent and independent variables, the covariates, the analytic approach for each research objective, and the ethical approval. The hallmark of an exemplary methods section is the justification of why each method was used. Table 2 provides common methods section pitfalls and recommendations for addressing them.

Results Section

The focus of the results section should be associations, or lack thereof, rather than statistical tests. Two considerations should guide your writing here. First, the results should present answers to each part of the research aim. Second, return to the methods section to ensure that the analysis and variables for each result have been explained.

Begin the results section by describing the number of participants in the final sample and details such as the number who were approached to participate, the proportion who were eligible and who enrolled, and the number of participants who dropped out. The next part of the results should describe the participant characteristics. After that, you may organize your results by the aim or by putting the most exciting results first. Do not forget to report your non-significant associations. These are still findings.

Tables and figures capture the reader’s attention and efficiently communicate your main findings [ 3 ]. Each table and figure should have a clear message and should complement, rather than repeat, the text. Tables and figures should communicate all salient details necessary for a reader to understand the findings without consulting the text. Include information on comparisons and tests, as well as information about the sample and timing of the study in the title, legend, or in a footnote. Note that figures are often more visually interesting than tables, so if it is feasible to make a figure, make a figure. To avoid confusing the reader, either avoid abbreviations in tables and figures, or define them in a footnote. Note that there should not be citations in the results section and you should not interpret results here. Table 3 provides common results section pitfalls and recommendations for addressing them.

Discussion Section

Opposite the introduction section, the discussion should take the form of a right-side-up triangle beginning with interpretation of your results and moving to general implications (Fig.  2 ). This section typically begins with a restatement of the main findings, which can usually be accomplished with a few carefully-crafted sentences.

Major elements of the discussion section of an original research article. Often, the elements overlap

Next, interpret the meaning or explain the significance of your results, lifting the reader’s gaze from the study’s specific findings to more general applications. Then, compare these study findings with other research. Are these findings in agreement or disagreement with those from other studies? Does this study impart additional nuance to well-accepted theories? Situate your findings within the broader context of scientific literature, then explain the pathways or mechanisms that might give rise to, or explain, the results.

Journals vary in their approach to strengths and limitations sections: some are embedded paragraphs within the discussion section, while some mandate separate section headings. Keep in mind that every study has strengths and limitations. Candidly reporting yours helps readers to correctly interpret your research findings.

The next element of the discussion is a summary of the potential impacts and applications of the research. Should these results be used to optimally design an intervention? Does the work have implications for clinical protocols or public policy? These considerations will help the reader to further grasp the possible impacts of the presented work.

Finally, the discussion should conclude with specific suggestions for future work. Here, you have an opportunity to illuminate specific gaps in the literature that compel further study. Avoid the phrase “future research is necessary” because the recommendation is too general to be helpful to readers. Instead, provide substantive and specific recommendations for future studies. Table 4 provides common discussion section pitfalls and recommendations for addressing them.

Follow the Journal’s Author Guidelines

After you select a target journal, identify the journal’s author guidelines to guide the formatting of your manuscript and references. Author guidelines will often (but not always) include instructions for titles, cover letters, and other components of a manuscript submission. Read the guidelines carefully. If you do not follow the guidelines, your article will be sent back to you.

Finally, do not submit your paper to more than one journal at a time. Even if this is not explicitly stated in the author guidelines of your target journal, it is considered inappropriate and unprofessional.

Your title should invite readers to continue reading beyond the first page [ 4 , 5 ]. It should be informative and interesting. Consider describing the independent and dependent variables, the population and setting, the study design, the timing, and even the main result in your title. Because the focus of the paper can change as you write and revise, we recommend you wait until you have finished writing your paper before composing the title.

Be sure that the title is useful for potential readers searching for your topic. The keywords you select should complement those in your title to maximize the likelihood that a researcher will find your paper through a database search. Avoid using abbreviations in your title unless they are very well known, such as SNP, because it is more likely that someone will use a complete word rather than an abbreviation as a search term to help readers find your paper.

After you have written a complete draft, use the checklist (Fig. 3 ) below to guide your revisions and editing. Additional resources are available on writing the abstract and citing references [ 5 ]. When you feel that your work is ready, ask a trusted colleague or two to read the work and provide informal feedback. The box below provides a checklist that summarizes the key points offered in this article.

Checklist for manuscript quality

Data Availability

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Acknowledgments

Ella August is grateful to the Sustainable Sciences Institute for mentoring her in training researchers on writing and publishing their research.

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Department of Maternal and Child Health, University of North Carolina Gillings School of Global Public Health, 135 Dauer Dr, 27599, Chapel Hill, NC, USA

Clara Busse & Ella August

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Busse, C., August, E. How to Write and Publish a Research Paper for a Peer-Reviewed Journal. J Canc Educ 36 , 909–913 (2021). https://doi.org/10.1007/s13187-020-01751-z

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Published : 30 April 2020

Issue Date : October 2021

DOI : https://doi.org/10.1007/s13187-020-01751-z

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The genesis of this paper is the proposal that genomes containing a poor percentage of guanosine and cytosine (GC) nucleotide pairs lead to proteomes more prone to aggregation than those encoded by GC-rich genomes. As a consequence these organisms are also more dependent on the protein folding machinery. If true, this interesting hypothesis could establish a direct link between the tendency to aggregate and the genomic code.

In their paper, the authors have tested the hypothesis on the genomes of eubacteria using a genome-wide approach based on multiple machine learning models. Eubacteria are an interesting set of organisms which have an appreciably high variation in their nucleotide composition with the percentage of CG genetic material ranging from 20% to 70%. The authors classified different eubacterial proteomes in terms of their aggregation propensity and chaperone-dependence. For this purpose, new classifiers had to be developed which were based on carefully curated data. They took account for twenty-four different features among which are sequence patterns, the pseudo amino acid composition of phenylalanine, aspartic and glutamic acid, the distribution of positively charged amino acids, the FoldIndex score and the hydrophobicity. These classifiers seem to be altogether more accurate and robust than previous such parameters.

The authors found that, contrary to what expected from the working hypothesis, which would predict a decrease in protein aggregation with an increase in GC richness, the aggregation propensity of proteomes increases with the GC content and thus the stability of the proteome against aggregation increases with the decrease in GC content. The work also established a direct correlation between GC-poor proteomes and a lower dependence on GroEL. The authors conclude by proposing that a decrease in eubacterial GC content may have been selected in organisms facing proteostasis problems. A way to test the overall results would be through in vitro evolution experiments aimed at testing whether adaptation to low GC content provide folding advantage.

The main strengths of this paper is that it addresses an interesting and timely question, finds a novel solution based on a carefully selected set of rules, and provides a clear answer. As such this article represents an excellent and elegant bioinformatics genome-wide study which will almost certainly influence our thinking about protein aggregation and evolution. Some of the weaknesses are the not always easy readability of the text which establishes unclear logical links between concepts.

Another possible criticism could be that, as any in silico study, it makes strong assumptions on the sequence features that lead to aggregation and strongly relies on the quality of the classifiers used. Even though the developed classifiers seem to be more robust than previous such parameters, they remain only overall indications which can only allow statistical considerations. It could of course be argued that this is good enough to reach meaningful conclusions in this specific case.

The paper by Chevalier et al. analyzed whether late sodium current (I NaL ) can be assessed using an automated patch-clamp device. To this end, the I NaL effects of ranolazine (a well known I NaL inhibitor) and veratridine (an I NaL activator) were described. The authors tested the CytoPatch automated patch-clamp equipment and performed whole-cell recordings in HEK293 cells stably transfected with human Nav1.5. Furthermore, they also tested the electrophysiological properties of human induced pluripotent stem cell-derived cardiomyocytes (hiPS) provided by Cellular Dynamics International. The title and abstract are appropriate for the content of the text. Furthermore, the article is well constructed, the experiments were well conducted, and analysis was well performed.

I NaL is a small current component generated by a fraction of Nav1.5 channels that instead to entering in the inactivated state, rapidly reopened in a burst mode. I NaL critically determines action potential duration (APD), in such a way that both acquired (myocardial ischemia and heart failure among others) or inherited (long QT type 3) diseases that augmented the I NaL magnitude also increase the susceptibility to cardiac arrhythmias. Therefore, I NaL has been recognized as an important target for the development of drugs with either antiischemic or antiarrhythmic effects. Unfortunately, accurate measurement of I NaL is a time consuming and technical challenge because of its extra-small density. The automated patch clamp device tested by Chevalier et al. resolves this problem and allows fast and reliable I NaL measurements.

The results here presented merit some comments and arise some unresolved questions. First, in some experiments (such is the case in experiments B and D in Figure 2) current recordings obtained before the ranolazine perfusion seem to be quite unstable. Indeed, the amplitude progressively increased to a maximum value that was considered as the control value (highlighted with arrows). Can this problem be overcome? Is this a consequence of a slow intracellular dialysis? Is it a consequence of a time-dependent shift of the voltage dependence of activation/inactivation? Second, as shown in Figure 2, intensity of drug effects seems to be quite variable. In fact, experiments A, B, C, and D in Figure 2 and panel 2D, demonstrated that veratridine augmentation ranged from 0-400%. Even assuming the normal biological variability, we wonder as to whether this broad range of effect intensities can be justified by changes in the perfusion system. Has been the automated dispensing system tested? If not, we suggest testing the effects of several K + concentrations on inward rectifier currents generated by Kir2.1 channels (I Kir2.1 ).

The authors demonstrated that the recording quality was so high that the automated device allows to the differentiation between noise and current, even when measuring currents of less than 5 pA of amplitude. In order to make more precise mechanistic assumptions, the authors performed an elegant estimation of current variance (σ 2 ) and macroscopic current (I) following the procedure described more than 30 years ago by Van Driessche and Lindemann 1 . By means of this method, Chevalier et al. reducing the open channel probability, while veratridine increases the number of channels in the burst mode. We respectfully would like to stress that these considerations must be put in context from a pharmacological point of view. We do not doubt that ranolazine acts as an open channel blocker, what it seems clear however, is that its onset block kinetics has to be “ultra” slow, otherwise ranolazine would decrease peak I NaL even at low frequencies of stimulation. This comment points towards the fact that for a precise mechanistic study of ionic current modifying drugs it is mandatory to analyze drug effects with much more complicated pulse protocols. Questions thus are: does this automated equipment allow to the analysis of the frequency-, time-, and voltage-dependent effects of drugs? Can versatile and complicated pulse protocols be applied? Does it allow to a good voltage control even when generated currents are big and fast? If this is not possible, and by means of its extraordinary discrimination between current and noise, this automated patch-clamp equipment will only be helpful for rapid I NaL -modifying drug screening. Obviously it will also be perfect to test HERG blocking drug effects as demanded by the regulatory authorities.

Finally, as cardiac electrophysiologists, we would like to stress that it seems that our dream of testing drug effects on human ventricular myocytes seems to come true. Indeed, human atrial myocytes are technically, ethically and logistically difficult to get, but human ventricular are almost impossible to be obtained unless from the explanted hearts from patients at the end stage of cardiac diseases. Here the authors demonstrated that ventricular myocytes derived from hiPS generate beautiful action potentials that can be recorded with this automated equipment. The traces shown suggested that there was not alternation in the action potential duration. Is this a consistent finding? How long do last these stable recordings? The only comment is that resting membrane potential seems to be somewhat variable. Can this be resolved? Is it an unexpected veratridine effect? Standardization of maturation methods of ventricular myocytes derived from hiPS will be a big achievement for cardiac cellular electrophysiology which was obliged for years to the imprecise extrapolation of data obtained from a combination of several species none of which was representative of human electrophysiology. The big deal will be the maturation of human atrial myocytes derived from hiPS that fulfil the known characteristics of human atrial cells.

We suggest suppressing the initial sentence of section 3. We surmise that results obtained from the experiments described in this section cannot serve to understand the role of I NaL in arrhythmogenesis.

1. Van Driessche W, Lindemann B: Concentration dependence of currents through single sodium-selective pores in frog skin. Nature . 1979; 282 (5738): 519-520 PubMed Abstract | Publisher Full Text

The authors have clarified several of the questions I raised in my previous review. Unfortunately, most of the major problems have not been addressed by this revision. As I stated in my previous review, I deem it unlikely that all those issues can be solved merely by a few added paragraphs. Instead there are still some fundamental concerns with the experimental design and, most critically, with the analysis. This means the strong conclusions put forward by this manuscript are not warranted and I cannot approve the manuscript in this form.

• The greatest concern is that when I followed the description of the methods in the previous version it was possible to decode, with almost perfect accuracy, any arbitrary stimulus labels I chose. See https://doi.org/10.6084/m9.figshare.1167456 for examples of this reanalysis. Regardless of whether we pretend that the actual stimulus appeared at a later time or was continuously alternating between signal and silence, the decoding is always close to perfect. This is an indication that the decoding has nothing to do with the actual stimulus heard by the Sender but is opportunistically exploiting some other features in the data. The control analysis the authors performed, reversing the stimulus labels, cannot address this problem because it suffers from the exact same problem. Essentially, what the classifier is presumably using is the time that has passed since the recording started.
• The reason for this is presumably that the authors used non-independent data for training and testing. Assuming I understand correctly (see point 3), random sampling one half of data samples from an EEG trace are not independent data . Repeating the analysis five times – the control analysis the authors performed – is not an adequate way to address this concern. Randomly selecting samples from a time series containing slow changes (such as the slow wave activity that presumably dominates these recordings under these circumstances) will inevitably contain strong temporal correlations. See TemporalCorrelations.jpg in https://doi.org/10.6084/m9.figshare.1185723 for 2D density histograms and a correlation matrix demonstrating this.
• While the revised methods section provides more detail now, it still is unclear about exactly what data were used. Conventional classification analysis report what data features (usual columns in the data matrix) and what observations (usual rows) were used. Anything could be a feature but typically this might be the different EEG channels or fMRI voxels etc. Observations are usually time points. Here I assume the authors transformed the raw samples into a different space using principal component analysis. It is not stated if the dimensionality was reduced using the eigenvalues. Either way, I assume the data samples (collected at 128 Hz) were then used as observations and the EEG channels transformed by PCA were used as features. The stimulus labels were assigned as ON or OFF for each sample. A set of 50% of samples (and labels) was then selected at random for training, and the rest was used for testing. Is this correct?
• A powerful non-linear classifier can capitalise on such correlations to discriminate arbitrary labels. In my own analyses I used both an SVM with RBF as well as a k-nearest neighbour classifier, both of which produce excellent decoding of arbitrary stimulus labels (see point 1). Interestingly, linear classifiers or less powerful SVM kernels fare much worse – a clear indication that the classifier learns about the complex non-linear pattern of temporal correlations that can describe the stimulus label. This is further corroborated by the fact that when using stimulus labels that are chosen completely at random (i.e. with high temporal frequency) decoding does not work.
• The authors have mostly clarified how the correlation analysis was performed. It is still left unclear, however, how the correlations for individual pairs were averaged. Was Fisher’s z-transformation used, or were the data pooled across pairs? More importantly, it is not entirely surprising that under the experimental conditions there will be some correlation between the EEG signals for different participants, especially in low frequency bands. Again, this further supports the suspicion that the classification utilizes slow frequency signals that are unrelated to the stimulus and the experimental hypothesis. In fact, a quick spot check seems to confirm this suspicion: correlating the time series separately for each channel from the Receiver in pair 1 with those from the Receiver in pair 18 reveals 131 significant (p‹0.05, Bonferroni corrected) out of 196 (14x14 channels) correlations… One could perhaps argue that this is not surprising because both these pairs had been exposed to identical stimulus protocols: one minute of initial silence and only one signal period (see point 6). However, it certainly argues strongly against the notion that the decoding is any way related to the mental connection between the particular Sender and Receiver in a given pair because it clearly works between Receivers in different pairs! However, to further control for this possibility I repeated the same analysis but now comparing the Receiver from pair 1 to the Receiver from pair 15. This pair was exposed to a different stimulus paradigm (2 minutes of initial silence and a longer paradigm with three signal periods). I only used the initial 3 minutes for the correlation analysis. Therefore, both recordings would have been exposed to only one signal period but at different times (at 1 min and 2 min for pair 1 and 15, respectively). Even though the stimulus protocol was completely different the time courses for all the channels are highly correlated and 137 out of 196 correlations are significant. Considering that I used the raw data for this analysis it should not surprise anyone that extracting power from different frequency bands in short time windows will also reveal significant correlations. Crucially, it demonstrates that correlations between Sender and Receiver are artifactual and trivial.
• The authors argue in their response and the revision that predictive strategies were unlikely. After having performed these additional analyses I am inclined to agree. The excellent decoding almost certainly has nothing to do with expectation or imagery effects and it is irrelevant whether participants could guess the temporal design of the experiment. Rather, the results are almost entirely an artefact of the analysis. However, this does not mean that predictability is not an issue. The figure StimulusTimecourses.jpg in https://doi.org/10.6084/m9.figshare.1185723 plots the stimulus time courses for all 20 pairs as can be extracted from the newly uploaded data. This confirms what I wrote in my previous review, in fact, with the corrected data sets the problem with predictability is even greater. Out of the 20 pairs, 13 started with 1 min of initial silence. The remaining 7 had 2 minutes of initial silence. Most of the stimulus paradigms are therefore perfectly aligned and thus highly correlated. This also proves incorrect the statement that initial silence periods were 1, 2, or 3 minutes. No pair had 3 min of initial silence. It would therefore have been very easy for any given Receiver to correctly guess the protocol. It should be clear that this is far from optimal for testing such an unorthodox hypothesis. Any future experiments should employ more randomization to decrease predictability. Even if this wasn’t the underlying cause of the present results, this is simply not great experimental design.
• The authors now acknowledge in their response that all the participants were authors. They say that this is also acknowledged in the methods section, but I did not see any statement about that in the revised manuscript. As before, I also find it highly questionable to include only authors in an experiment of this kind. It is not sufficient to claim that Receivers weren’t guessing their stimulus protocol. While I am giving the authors (and thus the participants) the benefit of the doubt that they actually believe they weren’t guessing/predicting the stimulus protocols, this does not rule out that they did. It may in fact be possible to make such predictions subconsciously (Now, if you ask me, this is an interesting scientific question someone should do an experiment on!). The fact familiar with the protocol may help that. Any future experiments should take steps to prevent this.
• I do not follow the explanation for the binomial test the authors used. Based on the excessive Bayes Factor of 390,625 it is clear that the authors assumed a chance level of 50% on their binomial test. Because the design is not balanced, this is not correct.
• In general, the Bayes Factor and the extremely high decoding accuracy should have given the authors reason to start. Considering the unusual hypothesis did the authors not at any point wonder if these results aren’t just far too good to be true? Decoding mental states from brain activity is typically extremely noisy and hardly affords accuracies at the level seen here. Extremely accurate decoding and Bayes Factors in the hundreds of thousands should be a tell-tale sign to check that there isn’t an analytical flaw that makes the result entirely trivial. I believe this is what happened here and thus I think this experiment serves as a very good demonstration for the pitfalls of applying such analysis without sanity checks. In order to make claims like this, the experimental design must contain control conditions that can rule out these problems. Presumably, recordings without any Sender, and maybe even when the “Receiver” is aware of this fact, should produce very similar results.

Based on all these factors, it is impossible for me to approve this manuscript. I should however state that it is laudable that the authors chose to make all the raw data of their experiment publicly available. Without this it would have impossible for me to carry out the additional analyses, and thus the most fundamental problem in the analysis would have remained unknown. I respect the authors’ patience and professionalism in dealing with what I can only assume is a rather harsh review experience. I am honoured by the request for an adversarial collaboration. I do not rule out such efforts at some point in the future. However, for all of the reasons outlined in this and my previous review, I do not think the time is right for this experiment to proceed to this stage. Fundamental analytical flaws and weaknesses in the design should be ruled out first. An adversarial collaboration only really makes sense to me for paradigms were we can be confident that mundane or trivial factors have been excluded.

This manuscript does an excellent job demonstrating significant strain differences in Burdian's paradigm. Since each Drosophila lab has their own wild type (usually Canton-S) isolate, this issue of strain differences is actually a very important one for between lab reproducibility. This work is a good reminder for all geneticists to pay attention to the population effects in the background controls, and presumably the mutant lines we are comparing.

I was very pleased to see the within-isolate behavior was consistent in replicate experiments one year apart. The authors further argue that the between-isolate differences in behavior arise from a Founder's effect, at least in the differences in locomotor behavior between the Paris lines CS_TP and CS_JC. I believe this is a very reasonable and testable hypothesis. It predicts that genetic variability for these traits exist within the populations. It should now be possible to perform selection experiments from the original CS_TP population to replicate the founding event and estimate the heritability of these traits.

Two other things that I liked about this manuscript are the ability to adjust parameters in figure 3, and our ability to download the raw data. After reading the manuscript, I was a little disappointed that the performance of the five strains in each 12 behavioral variables weren't broken down individually in a table or figure. I thought this may help us readers understand what the principle components were representing. The authors have made this data readily accessible in a downloadable spreadsheet.

This is an exceptionally good review and balanced assessment of the status of CETP inhibitors and ASCVD from a world authority in the field. The article highlights important data that might have been overlooked when promulgating the clinical value of CETPIs and related trials.

Only 2 areas need revision:

• Page 3, para 2: the notion that these data from Papp et al . convey is critical and the message needs an explicit sentence or two at end of paragraph.
• Page 4, Conclusion: the assertion concerning the ethics of the two Phase 3 clinical trials needs toning down. Perhaps rephrase to indicate that the value and sense of doing these trials is open to question, with attendant ethical implications, or softer wording to that effect.

The Wiley et al . manuscript describes a beautiful synthesis of contemporary genetic approaches to, with astonishing efficiency, identify lead compounds for therapeutic approaches to a serious human disease. I believe the importance of this paper stems from the applicability of the approach to the several thousand of rare human disease genes that Next-Gen sequencing will uncover in the next few years and the challenge we will have in figuring out the function of these genes and their resulting defects. This work presents a paradigm that can be broadly and usefully applied.

In detail, the authors begin with gene responsible for X-linked spinal muscular atrophy and express both the wild-type version of that human gene as well as a mutant form of that gene in S. pombe . The conceptual leap here is that progress in genetics is driven by phenotype, and this approach involving a yeast with no spine or muscles to atrophy is nevertheless and N-dimensional detector of phenotype.

The study is not without a small measure of luck in that expression of the wild-type UBA1 gene caused a slow growth phenotype which the mutant did not. Hence there was something in S. pombe that could feel the impact of this protein. Given this phenotype, the authors then went to work and using the power of the synthetic genetic array approach pioneered by Boone and colleagues made a systematic set of double mutants combining the human expressed UBA1 gene with knockout alleles of a plurality of S. pombe genes. They found well over a hundred mutations that either enhanced or suppressed the growth defect of the cells expressing UBI1. Most of these have human orthologs. My hunch is that many human genes expressed in yeast will have some comparably exploitable phenotype, and time will tell.

Building on the interaction networks of S. pombe genes already established, augmenting these networks by the protein interaction networks from yeast and from human proteome studies involving these genes, and from the structure of the emerging networks, the authors deduced that an E3 ligase modulated UBA1 and made the leap that it therefore might also impact X-linked Spinal Muscular Atrophy.

Here, the awesome power of the model organism community comes into the picture as there is a zebrafish model of spinal muscular atrophy. The principle of phenologs articulated by the Marcotte group inspire the recognition of the transitive logic of how phenotypes in one organism relate to phenotypes in another. With this zebrafish model, they were able to confirm that an inhibitor of E3 ligases and of the Nedd8-E1 activating suppressed the motor axon anomalies, as predicted by the effect of mutations in S. pombe on the phenotypes of the UBA1 overexpression.

I believe this is an important paper to teach in intro graduate courses as it illustrates beautifully how important it is to know about and embrace the many new sources of systematic genetic information and apply them broadly.

This paper by Amrhein et al. criticizes a paper by Bradley Efron that discusses Bayesian statistics ( Efron, 2013a ), focusing on a particular example that was also discussed in Efron (2013b) . The example concerns a woman who is carrying twins, both male (as determined by sonogram and we ignore the possibility that gender has been observed incorrectly). The parents-to-be ask Efron to tell them the probability that the twins are identical.

This is my first open review, so I'm not sure of the protocol. But given that there appears to be errors in both Efron (2013b) and the paper under review, I am sorry to say that my review might actually be longer than the article by Efron (2013a) , the primary focus of the critique, and the critique itself. I apologize in advance for this. To start, I will outline the problem being discussed for the sake of readers.

This problem has various parameters of interest. The primary parameter is the genetic composition of the twins in the mother’s womb. Are they identical (which I describe as the state x = 1) or fraternal twins ( x = 0)? Let y be the data, with y = 1 to indicate the twins are the same gender. Finally, we wish to obtain Pr( x = 1 | y = 1), the probability the twins are identical given they are the same gender 1 . Bayes’ rule gives us an expression for this:

Pr( x = 1 | y = 1) = Pr( x =1) Pr( y = 1 | x = 1) / {Pr( x =1) Pr( y = 1 | x = 1) + Pr( x =0) Pr( y = 1 | x = 0)}

Now we know that Pr( y = 1 | x = 1) = 1; twins must be the same gender if they are identical. Further, Pr( y = 1 | x = 0) = 1/2; if twins are not identical, the probability of them being the same gender is 1/2.

Finally, Pr( x = 1) is the prior probability that the twins are identical. The bone of contention in the Efron papers and the critique by Amrhein et al. revolves around how this prior is treated. One can think of Pr( x = 1) as the population-level proportion of twins that are identical for a mother like the one being considered.

However, if we ignore other forms of twins that are extremely rare (equivalent to ignoring coins finishing on their edges when flipping them), one incontrovertible fact is that Pr( x = 0) = 1 − Pr( x = 1); the probability that the twins are fraternal is the complement of the probability that they are identical.

The above values and expressions for Pr( y = 1 | x = 1), Pr( y = 1 | x = 0), and Pr( x = 0) leads to a simpler expression for the probability that we seek ‐ the probability that the twins are identical given they have the same gender:

Pr( x = 1 | y = 1) = 2 Pr( x =1) / [1 + Pr( x =1)] (1)

We see that the answer depends on the prior probability that the twins are identical, Pr( x =1). The paper by Amrhein et al. points out that this is a mathematical fact. For example, if identical twins were impossible (Pr( x = 1) = 0), then Pr( x = 1| y = 1) = 0. Similarly, if all twins were identical (Pr( x = 1) = 1), then Pr( x = 1| y = 1) = 1. The “true” prior lies somewhere in between. Apparently, the doctor knows that one third of twins are identical 2 . Therefore, if we assume Pr( x = 1) = 1/3, then Pr( x = 1| y = 1) = 1/2.

Now, what would happen if we didn't have the doctor's knowledge? Laplace's “Principle of Insufficient Reason” would suggest that we give equal prior probability to all possibilities, so Pr( x = 1) = 1/2 and Pr( x = 1| y = 1) = 2/3, an answer different from 1/2 that was obtained when using the doctor's prior of 1/3.

Efron(2013a) highlights this sensitivity to the prior, representing someone who defines an uninformative prior as a “violator”, with Laplace as the “prime violator”. In contrast, Amrhein et al. correctly points out that the difference in the posterior probabilities is merely a consequence of mathematical logic. No one is violating logic – they are merely expressing ignorance by specifying equal probabilities to all states of nature. Whether this is philosophically valid is debatable ( Colyvan 2008 ), but weight to that question, and it is well beyond the scope of this review. But setting Pr( x = 1) = 1/2 is not a violation; it is merely an assumption with consequences (and one that in hindsight might be incorrect 2 ).

Alternatively, if we don't know Pr( x = 1), we could describe that probability by its own probability distribution. Now the problem has two aspects that are uncertain. We don’t know the true state x , and we don’t know the prior (except in the case where we use the doctor’s knowledge that Pr( x = 1) = 1/3). Uncertainty in the state of x refers to uncertainty about this particular set of twins. In contrast, uncertainty in Pr( x = 1) reflects uncertainty in the population-level frequency of identical twins. A key point is that the state of one particular set of twins is a different parameter from the frequency of occurrence of identical twins in the population.

Without knowledge about Pr( x = 1), we might use Pr( x = 1) ~ dunif(0, 1), which is consistent with Laplace. Alternatively, Efron (2013b) notes another alternative for an uninformative prior: Pr( x = 1) ~ dbeta(0.5, 0.5), which is the Jeffreys prior for a probability.

Here I disagree with Amrhein et al. ; I think they are confusing the two uncertain parameters. Amrhein et al. state:

“We argue that this example is not only flawed, but useless in illustrating Bayesian data analysis because it does not rely on any data. Although there is one data point (a couple is due to be parents of twin boys, and the twins are fraternal), Efron does not use it to update prior knowledge. Instead, Efron combines different pieces of expert knowledge from the doctor and genetics using Bayes’ theorem.”

This claim might be correct when describing uncertainty in the population-level frequency of identical twins. The data about the twin boys is not useful by itself for this purpose – they are a biased sample (the data have come to light because their gender is the same; they are not a random sample of twins). Further, a sample of size one, especially if biased, is not a firm basis for inference about a population parameter. While the data are biased, the claim by Amrheim et al. that there are no data is incorrect.

However, the data point (the twins have the same gender) is entirely relevant to the question about the state of this particular set of twins. And it does update the prior. This updating of the prior is given by equation (1) above. The doctor’s prior probability that the twins are identical (1/3) becomes the posterior probability (1/2) when using information that the twins are the same gender. The prior is clearly updated with Pr( x = 1| y = 1) ≠ Pr( x = 1) in all but trivial cases; Amrheim et al. ’s statement that I quoted above is incorrect in this regard.

This possible confusion between uncertainty about these twins and uncertainty about the population level frequency of identical twins is further suggested by Amrhein et al. ’s statements:

“Second, for the uninformative prior, Efron mentions erroneously that he used a uniform distribution between zero and one, which is clearly different from the value of 0.5 that was used. Third, we find it at least debatable whether a prior can be called an uninformative prior if it has a fixed value of 0.5 given without any measurement of uncertainty.”

Note, if the prior for Pr( x = 1) is specified as 0.5, or dunif(0,1), or dbeta(0.5, 0.5), the posterior probability that these twins are identical is 2/3 in all cases. Efron (2013b) says the different priors lead to different results, but this result is incorrect, and the correct answer (2/3) is given in Efron (2013a) 3 . Nevertheless, a prior that specifies Pr( x = 1) = 0.5 does indicate uncertainty about whether this particular set of twins is identical (but certainty in the population level frequency of twins). And Efron’s (2013a) result is consistent with Pr( x = 1) having a uniform prior. Therefore, both claims in the quote above are incorrect.

It is probably easiest to show the (lack of) influence of the prior using MCMC sampling. Here is WinBUGS code for the case using Pr( x = 1) = 0.5.

Running this model in WinBUGS shows that the posterior mean of x is 2/3; this is the posterior probability that x = 1.

Instead of using pr_ident_twins <- 0.5, we could set this probability as being uncertain and define pr_ident_twins ~ dunif(0,1), or pr_ident_twins ~ dbeta(0.5,0.5). In either case, the posterior mean value of x remains 2/3 (contrary to Efron 2013b , but in accord with the correction in Efron 2013a ).

Note, however, that the value of the population level parameter pr_ident_twins is different in all three cases. In the first it remains unchanged at 1/2 where it was set. In the case where the prior distribution for pr_ident_twins is uniform or beta, the posterior distributions remain broad, but they differ depending on the prior (as they should – different priors lead to different posteriors 4 ). However, given the biased sample size of 1, the posterior distribution for this particular parameter is likely to be misleading as an estimate of the population-level frequency of twins.

So why doesn’t the choice of prior influence the posterior probability that these twins are identical? Well, for these three priors, the prior probability that any single set of twins is identical is 1/2 (this is essentially the mean of the prior distributions in these three cases).

If, instead, we set the prior as dbeta(1,2), which has a mean of 1/3, then the posterior probability that these twins are identical is 1/2. This is the same result as if we had set Pr( x = 1) = 1/3. In both these cases (choosing dbeta(1,2) or 1/3), the prior probability that a single set of twins is identical is 1/3, so the posterior is the same (1/2) given the data (the twins have the same gender).

Further, Amrhein et al. also seem to misunderstand the data. They note:

“Although there is one data point (a couple is due to be parents of twin boys, and the twins are fraternal)...”

This is incorrect. The parents simply know that the twins are both male. Whether they are fraternal is unknown (fraternal twins being the complement of identical twins) – that is the question the parents are asking. This error of interpretation makes the calculations in Box 1 and subsequent comments irrelevant.

Box 1 also implies Amrhein et al. are using the data to estimate the population frequency of identical twins rather than the state of this particular set of twins. This is different from the aim of Efron (2013a) and the stated question.

Efron suggests that Bayesian calculations should be checked with frequentist methods when priors are uncertain. However, this is a good example where this cannot be done easily, and Amrhein et al. are correct to point this out. In this case, we are interested in the probability that the hypothesis is true given the data (an inverse probability), not the probabilities that the observed data would be generated given particular hypotheses (frequentist probabilities). If one wants the inverse probability (the probability the twins are identical given they are the same gender), then Bayesian methods (andtherefore a prior) are required. A logical answer simply requires that the prior is constructed logically. Whether that answer is “correct” will be, in most cases, only known in hindsight.

However, one possible way to analyse this example using frequentist methods would be to assess the likelihood of obtaining the data for each of the two hypothesis (the twins are identical or fraternal). The likelihood of the twins having the same gender under the hypothesis that they are identical is 1. The likelihood of the twins having the same gender under the hypothesis that they are fraternal is 0.5. Therefore, the weight of evidence in favour of identical twins is twice that of fraternal twins. Scaling these weights so they sum to one ( Burnham and Anderson 2002 ), gives a weight of 2/3 for identical twins and 1/3 for fraternal twins. These scaled weights have the same numerical values as the posterior probabilities based on either a Laplace or Jeffreys prior. Thus, one might argue that the weight of evidence for each hypothesis when using frequentist methods is equivalent to the posterior probabilities derived from an uninformative prior. So, as a final aside in reference to Efron (2013a) , if we are being “violators” when using a uniform prior, are we also being “violators” when using frequentist methods to weigh evidence? Regardless of the answer to this rhetorical question, “checking” the results with frequentist methods doesn’t give any more insight than using uninformative priors (in this case). However, this analysis shows that the question can be analysed using frequentist methods; the single data point is not a problem for this. The claim in Armhein et al. that a frequentist analyis "is impossible because there is only one data point, and frequentist methods generally cannot handle such situations" is not supported by this example.

In summary, the comment by Amrhein et al. raises some interesting points that seem worth discussing, but it makes important errors in analysis and interpretation, and misrepresents the results of Efron (2013a) . This means the current version should not be approved.

Burnham, K.P. & D.R. Anderson. 2002. Model Selection and Multi-model Inference: a Practical Information-theoretic Approach. Springer-Verlag, New York.

Colyvan, M. 2008. Is Probability the Only Coherent Approach to Uncertainty? Risk Anal. 28: 645-652.

Efron B. (2003a) Bayes’ Theorem in the 21st Century. Science 340(6137): 1177-1178.

Efron B. (2013b) A 250-year argument: Belief, behavior, and the bootstrap. Bull Amer. Math Soc. 50: 129-146.

• The twins are both male. However, if the twins were both female, the statistical results would be the same, so I will simply use the data that the twins are the same gender.
• In reality, the frequency of twins that are identical is likely to vary depending on many factors but we will accept 1/3 for now.
• Efron (2013b) reports the posterior probability for these twins being identical as “a whopping 61.4% with a flat Laplace prior” but as 2/3 in Efron (2013a) . The latter (I assume 2/3 is “even more whopping”!) is the correct answer, which I confirmed via email with Professor Efron. Therefore, Efron (2013b) incorrectly claims the posterior probability is sensitive to the choice between a Jeffreys or Laplace uninformative prior.
• When the data are very informative relative to the different priors, the posteriors will be similar, although not identical.

I am very glad the authors wrote this essay. It is a well-written, needed, and useful summary of the current status of “data publication” from a certain perspective. The authors, however, need to be bolder and more analytical. This is an opinion piece, yet I see little opinion. A certain view is implied by the organization of the paper and the references chosen, but they could be more explicit.

The paper would be both more compelling and useful to a broad readership if the authors moved beyond providing a simple summary of the landscape and examined why there is controversy in some areas and then use the evidence they have compiled to suggest a path forward. They need to be more forthright in saying what data publication means to them, or what parts of it they do not deal with. Are they satisfied with the Lawrence et al. definition? Do they accept the critique of Parsons and Fox? What is the scope of their essay?

The authors take a rather narrow view of data publication, which I think hinders their analyses. They describe three types of (digital) data publication: Data as a supplement to an article; data as the subject of a paper; and data independent of a paper. The first two types are relatively new and they represent very little of the data actually being published or released today. The last category, which is essentially an “other” category, is rich in its complexity and encompasses the vast majority of data released. I was disappointed that the examples of this type were only the most bare-bones (Zenodo and Figshare). I think a deeper examination of this third category and its complexity would help the authors better characterize the current landscape and suggest paths forward.

Some questions the authors might consider: Are these really the only three models in consideration or does the publication model overstate a consensus around a certain type of data publication? Why are there different models and which approach is better for different situations? Do they have different business models or imply different social contracts? Might it also be worthy of typing “publishers” instead of “publications”? For example, do domain repositories vs. institutional repositories vs. publishers address the issues differently? Are these models sustaining models or just something to get us through the next 5-10 years while we really figure it out?

I think this oversimplification inhibited some deeper analysis in other areas as well. I would like to see more examination of the validation requirement beyond the lens of peer review, and I would like a deeper examination of incentives and credit beyond citation.

I thought the validation section of the paper was very relevant, but somewhat light. I like the choice of the term validation as more accurate than “quality” and it fits quite well with Callaghan’s useful distinction between technical and scientific review, but I think the authors overemphasize the peer-review style approach. The authors rightly argue that “peer-review” is where the publication metaphor leads us, but it may be a false path. They overstate some difficulties of peer-review (No-one looks at every data value? No, they use statistics, visualization, and other techniques.) while not fully considering who is responsible for what. We need a closer examination of different roles and who are appropriate validators (not necessarily conventional peers). The narrowly defined models of data publication may easily allow for a conventional peer-review process, but it is much more complex in the real-world “other” category. The authors discuss some of this in what they call “independent data validation,” but they don’t draw any conclusions.

Only the simplest of research data collections are validated only by the original creators. More often there are teams working together to develop experiments, sampling protocols, algorithms, etc. There are additional teams who assess, calibrate, and revise the data as they are collected and assembled. The authors discuss some of this in their examples like the PDS and tDAR, but I wish they were more analytical and offered an opinion on the way forward. Are there emerging practices or consensus in these team-based schemes? The level of service concept illustrated by Open Context may be one such area. Would formalizing or codifying some of these processes accomplish the same as peer-review or more? What is the role of the curator or data scientist in all of this? Given the authors’s backgrounds, I was surprised this role was not emphasized more. Finally, I think it is a mistake for science review to be the main way to assess reuse value. It has been shown time and again that data end up being used effectively (and valued) in ways that original experts never envisioned or even thought valid.

The discussion of data citation was good and captured the state of the art well, but again I would have liked to see some views on a way forward. Have we solved the basic problem and are now just dealing with edge cases? Is the “just-in-time identifier” the way to go? What are the implications? Will the more basic solutions work in the interim? More critically, are we overemphasizing the role of citation to provide academic credit? I was gratified that the authors referenced the Parsons and Fox paper which questions the whole data publication metaphor, but I was surprised that they only discussed the “data as software” alternative metaphor. That is a useful metaphor, but I think the ecosystem metaphor has broader acceptance. I mention this because the authors critique the software metaphor because “using it to alter or affect the academic reward system is a tricky prospect”. Yet there is little to suggest that data publication and corresponding citation alters that system either. Indeed there is little if any evidence that data publication and citation incentivize data sharing or stewardship. As Christine Borgman suggests, we need to look more closely at who we are trying to incentivize to do what. There is no reason to assume it follows the same model as research literature publication. It may be beyond the scope of this paper to fully examine incentive structures, but it at least needs to be acknowledged that building on the current model doesn’t seem to be working.

Finally, what is the takeaway message from this essay? It ends rather abruptly with no summary, no suggested directions or immediate challenges to overcome, no call to action, no indications of things we should stop trying, and only brief mention of alternative perspectives. What do the authors want us to take away from this paper?

Overall though, this is a timely and needed essay. It is well researched and nicely written with rich metaphor. With modifications addressing the detailed comments below and better recognizing the complexity of the current data publication landscape, this will be a worthwhile review paper. With more significant modification where the authors dig deeper into the complexities and controversies and truly grapple with their implications to suggest a way forward, this could be a very influential paper. It is possible that the definitions of “publication” and “peer-review” need not be just stretched but changed or even rejected.

• The whole paper needs a quick copy edit. There are a few typos, missing words, and wrong verb tenses. Note the word “data” is a plural noun. E.g., Data are not software, nor are they literature. (NSICD, instead of NSIDC)
• Page 2, para 2: “citability is addressed by assigning a PID.” This is not true, as the authors discuss on page 4, para 4. Indeed, page 4, para 4 seems to contradict itself. Citation is more than a locator/identifier.
• In the discussion of “Data independent of any paper” it is worth noting that there may often be linkages between these data and myriad papers. Indeed a looser concept of a data paper has existed for some time, where researchers request a citation to a paper even though it is not the data nor fully describes the data (e.g the CRU temp records)
• Page 4, para 1: I’m not sure it’s entirely true that published data cannot involve requesting permission. In past work with Indigenous knowledge holders, they were willing to publish summary data and then provide the details when satisfied the use was appropriate and not exploitive. I think those data were “published” as best they could be. A nit, perhaps, but it highlights that there are few if any hard and fast rules about data publication.
• Page 4, para 2: You may also want to mention the WDS certification effort, which is combining with the DSA via an RDA Working Group:
• Page 4, para 2: The joint declaration of data citation principles involved many more organizations than Force11, CODATA, and DCC. Please credit them all (maybe in a footnote). The glory of the effort was that it was truly a joint effort across many groups. There is no leader. Force11 was primarily a convener.
• Page 4, para 6: The deep citation approach recommended by ESIP is not to just to list variables or a range of data. It is to identify a “structural index” for the data and to use this to reference subsets. In Earth science this structural index is often space and time, but many other indices are possible--location in a gene sequence, file type, variable, bandwidth, viewing angle, etc. It is not just for “straightforward” data sets.
• Page 5, para 5: I take issue with the statement that few repositories provide scientific review. I can think of a couple dozen that do just off the top of my head, and I bet most domain repositories have some level of science review. The “scientists” may not always be in house, but the repository is a team facilitator. See my general comments.
• Page 5, para 10: The PDS system is only unusual in that it is well documented and advertised. As mentioned, this team style approach is actually fairly common.
• Page 6, para 3: Parsons and Fox don’t just argue that the data publication metaphor is limiting. They also say it is misleading. That should be acknowledged at least, if not actively grappled with.
• Artifact removal: Unfortunately the authors have not updated the paper with a 2x2 table showing guns and smiles by removed data points. This could dispel criticism that an asymmetrical expectation bias that has been shown to exist in similar experiments is not driving a bias leading to inappropriate conclusions.
• Artifact removal: Unfortunately the authors have not updated the paper with a 2x2 table showing guns and smiles by removed data points. This could dispel criticism that an asymmetrical expectation bias that has been shown to exist in similar experiments is not driving a bias leading to inappropriate conclusions. This is my strongest criticism of the paper and should be easily addressed as per my previous review comment. The fact that this simple data presentation was not performed to remove a clear potential source of spurious results is disappointing.
• The authors have added 95% CIs to figures S1 and S2. This clarifies the scope for expectation bias in these data. The addition of error bars permits the authors’ assumption of a linear trend, indicating that the effect of sequences of either guns or smiles may not skew results. Equally, there could be either a downwards or upwards trend fitting within the confidence intervals that could be indicative of a cognitive bias that may violate the assumptions of the authors, leading to spurious results. One way to remove these doubts could be to stratify the analyses by the length of sequences of identical symbols. If the results hold up in each of the strata, this potential bias could be shown to not be present in the data. If the bias is strong, particularly in longer runs, this could indicate that the positive result was due to small numbers of longer identical runs combined with a cognitive bias rather than an ability to predict future events.

Chamberlain and Szöcs present the taxize R package, a set of functions that provides interfaces to several web tools and databases, and simplifies the process of checking, updating, correcting and manipulating taxon names for researchers working with ecological/biological data. A key feature that is repeated throughout is the need for reproducibility of science workflows and taxize provides a means to achieve this within the R software ecosystem for taxonomic search.

The manuscript is well-written and nicely presented, with a good balance of descriptive text and discourse and practical illustration of package usage. A number of examples illustrate the scope of the package, something that is fully expanded upon in the two appendices, which are a welcome addition to the paper.

As to the package, I am not overly fond of long function names; the authors should consider dropping the data source abbreviations from the function names in a future update/revision of the package. Likewise there is some inconsistency in the naming conventions used. For example there is the ’tpl_search()’ function to search The Plant List, but the equivalent function to search uBio is ’ubio_namebank()’. Whilst this may reflect specific aspects of terminology in use at the respective data stores, it does not help the user gain familiarity with the package by having them remember inconsistent function names.

One advantage of taxize is that it draws together a rich selection of data stores to query. A further suggestion for a future update would be to add generic function names, that apply to a database connection/information object. The latter would describe the resource the user wants to search and any other required information, such as the API key, etc., for example:

The user function to search would then be ’search(foo, "Abies")’. Similar generically named functions would provide the primary user-interface, thus promoting a more consistent toolbox at the R level. This will become increasingly relevant as the scope of taxize increases through the addition of new data stores that the package can access.

In terms of presentation in the paper, I really don’t like the way the R code inputs merge with the R outputs. I know the author of Knitr doesn’t like the demarcation of output being polluted by the R prompt, but I do find it difficult parsing the inputs/outputs you show because often there is no space between them and users not familiar with R will have greater difficulties than I. Consider adding in more conventional indications of R outputs, or physically separate input from output by breaking up the chunks of code to have whitespace between the grey-background chunks. Related, in one location I noticed something amiss with the layout; in the first code block at the top of page 5, the printed output looks wrong here. I would expect the attributes to print on their own line and the data in the attribute to also be on its own separate line.

Note also, the inconsistency in the naming of the output object columns. For example, in the two code chunks shown in column 1 of page 4, the first block has an object printed with column names ’matched_name’ and ’data_source_title’, whilst camelCase is used in the outputs shown in the second block. As the package is revised and developed, consider this and other aspects of providing a consistent presentation to the user.

I was a little confused about the example in the section Resolve Taxonomic Names on page 4. Should the taxon name be “Helianthus annuus” or “Helianthus annus” ? In the ‘mynames’ definition you include ‘Helianthus annuus’ in the character vector but the output shown suggests that the submitted name was ‘Helianthus annus’ (1 “u”) in rows with rownames 9 and 10 in the output shown.

Other than that there were the following minor observations:

• Abstract: replace “easy” with “simple” in “...fashion that’s easy...” , and move the details about availability and the URI to the end of the sentence.
• Page 2, Column 1, Paragraph 2: You have “In addition, there is no one authoritative taxonomic names source...” , which is a little clumsy to read. How about “In addition, there is no one authoritative source of taxonomic names... ” ?
• Pg 2, C1, P2-3: The abbreviated data sources are presented first (in paragraph 2) and subsequently defined (in para 3). Restructure this so that the abbreviated forms are explained upon first usage.
• Pg 2, C2, P2: Most R packages are “in development” so I would drop the qualifier and reword the opening sentence of the paragraph.
• Pg 2, C2, P6: Change “and more can easily be added” to “and more can be easily added” seems to flow better?
• Pg 5, paragraph above Figure 1: You refer to converting the object to an **ape** *phylo* object and then repeat essentially the same information in the next sentence. Remove the repetition.
• Pg 6, C1: The header may be better as “Which taxa are children of the taxon of interest” .
• Pg 6: In the section “IUCN status”, the term “we” is used to refer to both the authors and the user. This is confusing. Reserve “we” for reference to the authors and use something else (“a user” perhaps) for the other instances. Check this throughout the entire manuscript.
• Pg 6, C2: in the paragraph immediately below the ‘grep()’ for “RAG1”, two consecutive sentences begin with “However”.
• Pg 7: The first sentence of “Aggregating data....” reads “In biology, one can asks questions...” . It should be “one asks” or “one can ask” .
• Pg 7, Conclusions: The first sentence reads “information is increasingly sought out by biologists” . I would drop “out” as “sought” is sufficient on its own.
• Appendices: Should the two figures in the Appendices have a different reference to differentiate them from Figure 1 in the main body of the paper? As it stands, the paper has two Figure 1s, one on page 5 and a second on page 12 in the Appendix.
• On Appendix Figure 2: The individual points are a little large. Consider reducing the plotting character size. I appreciate the effect you were going for with the transparency indicating density of observation through overplotting, but the effect is weakened by the size of the individual points.
• Should the phylogenetic trees have some scale to them? I presume the height of the stems is an indication of phylogenetic distance but the figure is hard to calibrate without an associated scale. A quick look at Paradis (2012) Analysis of Phylogenetics and Evolution with R would suggest however that a scale is not consistently applied to these trees. I am happy to be guided by the authors as they will be more familiar with the conventions than I.

Hydbring and Badalian-Very summarize in this review, the current status in the potential development of clinical applications based on miRNAs’ biology. The article gives an interesting historical and scientific perspective on a field that has only recently boomed.

Hydbring and Badalian-Very summarize in this review, the current status in the potential development of clinical applications based on miRNAs’ biology. The article gives an interesting historical and scientific perspective on a field that has only recently boomed; focusing mostly on the two main products in the pipeline of several biotech companies (in Europe and USA) which work with miRNAs-based agents, disease diagnostics and therapeutics. Interestingly, not only the specific agents that are being produced are mentioned, but also clever insights in the important cellular pathways regulated by key miRNAs are briefly discussed.

Minor points to consider in subsequent versions:

• Page 2; paragraph ‘Genomic location and transcription of microRNAs’ : the concept of miRNA clusters and precursors could be a bit better explained.
• Page 2; paragraph ‘Genomic location and transcription of microRNAs’ : when discussing the paper by the laboratory of Richard Young (reference 16); I think it is important to mention that that particular study refers to stem cells.
• Page 2; paragraph ‘Processing of microRNAs’ : “Argonate” should be replaced by “Argonaute”.
• Page 3; paragraph ‘MicroRNAs in disease diagnostics’ : are miR-15a and 16-1 two different miRNAs? I suggest mentioning them as: miR-15a and miR-16-1 and not using a slash sign (/) between them.
• Page 4; paragraph ‘Circulating microRNAs’ : I am a bit bothered by the description of multiple sclerosis (MS) only as an autoimmune disease. Without being an expert in the field, I believe that there are other hypotheses related to the etiology of MS.
• Page 5; paragraph ‘Clinical microRNA diagnostics’ : Does ‘hsa’ in hsa-miR-205 mean something?
• Page 5; paragraph ‘Clinical microRNA diagnostics’ : the authors mention the company Asuragen, Austin, TX, USA but they do not really say anything about their products. I suggest to either remove the reference to that company or to include their current pipeline efforts.
• Page 6; paragraph ‘MicroRNAs in therapeutics’ : in the first paragraph the authors suggest that miRNAs-based therapeutics should be able to be applied with “minimal side-effects”. Since one miRNA can affect a whole gene program, I found this a bit counterintuitive; I was wondering if any data has been published to support that statement. Also, in the same paragraph, the authors compare miRNAs to protein inhibitors, which are described as more specific and/or selective. I think there are now good indications to think that protein inhibitors are not always that specific and/or selective and that such a property actually could be important for their evidenced therapeutic effects.
• Page 6; paragraph ‘MicroRNAs in therapeutics’ : I think the concept of “antagomir” is an important one and could be better highlighted in the text.
• Throughout the text (pages 3, 5, 6, and 7): I am a bit bothered by separating the word “miRNA” or “miRNAs” at the end of a sentence in the following way: “miR-NA” or “miR-NAs”. It is a bit confusing considering the particular nomenclature used for miRNAs. That was probably done during the formatting and editing step of the paper.
• I was wondering if the authors could develop a bit more the general concept that seems to indicate that in disease (and in particular in cancer) the expression and levels of miRNAs are in general downregulated. Maybe some papers have been published about this phenomenon?

The authors describe their attempt to reproduce a study in which it was claimed that mild acid treatment was sufficient to reprogramme postnatal splenocytes from a mouse expressing GFP in the oct4 locus to pluripotent stem cells. The authors followed a protocol that has recently become available as a technical update of the original publication.

They report obtaining no pluripotent stem cells expressing GFP driven over the same time period of several days described in the original publication. They describe observation of some green fluorescence that they attributed to autofluorescence rather than GFP since it coincided with PI positive dead cells. They confirmed the absence of oct4 expression by RT-PCR and also found no evidence for Nanog or Sox2, also markers of pluripotent stem cells.

The paper appears to be an authentic attempt to reproduce the original study, although the study might have had additional value with more controls: “failure to reproduce” studies need to be particularly well controlled.

Examples that could have been valuable to include are:

• For the claim of autofluorescence: the emission spectrum of the samples would likely have shown a broad spectrum not coincident with that of GFP.
• The reprogramming efficiency of postnatal mouse splenocytes using more conventional methods in the hands of the authors would have been useful as a comparison. Idem the lung fibroblasts.
• There are no positive control samples (conventional mESC or miPSC) in the qPCR experiments for pluripotency markers. This would have indicated the biological sensitivity of the assay.
• Although perhaps a sensitive issue, it might have been helpful if the authors had been able to obtain samples of cells (or their mRNA) from the original authors for simultaneous analysis.

In summary, this is a useful study as it is citable and confirms previous blog reports, but it could have been improved by more controls.

The article is well written, treats an actual problem (the risk of development of valvulopathy after long-term cabergoline treatment in patients with macroprolactinoma) and provides evidence about the reversibility of valvular changes after timely discontinuation of DA treatment.

Title and abstract: The title is appropriate for the content of the article. The abstract is concise and accurately summarizes the essential information of the paper although it would be better if the authors define more precisely the anatomic specificity of valvulopathy – mild mitral regurgitation.

Case report: The clinical case presentation is comprehensive and detailed but there are some minor points that should be clarified:

• Please clarify the prolactin levels at diagnosis. In the Presentation section (line 3) “At presentation, prolactin level was found to be greater than 1000 ng/ml on diluted testing” but in the section describing the laboratory evaluation at diagnosis (line 7) “Prolactin level was 55 ng/ml”. Was the difference due to so called “hook effect”?
• Figure 1: In the text the follow-up MR imaging is indicated to be “after 10 months of cabergoline treatment” . However, the figures 1C and 1D represent 2 years post-treatment MR images. Please clarify.
• Figure 2: Echocardiograms 2A and 2B are defined as baseline but actually they correspond to the follow-up echocardiographic assessment at the 4th year of cabergoline treatment. Did the patient undergo a baseline (prior to dopamine agonist treatment) echocardiographic evaluation? If he did not, it should be mentioned as study limitation in the Discussion section.
• The mitral valve thickness was mentioned to be normal. Did the echographic examination visualize increased echogenicity (hyperechogenicity) of the mitral cusps?
• How could you explain the decrease of LV ejection fraction (from 60-65% to 50-55%) after switching from cabergoline to bromocriptine treatment and respectively its increase to 62% after doubling the bromocriptine daily dose? Was LV function estimated always by the same method during the follow-up?
• Final paragraph: Authors conclude that early discontinuation and management with bromocriptine may be effective in reversing cardiac valvular dysfunction. Even though, regular echocardiographic follow up should be considered in patients who are expected to be on long-term high dose treatment with bromocriptine regarding its partial 5-HT2b agonist activity.

This is an interesting topic: as the authors note, the way that communicators imagine their audiences will shape their output in significant ways. And I enjoyed what clearly has the potential to be a very rich data set.

This is an interesting topic: as the authors note, the way that communicators imagine their audiences will shape their output in significant ways. And I enjoyed what clearly has the potential to be a very rich data set. But I have some reservations about the adequacy of that data set, as it currently stands, given the claims the authors make; the relevance of the analytical framework(s) they draw upon; and the extent to which their analysis has offered significant new insights ‐ by which I mean, I would be keen to see the authors push their discussion further. My suggestions are essentially that they extend the data set they are working with to ensure that their analysis is both rigorous and generalisable, an re-consider the analytical frame they use. I will make some more concrete comments below.

With regard to the data: my feeling is that 14 interviews is a rather slim data set, and that this is heightened by the fact that they were all carried out in a single location, and recruited via snowball sampling and personal contacts. What efforts have the authors made to ensure that they are not speaking to a single, small, sub-community in the much wider category of science communicators? ‐ a case study, if you like, of a particular group of science communicators in North Carolina? In addition, though the authors reference grounded theory as a method for analysis, I got little sense of the data reaching saturation. The reliance on one-off quotes, and on the stories and interests of particular individuals, left me unsure as to how representative interview extracts were. I would therefore recommend either that the data set is extended by carrying out more interviews, in a wider variety of locations (e.g. other sites in the US), or that it is redeveloped as a case study of a particular local professional community. (Which would open up some fascinating questions ‐ how many of these people know each other? What spaces, online or offline, do they interact in, and do they share knowledge, for instance about their audiences? Are there certain touchstone events or publics they communally make reference to?)

As a more minor point with regard to the data set and what the authors want it to do, there were some inconsistencies as to how the study was framed. On p.2 they variously describe the purpose as to “understand the experiences and perspectives of science communicators” and the goals as identifying “the basic interests and value orientations attributed to lay audiences by science communicators”. Later, on p.5, they note that the “research is inductive and seeks to build theory rather than generalizable claims”, while in the Discussion they talk again about having identified communicators‘ “personal motivations” (p.12). There are a number of questions left hanging: is the purpose to understand communicator experiences ‐ in which case why focus on perceptions of audiences? Where is theory being built, and in what ways can this be mobilised in future work? The way that the study is framed and argued as a whole needs, I would suggest, to be clarified.

Relatedly, my sense is that some of this confusion is derived from what I find a rather busy analytical framework. I was not convinced of the value of combining inductive and deductive coding: if the ‘human value typology’ the authors use is ‘universal’, then what is added by open coding? Or, alternatively, why let their open coding, and their findings from this, be constrained by an additional, rather rigid, framework? The addition of the considerable literature on news values to the mix makes the discussion more confusing again. I would suggest that the authors either make much more clear the value of combining these different approaches ‐ building new theory outlining how they relate, and can be jointly mobilised in practice ‐ or fix on one. (My preference would be to focus on the findings from the open coding ‐ but that reflects my own disciplinary biases.)

A more minor analytical point: the authors note that their interviewees come from slightly different professions, and communicate through different formats, have different levels of experience, and different educational backgrounds ‐ but as far as I can see there is no comparative analysis based on this. Were there noticeable differences in the interview talk based on these categorisations? Or was the data set too small to identify any potential contrasts or themes? A note explaining this would be useful.

My final point has reference to the potential that this data set has, particularly if it is extended and developed. I would like to encourage the authors to take their analysis further: at the moment, I was not particularly surprised by the ways in which the communicators referenced news values or imagined their audiences. But it seems to me that the analytical work is not yet complete. What does it mean that communicators imagine audience values and preferences in the way that they do ‐ who is included and excluded by these imaginations? One experiment might be to consider what ‘ideal type’ publics are created in the communicators’ talk. What are the characteristics of the audiences constructed in the interviews and ‐ presumably ‐ in the communicative products of interviewees? What would these people look like? There are also some tantalizing hints in the Discussion that are not really discussed in the Findings ‐ of, for instance, the way in which communicator’s personal motivations may combine with their perceptions of audiences to shape their products. How does this happen? These are, of course, suggestions. But my wider point is that the authors need to show more clearly what is original and useful in their findings ‐ what it is, exactly, that will be important to other scholars in the field.

I hope my comments make sense ‐ please do not hesitate to contact me if not.

This is an interesting article and piece of software. I think it contributes towards further alternatives to easily visualize high dimensionality data on the web. It’s simple and easy to embed into other web frameworks or applications.

a) About the software

• CSV format . It was hard to guess the expected format. The authors need to add a syntax description of the CSV format at the help page.
• Simple HTML example . It will be easy to test HeatmapViewer (HmV) if you add a simple downloadable example file with the minimum required HTML-JavaScript to set up a HmV (without all the CSV import code).
• Color scale . HmV only implements a simple three point linear color scale. For me this is the major weakness of HmV. It will be very convenient that in the next HmV release the user can give as a parameter a function that manages the score to color conversion.

b) About the paper

• http://www.broadinstitute.org/gsea (desktop)
• http://jheatmap.github.io/jheatmap/ (website)
• http://www.gitools.org/ (desktop)
• http://blog.nextgenetics.net/demo/entry0044/ (website)
• http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html (python)
• http://matplotlib.org/api/pyplot_api.html (python)
• Predicted protein mutability landscape: The authors say: “Without using a tool such as the HeatmapViewer, we could hardly obtain an overview of the protein mutability landscape”. This paragraph seems to suggest that you can explore the data with HmV. I think that HmV is a good tool to report your data, but not to explore it.
• Conclusions: The authors say: “... provides a new, powerful way to generate and display matrix data in web presentations and in publications.” To use heat maps in web presentations and publications is nothing new. I think that HmV makes it easier and user-friendly, but it’s not new.

This article addresses the links between habitat condition and an endangered bird species in an important forest reserve (ASF) in eastern Kenya. It addresses an important topic, especially given ongoing anthropogenic pressures on this and similar types of forest reserves in eastern Kenya and throughout the tropics. Despite the rather small temporal and spatial extent of the study, it should make an important contribution to bird and forest conservation.

This article addresses the links between habitat condition and an endangered bird species in an important forest reserve (ASF) in eastern Kenya. It addresses an important topic, especially given ongoing anthropogenic pressures on this and similar types of forest reserves in eastern Kenya and throughout the tropics. Despite the rather small temporal and spatial extent of the study, it should make an important contribution to bird and forest conservation. There are a number of issues with the methods and analysis that need to be clarified/addressed however; furthermore, some of the conclusions overreach the data collected, while other important results are given less emphasis that they warrant. Below are more specific comments by section:

The conclusion that human-driven tree removal is an important contributor to the degradation of ASF is reasonable given the data reported in the article. Elephant damage, while clearly likely a very big contributor to habitat modification in ASF, was not the focus of the study (the authors state clearly in the Discussion that elephant damage was not systematically quantified, and thus no data were analyzed) ‐ and thus should only be mentioned in passing here ‐ if at all.

More information about the life history ecology of A. Sokokensis would provide welcome context here. A bit more detail about breeding sites as well as dispersal behavior etc. would be helpful – and especially why these and other aspects render the Pipit a good indicator species/proxy for habitat condition. This could be revisited in the Discussion as links are made between habitat conditions and occurrence of the bird (where you discuss the underlying mechanisms for why it thrives in some parts of ASF and not others, and why it’s abundance correlate strongly with some types of disturbance and not others). Again, you reference other studies that have explored other species in ASF and forest disturbance, but do not really explicitly state why the Pipit is a particularly important indicator of forest condition.

• Bird Survey: As described, all sightings and calls were recorded and incorporated into distance analysis – but it is not clear here whether or not distances to both auditory and visual encounters were measured the same way (i.e., with the rangefinder). Please clarify.
• Floor litter sampling: Not clear here whether or not litter cover was recorded as a continuous or categorical variable (percentage). If not, please describe percentage “categories” used.
• Mean litter depth graph (Figure 2) and accompanying text reports the means and sd but no post-hoc comparison test (e.g. Tukey HSD) – need to report the stats on which differences were/were not significant.
• Figure 3 – you indicate litter depth was better predictor of bird abundance than litter cover, but r-squared is higher for litter cover. Need to clarify (and also indicate why you chose only to shown depth values in Figure 3.
• The linear equation can be put in Figure 3 caption (not necessary to include in text).
• Figure 4 – stats aren’t presented here; also, the caption states that tree loss and leaf litter are inversely correlated – this might be taken to mean, given discussion (below) about pruning, that there could be a poaching threshold below which poaching may pay dividends to Pipits (and above which Pipits are negatively affected). This warrants further exploration/elaboration.
• The pruning result is arguably the most important one here – this suggests an intriguing trade-off between poaching and bird conservation (in particular, the suggestion that pruning by poachers may bolster Pipit populations – or at the very least mitigate against other aspects of habitat degradation). Worth highlighting this more in Discussion.
• Last sentence on p. 7 suggests causality (“That is because…”) – but your data only support correlation (one can imagine that there may have been other extrinsic or intrinsic drivers of population decline).
• P. 8: discussion of classification of habitat types in ASF is certainly interesting, but could be made much more succinct in keeping with focus of this paper.
• P. 9, top: first paragraph could be expanded – as noted before, tradeoff between poaching/pruning and Pipit abundance is worth exploring in more depth. Could your results be taken as a prescription for understory pruning as a conservation tool for the Sokoke Pipit or other threatened species? More detail here would be welcome (and also in Conclusion); in subsequent paragraph about Pipit foraging behavior and specific relationship to understory vegetation at varying heights could be incorporated into this discussion. Is there any info about optimal perch height for foraging or for flying through the understory? Linking to results of other studies in ASF, is there potential for positive correlations with optimal habitat conditions for the other important bird species in ASF in order to make more general conclusions about management?

Bierbach and co-authors investigated the topic of the evolution of the audience effect in live bearing fishes, by applying a comparative method. They specifically focused on the hypothesis that sperm competition risk, arising from male mate choice copying, and avoidance of aggressive interactions play a key role in driving the evolution of audience-induced changes in male mate choice behavior.

Bierbach and co-authors investigated the topic of the evolution of the audience effect in live bearing fishes, by applying a comparative method. They specifically focused on the hypothesis that sperm competition risk, arising from male mate choice copying, and avoidance of aggressive interactions play a key role in driving the evolution of audience-induced changes in male mate choice behavior. The authors found support to their hypothesis of an influence of SCR on the evolution of deceptive behavior as their findings at species level showed a positive correlation between mean sexual activity and the occurrence of deceptive behavior. Moreover, they found a positive correlation between mean aggressiveness and sexual activity but they did not detect a relationship between aggressiveness and audience effects.

The manuscript is certainly well written and attractive, but I have some major concerns on the data analyses that prevent me to endorse its acceptance at the present stage.

I see three main problems with the statistics that could have led to potentially wrong results and, thus, to completely misleading conclusions.

• First of all the Authors cannot run an ANCOVA in which there is a significant interaction between factor and covariate Tab. 2 (a). Indeed, when the assumption of common slopes is violated (as in their case), all other significant terms are meaningless. They might want to consider alternative statistical procedures, e.g. Johnson—Neyman method.
• Second, the Authors cannot retain into the model a non significant interaction term, as this may affect estimations for the factors Tab. 2 (d). They need to remove the species x treatment interaction (as they did for other non significant terms, see top left of the same page 7).
• The third problem I see regards all the GLMs in which species are compared. Authors entered the 'species' level as fixed factor when species are clearly a random factor. Entering species as fixed factors has the effect of badly inflating the denominator degrees of freedom, making authors’ conclusions far too permissive. They should, instead, use mixed LMs, in which species are the random factor. They should also take care that the degrees of freedom are approximately equal to the number of species (not the number of trials). To do so, they can enter as random factor the interaction between treatment and species.

Data need to be re-analyzed relying on the proper statistical procedures to confirm results and conclusions.

A more theoretical objection to the authors’ interpretation of results (supposing that results will be confirmed by the new analyses) could emerge from the idea that male success in mating with the preferred female may reduce the probability of immediate female’s re-mating, and thus reduce the risk of sperm competition on the short term. As a consequence, it may be not beneficial to significantly increase the risk of losing a high quality and inseminated female for a cost that will not be paid with certainty. The authors might want to consider also this for discussion.

Lastly, I think that the scenario generated from comparative studies at species level may be explained by phylogenetic factors other than sexual selection. Only the inclusion of phylogeny, that allow to account for the shared history among species, into data analyses can lead to unequivocal adaptive explanations for the observed patterns. I see the difficulty in doing this with few species, as it is the case of the present study, but I would suggest the Authors to consider also this future perspective. Moreover, a phylogenetic comparative study would be aided by the recent development of a well-resolved phylogenetic tree for the genus Poecilia (Meredith 2011).

Page 3: the authors should specify that also part of data on male aggressiveness (3 species from Table 1) come from previous studies, as they do for data on deceptive male mating behavior.

Page 5: since data on mate choice come from other studies is it so necessary to report a detailed description of methods for this section? Maybe the authors could refer to the already published methods and only give a brief additional description.

Page 6: how do the authors explain the complete absence of aggressive displays between the focal male and the audience male during the mate choice experiments? This sounds curious if considering that in all the examined species aggressive behaviors and dominance establishment are always observed during dyadic encounters.

In their response to my previous comments, the authors have clarified that only the data from the “Experimental phase” were used to calculate prediction accuracy. However, if I now understand the analysis procedure correctly, there are serious concerns with the approach adopted.

First, let me state what I now understand the analysis procedure to be:

• For each subject the PD values across the 20 trials were converted to z-scores.
• For each stimulus, the mean z-score was calculated.
• The sign of the mean z-score for each stimulus was used to make predictions.
• For each of the 20 trials, if the sign of the z-score on that trial was the same as for the mean z-score for that stimulus, a hit (correct prediction) was assigned. In contrast, if the sign of the z-score on that trial was the opposite as for the mean z-score for that stimulus, a miss (incorrect prediction) was assigned.
• For each stimulus the total hits and misses were calculated.
• Average hits (correct prediction) for each stimulus was calculated across subjects.

If this is a correct description of the procedure, the problem is that the same data were used to determine the sign of the z-score that would be associated with a correct prediction and to determine the actual correct predictions. This will effectively guarantee a correct prediction rate above chance.

To check if this is true, I quickly generated random data and used the analysis procedure as laid out above (see MATLAB code below). Across 10,000 iterations of 100 random subjects, the average “prediction” accuracy was ~57% for each stimulus (standard deviation, 1.1%), remarkably similar to the values reported by the authors in their two studies. In this simulation, I assumed that all subjects contributed 20 trials, but in the actual data analyzed in the study, some subjects contributed fewer than 20 trials due to artifacts in the pupil measurements.

If the above description of the analysis procedure is correct, then I think the authors have provided no evidence to support pupil dilation prediction of random events, with the results reflecting circularity in the analysis procedure.

However, if the above description of the procedure is incorrect, the authors need to clarify exactly what the analysis procedure was, perhaps by providing their analysis scripts.

I think this paper excellent and is an important addition to the literature. I really like the conceptualization of a self-replicating cycle as it illustrates the concept that the “problem” starts with the neuron, i.e., due to one or more of a variety of insults, the neuron is negatively impacted and releases H1, which in turn activates microglia with over expression of cytokines that may, when limited, foster repair but when activated becomes chronic (as is demonstrated here with the potential of cyclic H1 release) and thus facilitates neurotoxicity. I hope the authors intend to measure cytokine expression soon, especially IL-1 and TNF in both astrocytes and microglia, and S100B in astrocytes.

In more detail, Gilthorpe and colleagues provide novel experimental data that demonstrate a new role for a specific histone protein—the linker histone, H1—in neurodegeneration. This study, which was originally designed to identify axonal chemorepellents, actually provided a previously unknown role for H1, as well as other novel and thought provoking results. Fortuitously, as sometimes happens, the authors had a pleasant surprise: their results set some old dogmas on their respective ears and opened up new avenues of approach for studying the role of histones in self-amplification of neurodegenerative cycles. In point, they show that H1 is not just a nice little partner of nuclear DNA as previously thought. H1 is released from ‘damaged’ (or leaky) neurons, kills adjacent healthy neurons, and promotes a proinflammatory profile in both microglia and astrocytes.

Interestingly, the authors’ conceptualization of a damaged neuron → H1 release → healthy neuron killing cycle does not take into account the H1-mediated proinflammatory glial response. This facet of the study opens for these investigators a new avenue they may wish to follow: the role of H1 in stimulation of neuroinflammation with overexpression of cytokines. This is interesting, as neuronal injury has been shown to set in motion an acute phase response that activates glia, increases their expression of cytokines (interleukin-1 and S100B), which, in turn, induce neurons to produce excess Alzheimer-related proteins such as βAPP and ApoE (favoring formation of mature Aβ/ApoE plaques), activated MAPK-p38 and hyperphosphorylated tau (favoring formation of neurofibrillary tangles), and α synuclein (favoring formation of Lewy bodies). To date, the neuronal response shown responsible for stimulating glia is neuronal stress related release of sAPP, but these H1 results from Gilthorpe and colleagues may contribute to or exacerbate the role of sAPP.

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Which Source Should I Use?

• The Right Source For Your Need-Authority
• Finding Subject Specific Sources: Research Guides
• Understanding Peer Reviewed Articles
• Understanding Peer Reviewed Articles- Arts & Humanities
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• Locating Journals
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The Peer Review Process

So you need to use scholarly, peer-reviewed articles for an assignment...what does that mean? 

Peer review  is a process for evaluating research studies before they are published by an academic journal. These studies typically communicate  original research  or analysis for other researchers. 

The Peer Review Process at a Glance:

Looking for peer-reviewed articles?  Try searching in OneSearch or a library database  and look for options to limit your results to scholarly/peer-reviewed or academic journals. Check out this brief tutorial to show you how:   How to Locate a Scholarly (Peer Reviewed) Article

Part 1: Watch the Video

Part 1: watch the video all about peer review (3 min.) and reflect on discussion questions..

Discussion Questions

After watching the video, reflect on the following questions:

• According to the video, what are some of the pros and cons of the peer review process?
• Why is the peer review process important to scholarship?
• Do you think peer reviewers should be paid for their work? Why or why not?

Part 2: Practice

Part 2: take an interactive tutorial on reading a research article for your major..

Includes a certification of completion to download and upload to Canvas.

Social Sciences

(e.g. Psychology, Sociology)

(e.g. Health Science, Biology)

Arts & Humanities

(e.g. Visual & Media Arts, Cultural Studies, Literature, History)

Click on the handout to view in a new tab, download, or print.

For Instructors

• Teaching Peer Review for Instructors

In class or for homework, watch the video “All About Peer Review” (3 min.) .

Video discussion questions:

• According to the video, what are some of the pros and cons of the peer review process

Assignment Ideas

• Ask students to conduct their own peer review of an important journal article in your field. Ask them to reflect on the process. What was hard to critique?
• Have students examine a journals’ web page with information for authors. What information is given to the author about the peer review process for this journal?
• Assign this reading by CSUDH faculty member Terry McGlynn, "Should journals pay for manuscript reviews?" What is the author's argument? Who profits the most from published research? You could also hold a debate with one side for paying reviewers and the other side against.
• Search a database like Cabell’s for information on the journal submission process for a particular title or subject. How long does peer review take for a particular title? Is it is a blind review? How many reviewers are solicited? What is their acceptance rate?
• Assign short readings that address peer review models. We recommend this issue of Nature on peer review debate and open review and this Chronicle of Higher Education article on open review in Shakespeare Quarterly .

Proof of Completion

Mix and match this suite of instructional materials for your course needs!

Questions about integrating a graded online component into your class, contact the Online Learning Librarian, Rebecca Nowicki ( [email protected] ).

Example of a certificate of completion:

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Peer Review: An Introduction: Where to Find Peer Reviewed Sources

• Why not just use Google or Wikipedia?
• Where to Find Peer Reviewed Sources
• Where to Get More Help

Need More Help?

Have more questions? Contact Scholarly Communication and Publishing at [email protected]   for more information and guidance.

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Why is it so hard to find Peer-Reviewed Sources?

It isn't hard to find peer-reviewed sources: you just need to know where to look!  If you start in the right place, you can usually find a relevant, peer-reviewed source for your research in as few clicks as a Google search, and you can even use many of the search techniques you use in Google and Wikipedia.

The easiest way to find a peer-reviewed article is by using one of the Library's numerous databases. All of the Library's databases are listed in the Online Journals and Databases index. The databases are divided by name and discipline.

Departmental libraries and library subject guides have created subject-focused lists of electronic and print research resources that are useful for their disciplines. You can search the library directory  for links to the departmental libraries at the University of Illinois Library, or search library websites by college  if you're not sure which departmental library serves your subject.

Peer-Reviewed Resources for Disciplinary Topics

There are numerous print and digital resources for specific disciplines, areas of study, and specialist fields.  To find research resources and databases for your area, consult the comprehensive directory of LibGuides , the websites of specialist libraries, and above all, contact a librarian for help !

Here are a few major databases for finding peer-reviewed research sources in the humanities, social sciences, and sciences:

• MLA International Bibliography This link opens in a new window Indexes critical materials on literature, languages, linguistics, and folklore. Proved access to citations from worldwide publications, including periodicals, books, essay collections, working papers, proceedings, dissertations and bibliographies. Use MLA International Bibliography in the NEW EBSCO user interface . more... less... Alternate Access Link
• Web of Science (Core Collection) This link opens in a new window Web of Science indexes core journal articles, conference proceedings, data sets, and other resources in the sciences, social sciences, arts, and humanities.

A scholarly, multidisciplinary database providing indexing and abstracts for over 10,000 publications, including monographs, reports, conference proceedings, and others. Also includes full-text access to over 5,000 journals. Offers coverage of many areas of academic study including: archaeology, area studies, astronomy, biology, chemistry, civil engineering, electrical engineering, ethnic & multicultural studies, food science & technology, general science, geography, geology, law, mathematics, mechanical engineering, music, physics, psychology, religion & theology, women's studies, and other fields. 

Alternate Access Link  

• IEEE Xplore This link opens in a new window Provides full-text access to IEEE transactions, IEEE and IEE journals, magazines, and conference proceedings published since 1988, and all current IEEE standards; brings additional search and access features to IEEE/IEE digital library users. Browsable by books & e-books, conference publications, education and learning, journals and magazines, standards and by topic. Also provides links to IEEE standards, IEEE spectrum and other sites.
• Scopus This link opens in a new window Scopus is the largest abstract and citation database including peer-reviewed titles from international publishers, Open Access journals, conference proceedings, trade publications and quality web sources. Subject coverage includes: Chemistry, Physics, Mathematics and Engineering; Life and Health Sciences; Social Sciences, Psychology and Economics; Biological, Agricultural and Environmental Sciences.
• Business Source Ultimate This link opens in a new window Provides bibliographic and full text content, including indexing and abstracts for scholarly business journals back as far as 1886 and full text journal articles in all disciplines of business, including marketing, management, MIS, POM, accounting, finance and economics. The database full text content includes financial data, books, monographs, major reference works, book digests, conference proceedings, case studies, investment research reports, industry reports, market research reports, country reports, company profiles, SWOT analyses and more. Use Business Source Ultimate in the NEW EBSCO user interface . more... less... Alternate Access Link
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Articles: Finding (and Identifying) Peer-Reviewed Articles: What is Peer Review?

• What is Peer Review?
• Finding Peer Reviewed Articles
• Databases That Can Determine Peer Review

Peer Review in 3 Minutes

What is "Peer-Review"?

What are they.

Scholarly articles are papers that describe a research study. 

Why are scholarly articles useful?

They report original research projects that have been reviewed by other experts before they are accepted for publication, so you can reasonably be assured that they contain valid information. 

How do you identify scholarly or peer-reviewed articles?

• They are usually fairly lengthy - most likely at least 7-10 pages
• The authors and their credentials should be identified, at least the company or university where the author is employed
• There is usually a list of References or Works Cited at the end of the paper, listing the sources that the authors used in their research

How do you find them? 

Some of the library's databases contain scholarly articles, either exclusively or in combination with other types of articles. 

Google Scholar is another option for searching for scholarly articles. 

Know the Difference Between Scholarly and Popular Journals/Magazines

Peer reviewed articles are found in scholarly journals.  The checklist below can help you determine if what you are looking at is peer reviewed or scholarly.

• Both kinds of journals and magazines can be useful sources of information.
• Popular magazines and newspapers are good for overviews, recent news, first-person accounts, and opinions about a topic.
• Scholarly journals, often called scientific or peer-reviewed journals, are good sources of actual studies or research conducted about a particular topic. They go through a process of review by experts, so the information is usually highly reliable.

• Next: Finding Peer Reviewed Articles >>
• Last Updated: May 21, 2024 8:45 AM
• URL: https://libguides.usu.edu/peer-review

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Peer Review in Scientific Publications: Benefits, Critiques, & A Survival Guide

Jacalyn kelly.

1 Clinical Biochemistry, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada

Tara Sadeghieh

Khosrow adeli.

2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada

3 Chair, Communications and Publications Division (CPD), International Federation for Sick Clinical Chemistry (IFCC), Milan, Italy

The authors declare no conflicts of interest regarding publication of this article.

Peer review has been defined as a process of subjecting an author’s scholarly work, research or ideas to the scrutiny of others who are experts in the same field. It functions to encourage authors to meet the accepted high standards of their discipline and to control the dissemination of research data to ensure that unwarranted claims, unacceptable interpretations or personal views are not published without prior expert review. Despite its wide-spread use by most journals, the peer review process has also been widely criticised due to the slowness of the process to publish new findings and due to perceived bias by the editors and/or reviewers. Within the scientific community, peer review has become an essential component of the academic writing process. It helps ensure that papers published in scientific journals answer meaningful research questions and draw accurate conclusions based on professionally executed experimentation. Submission of low quality manuscripts has become increasingly prevalent, and peer review acts as a filter to prevent this work from reaching the scientific community. The major advantage of a peer review process is that peer-reviewed articles provide a trusted form of scientific communication. Since scientific knowledge is cumulative and builds on itself, this trust is particularly important. Despite the positive impacts of peer review, critics argue that the peer review process stifles innovation in experimentation, and acts as a poor screen against plagiarism. Despite its downfalls, there has not yet been a foolproof system developed to take the place of peer review, however, researchers have been looking into electronic means of improving the peer review process. Unfortunately, the recent explosion in online only/electronic journals has led to mass publication of a large number of scientific articles with little or no peer review. This poses significant risk to advances in scientific knowledge and its future potential. The current article summarizes the peer review process, highlights the pros and cons associated with different types of peer review, and describes new methods for improving peer review.

WHAT IS PEER REVIEW AND WHAT IS ITS PURPOSE?

Peer Review is defined as “a process of subjecting an author’s scholarly work, research or ideas to the scrutiny of others who are experts in the same field” ( 1 ). Peer review is intended to serve two primary purposes. Firstly, it acts as a filter to ensure that only high quality research is published, especially in reputable journals, by determining the validity, significance and originality of the study. Secondly, peer review is intended to improve the quality of manuscripts that are deemed suitable for publication. Peer reviewers provide suggestions to authors on how to improve the quality of their manuscripts, and also identify any errors that need correcting before publication.

HISTORY OF PEER REVIEW

The concept of peer review was developed long before the scholarly journal. In fact, the peer review process is thought to have been used as a method of evaluating written work since ancient Greece ( 2 ). The peer review process was first described by a physician named Ishaq bin Ali al-Rahwi of Syria, who lived from 854-931 CE, in his book Ethics of the Physician ( 2 ). There, he stated that physicians must take notes describing the state of their patients’ medical conditions upon each visit. Following treatment, the notes were scrutinized by a local medical council to determine whether the physician had met the required standards of medical care. If the medical council deemed that the appropriate standards were not met, the physician in question could receive a lawsuit from the maltreated patient ( 2 ).

The invention of the printing press in 1453 allowed written documents to be distributed to the general public ( 3 ). At this time, it became more important to regulate the quality of the written material that became publicly available, and editing by peers increased in prevalence. In 1620, Francis Bacon wrote the work Novum Organum, where he described what eventually became known as the first universal method for generating and assessing new science ( 3 ). His work was instrumental in shaping the Scientific Method ( 3 ). In 1665, the French Journal des sçavans and the English Philosophical Transactions of the Royal Society were the first scientific journals to systematically publish research results ( 4 ). Philosophical Transactions of the Royal Society is thought to be the first journal to formalize the peer review process in 1665 ( 5 ), however, it is important to note that peer review was initially introduced to help editors decide which manuscripts to publish in their journals, and at that time it did not serve to ensure the validity of the research ( 6 ). It did not take long for the peer review process to evolve, and shortly thereafter papers were distributed to reviewers with the intent of authenticating the integrity of the research study before publication. The Royal Society of Edinburgh adhered to the following peer review process, published in their Medical Essays and Observations in 1731: “Memoirs sent by correspondence are distributed according to the subject matter to those members who are most versed in these matters. The report of their identity is not known to the author.” ( 7 ). The Royal Society of London adopted this review procedure in 1752 and developed the “Committee on Papers” to review manuscripts before they were published in Philosophical Transactions ( 6 ).

Peer review in the systematized and institutionalized form has developed immensely since the Second World War, at least partly due to the large increase in scientific research during this period ( 7 ). It is now used not only to ensure that a scientific manuscript is experimentally and ethically sound, but also to determine which papers sufficiently meet the journal’s standards of quality and originality before publication. Peer review is now standard practice by most credible scientific journals, and is an essential part of determining the credibility and quality of work submitted.

IMPACT OF THE PEER REVIEW PROCESS

Peer review has become the foundation of the scholarly publication system because it effectively subjects an author’s work to the scrutiny of other experts in the field. Thus, it encourages authors to strive to produce high quality research that will advance the field. Peer review also supports and maintains integrity and authenticity in the advancement of science. A scientific hypothesis or statement is generally not accepted by the academic community unless it has been published in a peer-reviewed journal ( 8 ). The Institute for Scientific Information ( ISI ) only considers journals that are peer-reviewed as candidates to receive Impact Factors. Peer review is a well-established process which has been a formal part of scientific communication for over 300 years.

OVERVIEW OF THE PEER REVIEW PROCESS

The peer review process begins when a scientist completes a research study and writes a manuscript that describes the purpose, experimental design, results, and conclusions of the study. The scientist then submits this paper to a suitable journal that specializes in a relevant research field, a step referred to as pre-submission. The editors of the journal will review the paper to ensure that the subject matter is in line with that of the journal, and that it fits with the editorial platform. Very few papers pass this initial evaluation. If the journal editors feel the paper sufficiently meets these requirements and is written by a credible source, they will send the paper to accomplished researchers in the field for a formal peer review. Peer reviewers are also known as referees (this process is summarized in Figure 1 ). The role of the editor is to select the most appropriate manuscripts for the journal, and to implement and monitor the peer review process. Editors must ensure that peer reviews are conducted fairly, and in an effective and timely manner. They must also ensure that there are no conflicts of interest involved in the peer review process.

Overview of the review process

When a reviewer is provided with a paper, he or she reads it carefully and scrutinizes it to evaluate the validity of the science, the quality of the experimental design, and the appropriateness of the methods used. The reviewer also assesses the significance of the research, and judges whether the work will contribute to advancement in the field by evaluating the importance of the findings, and determining the originality of the research. Additionally, reviewers identify any scientific errors and references that are missing or incorrect. Peer reviewers give recommendations to the editor regarding whether the paper should be accepted, rejected, or improved before publication in the journal. The editor will mediate author-referee discussion in order to clarify the priority of certain referee requests, suggest areas that can be strengthened, and overrule reviewer recommendations that are beyond the study’s scope ( 9 ). If the paper is accepted, as per suggestion by the peer reviewer, the paper goes into the production stage, where it is tweaked and formatted by the editors, and finally published in the scientific journal. An overview of the review process is presented in Figure 1 .

WHO CONDUCTS REVIEWS?

Peer reviews are conducted by scientific experts with specialized knowledge on the content of the manuscript, as well as by scientists with a more general knowledge base. Peer reviewers can be anyone who has competence and expertise in the subject areas that the journal covers. Reviewers can range from young and up-and-coming researchers to old masters in the field. Often, the young reviewers are the most responsive and deliver the best quality reviews, though this is not always the case. On average, a reviewer will conduct approximately eight reviews per year, according to a study on peer review by the Publishing Research Consortium (PRC) ( 7 ). Journals will often have a pool of reviewers with diverse backgrounds to allow for many different perspectives. They will also keep a rather large reviewer bank, so that reviewers do not get burnt out, overwhelmed or time constrained from reviewing multiple articles simultaneously.

WHY DO REVIEWERS REVIEW?

Referees are typically not paid to conduct peer reviews and the process takes considerable effort, so the question is raised as to what incentive referees have to review at all. Some feel an academic duty to perform reviews, and are of the mentality that if their peers are expected to review their papers, then they should review the work of their peers as well. Reviewers may also have personal contacts with editors, and may want to assist as much as possible. Others review to keep up-to-date with the latest developments in their field, and reading new scientific papers is an effective way to do so. Some scientists use peer review as an opportunity to advance their own research as it stimulates new ideas and allows them to read about new experimental techniques. Other reviewers are keen on building associations with prestigious journals and editors and becoming part of their community, as sometimes reviewers who show dedication to the journal are later hired as editors. Some scientists see peer review as a chance to become aware of the latest research before their peers, and thus be first to develop new insights from the material. Finally, in terms of career development, peer reviewing can be desirable as it is often noted on one’s resume or CV. Many institutions consider a researcher’s involvement in peer review when assessing their performance for promotions ( 11 ). Peer reviewing can also be an effective way for a scientist to show their superiors that they are committed to their scientific field ( 5 ).

ARE REVIEWERS KEEN TO REVIEW?

A 2009 international survey of 4000 peer reviewers conducted by the charity Sense About Science at the British Science Festival at the University of Surrey, found that 90% of reviewers were keen to peer review ( 12 ). One third of respondents to the survey said they were happy to review up to five papers per year, and an additional one third of respondents were happy to review up to ten.

HOW LONG DOES IT TAKE TO REVIEW ONE PAPER?

On average, it takes approximately six hours to review one paper ( 12 ), however, this number may vary greatly depending on the content of the paper and the nature of the peer reviewer. One in every 100 participants in the “Sense About Science” survey claims to have taken more than 100 hours to review their last paper ( 12 ).

HOW TO DETERMINE IF A JOURNAL IS PEER REVIEWED

Ulrichsweb is a directory that provides information on over 300,000 periodicals, including information regarding which journals are peer reviewed ( 13 ). After logging into the system using an institutional login (eg. from the University of Toronto), search terms, journal titles or ISSN numbers can be entered into the search bar. The database provides the title, publisher, and country of origin of the journal, and indicates whether the journal is still actively publishing. The black book symbol (labelled ‘refereed’) reveals that the journal is peer reviewed.

THE EVALUATION CRITERIA FOR PEER REVIEW OF SCIENTIFIC PAPERS

As previously mentioned, when a reviewer receives a scientific manuscript, he/she will first determine if the subject matter is well suited for the content of the journal. The reviewer will then consider whether the research question is important and original, a process which may be aided by a literature scan of review articles.

Scientific papers submitted for peer review usually follow a specific structure that begins with the title, followed by the abstract, introduction, methodology, results, discussion, conclusions, and references. The title must be descriptive and include the concept and organism investigated, and potentially the variable manipulated and the systems used in the study. The peer reviewer evaluates if the title is descriptive enough, and ensures that it is clear and concise. A study by the National Association of Realtors (NAR) published by the Oxford University Press in 2006 indicated that the title of a manuscript plays a significant role in determining reader interest, as 72% of respondents said they could usually judge whether an article will be of interest to them based on the title and the author, while 13% of respondents claimed to always be able to do so ( 14 ).

The abstract is a summary of the paper, which briefly mentions the background or purpose, methods, key results, and major conclusions of the study. The peer reviewer assesses whether the abstract is sufficiently informative and if the content of the abstract is consistent with the rest of the paper. The NAR study indicated that 40% of respondents could determine whether an article would be of interest to them based on the abstract alone 60-80% of the time, while 32% could judge an article based on the abstract 80-100% of the time ( 14 ). This demonstrates that the abstract alone is often used to assess the value of an article.

The introduction of a scientific paper presents the research question in the context of what is already known about the topic, in order to identify why the question being studied is of interest to the scientific community, and what gap in knowledge the study aims to fill ( 15 ). The introduction identifies the study’s purpose and scope, briefly describes the general methods of investigation, and outlines the hypothesis and predictions ( 15 ). The peer reviewer determines whether the introduction provides sufficient background information on the research topic, and ensures that the research question and hypothesis are clearly identifiable.

The methods section describes the experimental procedures, and explains why each experiment was conducted. The methods section also includes the equipment and reagents used in the investigation. The methods section should be detailed enough that it can be used it to repeat the experiment ( 15 ). Methods are written in the past tense and in the active voice. The peer reviewer assesses whether the appropriate methods were used to answer the research question, and if they were written with sufficient detail. If information is missing from the methods section, it is the peer reviewer’s job to identify what details need to be added.

The results section is where the outcomes of the experiment and trends in the data are explained without judgement, bias or interpretation ( 15 ). This section can include statistical tests performed on the data, as well as figures and tables in addition to the text. The peer reviewer ensures that the results are described with sufficient detail, and determines their credibility. Reviewers also confirm that the text is consistent with the information presented in tables and figures, and that all figures and tables included are important and relevant ( 15 ). The peer reviewer will also make sure that table and figure captions are appropriate both contextually and in length, and that tables and figures present the data accurately.

The discussion section is where the data is analyzed. Here, the results are interpreted and related to past studies ( 15 ). The discussion describes the meaning and significance of the results in terms of the research question and hypothesis, and states whether the hypothesis was supported or rejected. This section may also provide possible explanations for unusual results and suggestions for future research ( 15 ). The discussion should end with a conclusions section that summarizes the major findings of the investigation. The peer reviewer determines whether the discussion is clear and focused, and whether the conclusions are an appropriate interpretation of the results. Reviewers also ensure that the discussion addresses the limitations of the study, any anomalies in the results, the relationship of the study to previous research, and the theoretical implications and practical applications of the study.

The references are found at the end of the paper, and list all of the information sources cited in the text to describe the background, methods, and/or interpret results. Depending on the citation method used, the references are listed in alphabetical order according to author last name, or numbered according to the order in which they appear in the paper. The peer reviewer ensures that references are used appropriately, cited accurately, formatted correctly, and that none are missing.

Finally, the peer reviewer determines whether the paper is clearly written and if the content seems logical. After thoroughly reading through the entire manuscript, they determine whether it meets the journal’s standards for publication,

and whether it falls within the top 25% of papers in its field ( 16 ) to determine priority for publication. An overview of what a peer reviewer looks for when evaluating a manuscript, in order of importance, is presented in Figure 2 .

How a peer review evaluates a manuscript

To increase the chance of success in the peer review process, the author must ensure that the paper fully complies with the journal guidelines before submission. The author must also be open to criticism and suggested revisions, and learn from mistakes made in previous submissions.

ADVANTAGES AND DISADVANTAGES OF THE DIFFERENT TYPES OF PEER REVIEW

The peer review process is generally conducted in one of three ways: open review, single-blind review, or double-blind review. In an open review, both the author of the paper and the peer reviewer know one another’s identity. Alternatively, in single-blind review, the reviewer’s identity is kept private, but the author’s identity is revealed to the reviewer. In double-blind review, the identities of both the reviewer and author are kept anonymous. Open peer review is advantageous in that it prevents the reviewer from leaving malicious comments, being careless, or procrastinating completion of the review ( 2 ). It encourages reviewers to be open and honest without being disrespectful. Open reviewing also discourages plagiarism amongst authors ( 2 ). On the other hand, open peer review can also prevent reviewers from being honest for fear of developing bad rapport with the author. The reviewer may withhold or tone down their criticisms in order to be polite ( 2 ). This is especially true when younger reviewers are given a more esteemed author’s work, in which case the reviewer may be hesitant to provide criticism for fear that it will damper their relationship with a superior ( 2 ). According to the Sense About Science survey, editors find that completely open reviewing decreases the number of people willing to participate, and leads to reviews of little value ( 12 ). In the aforementioned study by the PRC, only 23% of authors surveyed had experience with open peer review ( 7 ).

Single-blind peer review is by far the most common. In the PRC study, 85% of authors surveyed had experience with single-blind peer review ( 7 ). This method is advantageous as the reviewer is more likely to provide honest feedback when their identity is concealed ( 2 ). This allows the reviewer to make independent decisions without the influence of the author ( 2 ). The main disadvantage of reviewer anonymity, however, is that reviewers who receive manuscripts on subjects similar to their own research may be tempted to delay completing the review in order to publish their own data first ( 2 ).

Double-blind peer review is advantageous as it prevents the reviewer from being biased against the author based on their country of origin or previous work ( 2 ). This allows the paper to be judged based on the quality of the content, rather than the reputation of the author. The Sense About Science survey indicates that 76% of researchers think double-blind peer review is a good idea ( 12 ), and the PRC survey indicates that 45% of authors have had experience with double-blind peer review ( 7 ). The disadvantage of double-blind peer review is that, especially in niche areas of research, it can sometimes be easy for the reviewer to determine the identity of the author based on writing style, subject matter or self-citation, and thus, impart bias ( 2 ).

Masking the author’s identity from peer reviewers, as is the case in double-blind review, is generally thought to minimize bias and maintain review quality. A study by Justice et al. in 1998 investigated whether masking author identity affected the quality of the review ( 17 ). One hundred and eighteen manuscripts were randomized; 26 were peer reviewed as normal, and 92 were moved into the ‘intervention’ arm, where editor quality assessments were completed for 77 manuscripts and author quality assessments were completed for 40 manuscripts ( 17 ). There was no perceived difference in quality between the masked and unmasked reviews. Additionally, the masking itself was often unsuccessful, especially with well-known authors ( 17 ). However, a previous study conducted by McNutt et al. had different results ( 18 ). In this case, blinding was successful 73% of the time, and they found that when author identity was masked, the quality of review was slightly higher ( 18 ). Although Justice et al. argued that this difference was too small to be consequential, their study targeted only biomedical journals, and the results cannot be generalized to journals of a different subject matter ( 17 ). Additionally, there were problems masking the identities of well-known authors, introducing a flaw in the methods. Regardless, Justice et al. concluded that masking author identity from reviewers may not improve review quality ( 17 ).

In addition to open, single-blind and double-blind peer review, there are two experimental forms of peer review. In some cases, following publication, papers may be subjected to post-publication peer review. As many papers are now published online, the scientific community has the opportunity to comment on these papers, engage in online discussions and post a formal review. For example, online publishers PLOS and BioMed Central have enabled scientists to post comments on published papers if they are registered users of the site ( 10 ). Philica is another journal launched with this experimental form of peer review. Only 8% of authors surveyed in the PRC study had experience with post-publication review ( 7 ). Another experimental form of peer review called Dynamic Peer Review has also emerged. Dynamic peer review is conducted on websites such as Naboj, which allow scientists to conduct peer reviews on articles in the preprint media ( 19 ). The peer review is conducted on repositories and is a continuous process, which allows the public to see both the article and the reviews as the article is being developed ( 19 ). Dynamic peer review helps prevent plagiarism as the scientific community will already be familiar with the work before the peer reviewed version appears in print ( 19 ). Dynamic review also reduces the time lag between manuscript submission and publishing. An example of a preprint server is the ‘arXiv’ developed by Paul Ginsparg in 1991, which is used primarily by physicists ( 19 ). These alternative forms of peer review are still un-established and experimental. Traditional peer review is time-tested and still highly utilized. All methods of peer review have their advantages and deficiencies, and all are prone to error.

PEER REVIEW OF OPEN ACCESS JOURNALS

Open access (OA) journals are becoming increasingly popular as they allow the potential for widespread distribution of publications in a timely manner ( 20 ). Nevertheless, there can be issues regarding the peer review process of open access journals. In a study published in Science in 2013, John Bohannon submitted 304 slightly different versions of a fictional scientific paper (written by a fake author, working out of a non-existent institution) to a selected group of OA journals. This study was performed in order to determine whether papers submitted to OA journals are properly reviewed before publication in comparison to subscription-based journals. The journals in this study were selected from the Directory of Open Access Journals (DOAJ) and Biall’s List, a list of journals which are potentially predatory, and all required a fee for publishing ( 21 ). Of the 304 journals, 157 accepted a fake paper, suggesting that acceptance was based on financial interest rather than the quality of article itself, while 98 journals promptly rejected the fakes ( 21 ). Although this study highlights useful information on the problems associated with lower quality publishers that do not have an effective peer review system in place, the article also generalizes the study results to all OA journals, which can be detrimental to the general perception of OA journals. There were two limitations of the study that made it impossible to accurately determine the relationship between peer review and OA journals: 1) there was no control group (subscription-based journals), and 2) the fake papers were sent to a non-randomized selection of journals, resulting in bias.

JOURNAL ACCEPTANCE RATES

Based on a recent survey, the average acceptance rate for papers submitted to scientific journals is about 50% ( 7 ). Twenty percent of the submitted manuscripts that are not accepted are rejected prior to review, and 30% are rejected following review ( 7 ). Of the 50% accepted, 41% are accepted with the condition of revision, while only 9% are accepted without the request for revision ( 7 ).

SATISFACTION WITH THE PEER REVIEW SYSTEM

Based on a recent survey by the PRC, 64% of academics are satisfied with the current system of peer review, and only 12% claimed to be ‘dissatisfied’ ( 7 ). The large majority, 85%, agreed with the statement that ‘scientific communication is greatly helped by peer review’ ( 7 ). There was a similarly high level of support (83%) for the idea that peer review ‘provides control in scientific communication’ ( 7 ).

HOW TO PEER REVIEW EFFECTIVELY

The following are ten tips on how to be an effective peer reviewer as indicated by Brian Lucey, an expert on the subject ( 22 ):

1) Be professional

Peer review is a mutual responsibility among fellow scientists, and scientists are expected, as part of the academic community, to take part in peer review. If one is to expect others to review their work, they should commit to reviewing the work of others as well, and put effort into it.

2) Be pleasant

If the paper is of low quality, suggest that it be rejected, but do not leave ad hominem comments. There is no benefit to being ruthless.

3) Read the invite

When emailing a scientist to ask them to conduct a peer review, the majority of journals will provide a link to either accept or reject. Do not respond to the email, respond to the link.

4) Be helpful

Suggest how the authors can overcome the shortcomings in their paper. A review should guide the author on what is good and what needs work from the reviewer’s perspective.

5) Be scientific

The peer reviewer plays the role of a scientific peer, not an editor for proofreading or decision-making. Don’t fill a review with comments on editorial and typographic issues. Instead, focus on adding value with scientific knowledge and commenting on the credibility of the research conducted and conclusions drawn. If the paper has a lot of typographical errors, suggest that it be professionally proof edited as part of the review.

6) Be timely

Stick to the timeline given when conducting a peer review. Editors track who is reviewing what and when and will know if someone is late on completing a review. It is important to be timely both out of respect for the journal and the author, as well as to not develop a reputation of being late for review deadlines.

7) Be realistic

The peer reviewer must be realistic about the work presented, the changes they suggest and their role. Peer reviewers may set the bar too high for the paper they are editing by proposing changes that are too ambitious and editors must override them.

8) Be empathetic

Ensure that the review is scientific, helpful and courteous. Be sensitive and respectful with word choice and tone in a review.

Remember that both specialists and generalists can provide valuable insight when peer reviewing. Editors will try to get both specialised and general reviewers for any particular paper to allow for different perspectives. If someone is asked to review, the editor has determined they have a valid and useful role to play, even if the paper is not in their area of expertise.

10) Be organised

A review requires structure and logical flow. A reviewer should proofread their review before submitting it for structural, grammatical and spelling errors as well as for clarity. Most publishers provide short guides on structuring a peer review on their website. Begin with an overview of the proposed improvements; then provide feedback on the paper structure, the quality of data sources and methods of investigation used, the logical flow of argument, and the validity of conclusions drawn. Then provide feedback on style, voice and lexical concerns, with suggestions on how to improve.

In addition, the American Physiology Society (APS) recommends in its Peer Review 101 Handout that peer reviewers should put themselves in both the editor’s and author’s shoes to ensure that they provide what both the editor and the author need and expect ( 11 ). To please the editor, the reviewer should ensure that the peer review is completed on time, and that it provides clear explanations to back up recommendations. To be helpful to the author, the reviewer must ensure that their feedback is constructive. It is suggested that the reviewer take time to think about the paper; they should read it once, wait at least a day, and then re-read it before writing the review ( 11 ). The APS also suggests that Graduate students and researchers pay attention to how peer reviewers edit their work, as well as to what edits they find helpful, in order to learn how to peer review effectively ( 11 ). Additionally, it is suggested that Graduate students practice reviewing by editing their peers’ papers and asking a faculty member for feedback on their efforts. It is recommended that young scientists offer to peer review as often as possible in order to become skilled at the process ( 11 ). The majority of students, fellows and trainees do not get formal training in peer review, but rather learn by observing their mentors. According to the APS, one acquires experience through networking and referrals, and should therefore try to strengthen relationships with journal editors by offering to review manuscripts ( 11 ). The APS also suggests that experienced reviewers provide constructive feedback to students and junior colleagues on their peer review efforts, and encourages them to peer review to demonstrate the importance of this process in improving science ( 11 ).

The peer reviewer should only comment on areas of the manuscript that they are knowledgeable about ( 23 ). If there is any section of the manuscript they feel they are not qualified to review, they should mention this in their comments and not provide further feedback on that section. The peer reviewer is not permitted to share any part of the manuscript with a colleague (even if they may be more knowledgeable in the subject matter) without first obtaining permission from the editor ( 23 ). If a peer reviewer comes across something they are unsure of in the paper, they can consult the literature to try and gain insight. It is important for scientists to remember that if a paper can be improved by the expertise of one of their colleagues, the journal must be informed of the colleague’s help, and approval must be obtained for their colleague to read the protected document. Additionally, the colleague must be identified in the confidential comments to the editor, in order to ensure that he/she is appropriately credited for any contributions ( 23 ). It is the job of the reviewer to make sure that the colleague assisting is aware of the confidentiality of the peer review process ( 23 ). Once the review is complete, the manuscript must be destroyed and cannot be saved electronically by the reviewers ( 23 ).

COMMON ERRORS IN SCIENTIFIC PAPERS

When performing a peer review, there are some common scientific errors to look out for. Most of these errors are violations of logic and common sense: these may include contradicting statements, unwarranted conclusions, suggestion of causation when there is only support for correlation, inappropriate extrapolation, circular reasoning, or pursuit of a trivial question ( 24 ). It is also common for authors to suggest that two variables are different because the effects of one variable are statistically significant while the effects of the other variable are not, rather than directly comparing the two variables ( 24 ). Authors sometimes oversee a confounding variable and do not control for it, or forget to include important details on how their experiments were controlled or the physical state of the organisms studied ( 24 ). Another common fault is the author’s failure to define terms or use words with precision, as these practices can mislead readers ( 24 ). Jargon and/or misused terms can be a serious problem in papers. Inaccurate statements about specific citations are also a common occurrence ( 24 ). Additionally, many studies produce knowledge that can be applied to areas of science outside the scope of the original study, therefore it is better for reviewers to look at the novelty of the idea, conclusions, data, and methodology, rather than scrutinize whether or not the paper answered the specific question at hand ( 24 ). Although it is important to recognize these points, when performing a review it is generally better practice for the peer reviewer to not focus on a checklist of things that could be wrong, but rather carefully identify the problems specific to each paper and continuously ask themselves if anything is missing ( 24 ). An extremely detailed description of how to conduct peer review effectively is presented in the paper How I Review an Original Scientific Article written by Frederic G. Hoppin, Jr. It can be accessed through the American Physiological Society website under the Peer Review Resources section.

CRITICISM OF PEER REVIEW

A major criticism of peer review is that there is little evidence that the process actually works, that it is actually an effective screen for good quality scientific work, and that it actually improves the quality of scientific literature. As a 2002 study published in the Journal of the American Medical Association concluded, ‘Editorial peer review, although widely used, is largely untested and its effects are uncertain’ ( 25 ). Critics also argue that peer review is not effective at detecting errors. Highlighting this point, an experiment by Godlee et al. published in the British Medical Journal (BMJ) inserted eight deliberate errors into a paper that was nearly ready for publication, and then sent the paper to 420 potential reviewers ( 7 ). Of the 420 reviewers that received the paper, 221 (53%) responded, the average number of errors spotted by reviewers was two, no reviewer spotted more than five errors, and 35 reviewers (16%) did not spot any.

Another criticism of peer review is that the process is not conducted thoroughly by scientific conferences with the goal of obtaining large numbers of submitted papers. Such conferences often accept any paper sent in, regardless of its credibility or the prevalence of errors, because the more papers they accept, the more money they can make from author registration fees ( 26 ). This misconduct was exposed in 2014 by three MIT graduate students by the names of Jeremy Stribling, Dan Aguayo and Maxwell Krohn, who developed a simple computer program called SCIgen that generates nonsense papers and presents them as scientific papers ( 26 ). Subsequently, a nonsense SCIgen paper submitted to a conference was promptly accepted. Nature recently reported that French researcher Cyril Labbé discovered that sixteen SCIgen nonsense papers had been used by the German academic publisher Springer ( 26 ). Over 100 nonsense papers generated by SCIgen were published by the US Institute of Electrical and Electronic Engineers (IEEE) ( 26 ). Both organisations have been working to remove the papers. Labbé developed a program to detect SCIgen papers and has made it freely available to ensure publishers and conference organizers do not accept nonsense work in the future. It is available at this link: http://scigendetect.on.imag.fr/main.php ( 26 ).

Additionally, peer review is often criticized for being unable to accurately detect plagiarism. However, many believe that detecting plagiarism cannot practically be included as a component of peer review. As explained by Alice Tuff, development manager at Sense About Science, ‘The vast majority of authors and reviewers think peer review should detect plagiarism (81%) but only a minority (38%) think it is capable. The academic time involved in detecting plagiarism through peer review would cause the system to grind to a halt’ ( 27 ). Publishing house Elsevier began developing electronic plagiarism tools with the help of journal editors in 2009 to help improve this issue ( 27 ).

It has also been argued that peer review has lowered research quality by limiting creativity amongst researchers. Proponents of this view claim that peer review has repressed scientists from pursuing innovative research ideas and bold research questions that have the potential to make major advances and paradigm shifts in the field, as they believe that this work will likely be rejected by their peers upon review ( 28 ). Indeed, in some cases peer review may result in rejection of innovative research, as some studies may not seem particularly strong initially, yet may be capable of yielding very interesting and useful developments when examined under different circumstances, or in the light of new information ( 28 ). Scientists that do not believe in peer review argue that the process stifles the development of ingenious ideas, and thus the release of fresh knowledge and new developments into the scientific community.

Another issue that peer review is criticized for, is that there are a limited number of people that are competent to conduct peer review compared to the vast number of papers that need reviewing. An enormous number of papers published (1.3 million papers in 23,750 journals in 2006), but the number of competent peer reviewers available could not have reviewed them all ( 29 ). Thus, people who lack the required expertise to analyze the quality of a research paper are conducting reviews, and weak papers are being accepted as a result. It is now possible to publish any paper in an obscure journal that claims to be peer-reviewed, though the paper or journal itself could be substandard ( 29 ). On a similar note, the US National Library of Medicine indexes 39 journals that specialize in alternative medicine, and though they all identify themselves as “peer-reviewed”, they rarely publish any high quality research ( 29 ). This highlights the fact that peer review of more controversial or specialized work is typically performed by people who are interested and hold similar views or opinions as the author, which can cause bias in their review. For instance, a paper on homeopathy is likely to be reviewed by fellow practicing homeopaths, and thus is likely to be accepted as credible, though other scientists may find the paper to be nonsense ( 29 ). In some cases, papers are initially published, but their credibility is challenged at a later date and they are subsequently retracted. Retraction Watch is a website dedicated to revealing papers that have been retracted after publishing, potentially due to improper peer review ( 30 ).

Additionally, despite its many positive outcomes, peer review is also criticized for being a delay to the dissemination of new knowledge into the scientific community, and as an unpaid-activity that takes scientists’ time away from activities that they would otherwise prioritize, such as research and teaching, for which they are paid ( 31 ). As described by Eva Amsen, Outreach Director for F1000Research, peer review was originally developed as a means of helping editors choose which papers to publish when journals had to limit the number of papers they could print in one issue ( 32 ). However, nowadays most journals are available online, either exclusively or in addition to print, and many journals have very limited printing runs ( 32 ). Since there are no longer page limits to journals, any good work can and should be published. Consequently, being selective for the purpose of saving space in a journal is no longer a valid excuse that peer reviewers can use to reject a paper ( 32 ). However, some reviewers have used this excuse when they have personal ulterior motives, such as getting their own research published first.

RECENT INITIATIVES TOWARDS IMPROVING PEER REVIEW

F1000Research was launched in January 2013 by Faculty of 1000 as an open access journal that immediately publishes papers (after an initial check to ensure that the paper is in fact produced by a scientist and has not been plagiarised), and then conducts transparent post-publication peer review ( 32 ). F1000Research aims to prevent delays in new science reaching the academic community that are caused by prolonged publication times ( 32 ). It also aims to make peer reviewing more fair by eliminating any anonymity, which prevents reviewers from delaying the completion of a review so they can publish their own similar work first ( 32 ). F1000Research offers completely open peer review, where everything is published, including the name of the reviewers, their review reports, and the editorial decision letters ( 32 ).

PeerJ was founded by Jason Hoyt and Peter Binfield in June 2012 as an open access, peer reviewed scholarly journal for the Biological and Medical Sciences ( 33 ). PeerJ selects articles to publish based only on scientific and methodological soundness, not on subjective determinants of ‘impact ’, ‘novelty’ or ‘interest’ ( 34 ). It works on a “lifetime publishing plan” model which charges scientists for publishing plans that give them lifetime rights to publish with PeerJ, rather than charging them per publication ( 34 ). PeerJ also encourages open peer review, and authors are given the option to post the full peer review history of their submission with their published article ( 34 ). PeerJ also offers a pre-print review service called PeerJ Pre-prints, in which paper drafts are reviewed before being sent to PeerJ to publish ( 34 ).

Rubriq is an independent peer review service designed by Shashi Mudunuri and Keith Collier to improve the peer review system ( 35 ). Rubriq is intended to decrease redundancy in the peer review process so that the time lost in redundant reviewing can be put back into research ( 35 ). According to Keith Collier, over 15 million hours are lost each year to redundant peer review, as papers get rejected from one journal and are subsequently submitted to a less prestigious journal where they are reviewed again ( 35 ). Authors often have to submit their manuscript to multiple journals, and are often rejected multiple times before they find the right match. This process could take months or even years ( 35 ). Rubriq makes peer review portable in order to help authors choose the journal that is best suited for their manuscript from the beginning, thus reducing the time before their paper is published ( 35 ). Rubriq operates under an author-pay model, in which the author pays a fee and their manuscript undergoes double-blind peer review by three expert academic reviewers using a standardized scorecard ( 35 ). The majority of the author’s fee goes towards a reviewer honorarium ( 35 ). The papers are also screened for plagiarism using iThenticate ( 35 ). Once the manuscript has been reviewed by the three experts, the most appropriate journal for submission is determined based on the topic and quality of the paper ( 35 ). The paper is returned to the author in 1-2 weeks with the Rubriq Report ( 35 ). The author can then submit their paper to the suggested journal with the Rubriq Report attached. The Rubriq Report will give the journal editors a much stronger incentive to consider the paper as it shows that three experts have recommended the paper to them ( 35 ). Rubriq also has its benefits for reviewers; the Rubriq scorecard gives structure to the peer review process, and thus makes it consistent and efficient, which decreases time and stress for the reviewer. Reviewers also receive feedback on their reviews and most significantly, they are compensated for their time ( 35 ). Journals also benefit, as they receive pre-screened papers, reducing the number of papers sent to their own reviewers, which often end up rejected ( 35 ). This can reduce reviewer fatigue, and allow only higher-quality articles to be sent to their peer reviewers ( 35 ).

According to Eva Amsen, peer review and scientific publishing are moving in a new direction, in which all papers will be posted online, and a post-publication peer review will take place that is independent of specific journal criteria and solely focused on improving paper quality ( 32 ). Journals will then choose papers that they find relevant based on the peer reviews and publish those papers as a collection ( 32 ). In this process, peer review and individual journals are uncoupled ( 32 ). In Keith Collier’s opinion, post-publication peer review is likely to become more prevalent as a complement to pre-publication peer review, but not as a replacement ( 35 ). Post-publication peer review will not serve to identify errors and fraud but will provide an additional measurement of impact ( 35 ). Collier also believes that as journals and publishers consolidate into larger systems, there will be stronger potential for “cascading” and shared peer review ( 35 ).

CONCLUDING REMARKS

Peer review has become fundamental in assisting editors in selecting credible, high quality, novel and interesting research papers to publish in scientific journals and to ensure the correction of any errors or issues present in submitted papers. Though the peer review process still has some flaws and deficiencies, a more suitable screening method for scientific papers has not yet been proposed or developed. Researchers have begun and must continue to look for means of addressing the current issues with peer review to ensure that it is a full-proof system that ensures only quality research papers are released into the scientific community.

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Structure of Scholarly Articles and Peer Review: Peer Review

Created by health science librarians.

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• Compare Types of Journals

What is a Peer Reviewed Journal?

Examples of databases with a peer reviewed limit, use ulrichs to check peer reviewed status.

One of the main characteristics of scholarly journals is the process of peer review. Research articles under consideration for publication in a scholarly journal are sent to experts in the subject field (peers) for evaluation and comment (review). Journals following this process are sometimes called Refereed Journals.

• Peer Review in 3 Minutes Video tutorial created by North Carolina State University covers: how peer-reviewed articles are different from other types of publications; how peer-reviewed articles are tied to teaching and learning activities on college campuses; and where to go for help in finding peer-reviewed articles.
• Academic Search Premier Provides access to major popular and scholarly journals with many full-text articles. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. Coverage: Indexing, 1975-present; Full-text, 1975-present
• CINAHL Plus with Full Text CINAHL Plus with Full Text is a collection of more than 770 full text nursing & allied health journals dating as far back as 1937, with bibliographic indexing for more than 5,000 additional nursing and related journals. Also included are select health care books, nursing dissertations, conference proceedings, standards of practice, educational software, audiovisuals and book chapters. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. Coverage: 1982-present
• Health Source: Nursing/Academic Edition Indexing, abstracts and full-text for hundreds of nursing and allied health journals covering a variety of specialties including pediatric nursing, critical care, mental health, nursing management, medical law and many more. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. North Carolina residents with a borrower's card may access from off campus by visiting NCLive directly. Contact the Davis Library Service Desk for the NCLive password (instructions) . Coverage: Coverage varies; Indexing, 1974-present; Full-text, 1990-present
• PsycInfo Covers the academic research and practice literature in psychology. Covers journals, dissertations, book chapters, books, technical reports, and other documents from 1887 to the present. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. Coverage: 1887 - Present
• SPORTDiscus with Full Text Full-text and abstract database of journal and book literature on sports medicine, physical therapy, exercise science, sports, fitness, and related disciplines. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. Coverage: 1985 to present for full text; other indexing back to 1800

In these databases:

• Type the words you want to search in the box at the top
• Scroll down to the "Limit your results" section
• Select the "Peer Reviewed" check box
• Click the Search button

The following image is from CINAHL and shows the Peer Reviewed check box below the publication field. The Peer Reviewed check box may be in a slightly different place in the limit section of other databases. Not all databases provide the option to limit a search to peer reviewed articles.

• Ulrichs Web Online Ulrich's Periodicals Directory is a bibliographic database providing detailed, comprehensive, and authoritative information on serials published throughout the world. It covers all subjects and includes publications that are published regularly or irregularly and are circulated free of charge or by paid subscription. ULRICHSWEB.com is updated weekly and contains search and browse indexes--such as language and frequency--that are not found in the print version. In addition ULRICHSWEB.com links users to related serials for alternate titles and alternate media formats and contains tens of thousands of URLs and e-mail addresses for links to journals and publishers. ULRICHSWEB.com gives users access to serials information beyond the title level, with links to tables of contents, article abstracts, journal full-text, and document delivery. Note: Users will need to register for a free individual account to take advantage of the full functionality of this resource. more... less... Access: Off Campus Access is available for: UNC-Chapel Hill students, faculty, and staff; UNC Hospitals employees; UNC-Chapel Hill affiliated AHEC users. Coverage: Varies by periodical

Search Tip : Be sure to put quotations marks around phrases to make search results more specific. Select Advanced Search, enter a journal title or subject word(s), click search. Select Refereed / Peer-reviewed in the Narrow Results option.

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What is Peer Review?

If an article is peer reviewed , it was reviewed by scholars who are experts in related academic or professional fields before it was published. Those scholars assessed the quality of the article's research, as well as its overall contribution to the literature in their field. 

When we talk about peer-reviewed journals , we're referring to journals that use a peer-review process.

Related terms you might hear include: 

• Academic: Intended for academic use, or an academic audience. 
• Scholarly:  Intended for scholarly use, or a scholarly audience. 
• Refereed: Refers to a specific kind of peer-review process. 

National University Library System. (2018). "Find Articles: How to Find Scholarly/Peer-Reviewed Articles". Retrieved from: http://nu.libguides.com/articles/PR.

How Peer Review Works

 Here's how it typically works:

• Submission : An author submits their research paper or article to a scholarly journal for publication consideration.
• Editorial Assessment : The journal's editor(s) review the submission to determine if it meets the journal's scope, standards, and criteria for publication. They may reject it outright if it doesn't meet these criteria.
• Peer Review : If the submission passes the initial editorial assessment, it is sent out to experts in the field, known as "peers" or "referees," for thorough evaluation. These experts are typically researchers or scholars who have expertise in the subject matter of the submitted work but are not directly affiliated with the author.
• Peer Feedback : The peer reviewers carefully examine the submission for its originality, significance, methodology, accuracy, and overall quality. They provide detailed feedback, critiques, and suggestions for improvement to the journal's editor(s).
• Editorial Decision : Based on the feedback from the peer reviewers, the editor(s) make a decision on whether to accept the submission for publication, request revisions from the author(s) to address specific concerns, or reject it if it does not meet the journal's standards.
• Revision and Resubmission (if applicable): If revisions are requested, the author(s) revise their work in response to the reviewers' feedback and resubmit it to the journal. The revised version may undergo further rounds of peer review until it meets the journal's requirements.
• Publication : Once the submission has successfully passed peer review and any necessary revisions, it is accepted for publication and included in the journal's forthcoming issue.

Peer review serves as a critical checkpoint in the academic publishing process, helping to ensure that only high-quality, rigorously researched, and credible scholarly work is disseminated to the academic community and the public. It helps to uphold standards of academic integrity, accuracy, and reliability.

How Do I Know If a Journal is Peer-Reviewed?

The easiest way to find out if a journal is peer-reviewed is to search for the title in a serials directory like UlrichsWeb:

• UlrichsWeb Global Serials Directory Includes in each record: ISBN, title, publisher, country of publication, status (Active, ceased, etc.), start year, frequency, refereed (Yes/No), media, language, price, subject, Dewey #, circulation, editor(s), email, URL, brief description Also known as: Ulrichs

How to Use Ulrichs

1. Type the name of the journal in the search bar and click the search button. NOTE : you need to use the full name of the journal, not an abbreviation.

2. Locate the journal in the results list. You may see multiple entries for one journal because Ulrichs lists print, electronic, and international version separately.​​​​​​​

Other Techniques for Determining Peer Review Status

Determining whether an article has been peer-reviewed without a service like Ulrichs typically involves a few steps:

• Journal Reputation: Look at the journal where the article is published. Reputable academic journals usually have a peer-review process in place. Check the journal's website or databases like PubMed, Scopus, or Web of Science to see if it's peer-reviewed.
• Article Information: Sometimes, journals explicitly state whether articles undergo peer review. This information can usually be found on the journal's website, alongside other details about submission and publication processes.
• Author Guidelines: Journals often provide authors with guidelines that include information about the peer-review process. Authors are usually instructed to submit their work for peer review as part of the publication process.
• Editorial Policies: Review the journal's editorial policies. Peer-reviewed journals typically have detailed descriptions of their review processes, including how they select reviewers, criteria for acceptance, and timelines for review.
• Check the Article Itself: While this is not always conclusive, some peer-reviewed articles will include a statement indicating that the article has undergone peer review. Look for phrases like "peer-reviewed" and "refereed."
• Indexing Databases: Many indexing databases only include peer-reviewed journals in their listings. If you find the article indexed in databases like PubMed, you can generally assume it has been peer-reviewed.

Remember that while these methods can help you determine whether an article has undergone peer review, it's always good practice to critically evaluate the content of the article regardless of its peer-review status.

How Do I Know If an Article is Peer-Reviewed?

Even if an article was published in a peer-reviewed journal, it may not necessarily be peer-reviewed itself; for example, a commentary article may undergo editorial review instead, meaning it was only reviewed by the journal editor.

There are some clues you can look for to help you identify if an article is peer-reviewed:

• Does the abstract discuss the author's/authors' research process?
• Does the abstract include a variation of the phrase "This study..."?
• Is there a Methodology or Data header in the text of the article?
• Does the paper discuss related research in a literature review?
• Is there an analysis of a need for further research, or gaps in the literature?
• Are the references for scholarly articles and books?

If an article published in a verified peer-reviewed journal includes these elements, it is most likely a peer-reviewed article.

• National University Library: Scholarly Checklist Use this printable checklist to help you identify scholarly, research-based articles

Identifying Peer Reviewed Materials in Scholarly Databases

Peer reviewed material in pubmed and medline.

Good news! Most of the journals in Medline and PubMed are peer reviewed.  Generally speaking, if you find a journal citation in Medline and PubMed you should be just fine. However, there is no way to limit your results within PubMed or the Medline EBSCO interface to knock out the few publications that are not considered refereed titles.

However, EBSCO (a third-party vendor) does provide a list of all titles within Medline and lets you see which titles are considered peer reviewed. You can check if your journal is OK - see the "Peer Review" tab in the report below to see the very small list of titles that don't make the cut.

• Medline: List of Full-Text Journals These journals cover a wide range of subjects within the biomedical and health fields containing information needed by doctors, nurses, health professionals, and researchers engaged in clinical care, public health, and health policy development. Information on peer-reviewed status available within table of titles.

Peer Reviewed Material in CINAHL & PsycINFO

In CINAHL and PsycINFO, there is a "Peer Reviewed" box in the advanced search, which allows you to limit your search results to those that have been identified as peer reviewed.

• View the Title List for CINAHL Complete This page links to the full title list for CINAHL Complete in both Excel and HTML formats.
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Free APA Journals ™ Articles

Recently published articles from subdisciplines of psychology covered by more than 90 APA Journals™ publications.

For additional free resources (such as article summaries, podcasts, and more), please visit the Highlights in Psychological Research page.

• Basic / Experimental Psychology
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• Developmental Psychology
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• Social Psychology & Social Processes
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• What Is Peer Review? | Types & Examples

What Is Peer Review? | Types & Examples

Published on 6 May 2022 by Tegan George . Revised on 2 September 2022.

Peer review, sometimes referred to as refereeing , is the process of evaluating submissions to an academic journal. Using strict criteria, a panel of reviewers in the same subject area decides whether to accept each submission for publication.

Peer-reviewed articles are considered a highly credible source due to the stringent process they go through before publication.

There are various types of peer review. The main difference between them is to what extent the authors, reviewers, and editors know each other’s identities. The most common types are:

• Single-blind review
• Double-blind review
• Triple-blind review

Collaborative review

Open review.

Relatedly, peer assessment is a process where your peers provide you with feedback on something you’ve written, based on a set of criteria or benchmarks from an instructor. They then give constructive feedback, compliments, or guidance to help you improve your draft.

Table of contents

What is the purpose of peer review, types of peer review, the peer review process, providing feedback to your peers, peer review example, advantages of peer review, criticisms of peer review, frequently asked questions about peer review.

Many academic fields use peer review, largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the manuscript. For this reason, academic journals are among the most credible sources you can refer to.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Prevent plagiarism, run a free check.

Depending on the journal, there are several types of peer review.

Single-blind peer review

The most common type of peer review is single-blind (or single anonymised) review . Here, the names of the reviewers are not known by the author.

While this gives the reviewers the ability to give feedback without the possibility of interference from the author, there has been substantial criticism of this method in the last few years. Many argue that single-blind reviewing can lead to poaching or intellectual theft or that anonymised comments cause reviewers to be too harsh.

Double-blind peer review

In double-blind (or double anonymised) review , both the author and the reviewers are anonymous.

Arguments for double-blind review highlight that this mitigates any risk of prejudice on the side of the reviewer, while protecting the nature of the process. In theory, it also leads to manuscripts being published on merit rather than on the reputation of the author.

Triple-blind peer review

While triple-blind (or triple anonymised) review – where the identities of the author, reviewers, and editors are all anonymised – does exist, it is difficult to carry out in practice.

Proponents of adopting triple-blind review for journal submissions argue that it minimises potential conflicts of interest and biases. However, ensuring anonymity is logistically challenging, and current editing software is not always able to fully anonymise everyone involved in the process.

In collaborative review , authors and reviewers interact with each other directly throughout the process. However, the identity of the reviewer is not known to the author. This gives all parties the opportunity to resolve any inconsistencies or contradictions in real time, and provides them a rich forum for discussion. It can mitigate the need for multiple rounds of editing and minimise back-and-forth.

Collaborative review can be time- and resource-intensive for the journal, however. For these collaborations to occur, there has to be a set system in place, often a technological platform, with staff monitoring and fixing any bugs or glitches.

Lastly, in open review , all parties know each other’s identities throughout the process. Often, open review can also include feedback from a larger audience, such as an online forum, or reviewer feedback included as part of the final published product.

While many argue that greater transparency prevents plagiarism or unnecessary harshness, there is also concern about the quality of future scholarship if reviewers feel they have to censor their comments.

In general, the peer review process includes the following steps:

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to the author, or
• Send it onward to the selected peer reviewer(s)
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
• Lastly, the edited manuscript is sent back to the author. They input the edits and resubmit it to the editor for publication.

In an effort to be transparent, many journals are now disclosing who reviewed each article in the published product. There are also increasing opportunities for collaboration and feedback, with some journals allowing open communication between reviewers and authors.

It can seem daunting at first to conduct a peer review or peer assessment. If you’re not sure where to start, there are several best practices you can use.

Summarise the argument in your own words

Summarising the main argument helps the author see how their argument is interpreted by readers, and gives you a jumping-off point for providing feedback. If you’re having trouble doing this, it’s a sign that the argument needs to be clearer, more concise, or worded differently.

If the author sees that you’ve interpreted their argument differently than they intended, they have an opportunity to address any misunderstandings when they get the manuscript back.

Separate your feedback into major and minor issues

It can be challenging to keep feedback organised. One strategy is to start out with any major issues and then flow into the more minor points. It’s often helpful to keep your feedback in a numbered list, so the author has concrete points to refer back to.

Major issues typically consist of any problems with the style, flow, or key points of the manuscript. Minor issues include spelling errors, citation errors, or other smaller, easy-to-apply feedback.

The best feedback you can provide is anything that helps them strengthen their argument or resolve major stylistic issues.

Give the type of feedback that you would like to receive

No one likes being criticised, and it can be difficult to give honest feedback without sounding overly harsh or critical. One strategy you can use here is the ‘compliment sandwich’, where you ‘sandwich’ your constructive criticism between two compliments.

Be sure you are giving concrete, actionable feedback that will help the author submit a successful final draft. While you shouldn’t tell them exactly what they should do, your feedback should help them resolve any issues they may have overlooked.

As a rule of thumb, your feedback should be:

• Easy to understand
• Constructive

Below is a brief annotated research example. You can view examples of peer feedback by hovering over the highlighted sections.

Influence of phone use on sleep

Studies show that teens from the US are getting less sleep than they were a decade ago (Johnson, 2019) . On average, teens only slept for 6 hours a night in 2021, compared to 8 hours a night in 2011. Johnson mentions several potential causes, such as increased anxiety, changed diets, and increased phone use.

The current study focuses on the effect phone use before bedtime has on the number of hours of sleep teens are getting.

For this study, a sample of 300 teens was recruited using social media, such as Facebook, Instagram, and Snapchat. The first week, all teens were allowed to use their phone the way they normally would, in order to obtain a baseline.

The sample was then divided into 3 groups:

• Group 1 was not allowed to use their phone before bedtime.
• Group 2 used their phone for 1 hour before bedtime.
• Group 3 used their phone for 3 hours before bedtime.

All participants were asked to go to sleep around 10 p.m. to control for variation in bedtime . In the morning, their Fitbit showed the number of hours they’d slept. They kept track of these numbers themselves for 1 week.

Two independent t tests were used in order to compare Group 1 and Group 2, and Group 1 and Group 3. The first t test showed no significant difference ( p > .05) between the number of hours for Group 1 ( M = 7.8, SD = 0.6) and Group 2 ( M = 7.0, SD = 0.8). The second t test showed a significant difference ( p < .01) between the average difference for Group 1 ( M = 7.8, SD = 0.6) and Group 3 ( M = 6.1, SD = 1.5).

This shows that teens sleep fewer hours a night if they use their phone for over an hour before bedtime, compared to teens who use their phone for 0 to 1 hours.

Peer review is an established and hallowed process in academia, dating back hundreds of years. It provides various fields of study with metrics, expectations, and guidance to ensure published work is consistent with predetermined standards.

• Protects the quality of published research

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. Any content that raises red flags for reviewers can be closely examined in the review stage, preventing plagiarised or duplicated research from being published.

• Gives you access to feedback from experts in your field

Peer review represents an excellent opportunity to get feedback from renowned experts in your field and to improve your writing through their feedback and guidance. Experts with knowledge about your subject matter can give you feedback on both style and content, and they may also suggest avenues for further research that you hadn’t yet considered.

• Helps you identify any weaknesses in your argument

Peer review acts as a first defence, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process. This way, you’ll end up with a more robust, more cohesive article.

While peer review is a widely accepted metric for credibility, it’s not without its drawbacks.

• Reviewer bias

The more transparent double-blind system is not yet very common, which can lead to bias in reviewing. A common criticism is that an excellent paper by a new researcher may be declined, while an objectively lower-quality submission by an established researcher would be accepted.

• Delays in publication

The thoroughness of the peer review process can lead to significant delays in publishing time. Research that was current at the time of submission may not be as current by the time it’s published.

• Risk of human error

By its very nature, peer review carries a risk of human error. In particular, falsification often cannot be detected, given that reviewers would have to replicate entire experiments to ensure the validity of results.

Peer review is a process of evaluating submissions to an academic journal. Utilising rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication.

For this reason, academic journals are often considered among the most credible sources you can use in a research project – provided that the journal itself is trustworthy and well regarded.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field.

It acts as a first defence, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps:

• Reject the manuscript and send it back to author, or
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

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How to Recognize Peer-Reviewed (Refereed) Journals

Find all the information you need on recognizing and citing sources for your research papers. 

In many cases, professors will require that students utilize articles from “peer-reviewed” journals. Sometimes the phrases “refereed journals” or “scholarly journals” are used to describe the same type of journals. But what are peer-reviewed (or refereed or scholarly) journal articles, and why do faculty require their use?

Popular, Trade and Scholarly Information

• “Popular” newspapers and magazines containing news - Articles are written by reporters who may or may not be experts in the field of the article. Consequently, articles may contain incorrect information.
• Journals containing articles written by professionals and/or academics - Some trade or academic journals have articles that are written by a single person with little review. Although the articles are written by “experts,” any particular “expert” may have some ideas that are really “out there!”
• Peer-reviewed (refereed or scholarly) journals - Articles are written by experts and are reviewed by several other experts in the field before the article is published in the journal in order to ensure the article’s quality. (The article is more likely to be scientifically valid, reach reasonable conclusions, etc.) In most cases, the reviewers do not know who the author of the article is, so the article succeeds or fails on its own merit, not the reputation of the expert.

Helpful hint!

Not all information in a peer-reviewed journal is actually refereed or reviewed. For example, editorials, letters to the editor, book reviews and other types of information don’t count as articles, and may not be accepted by your professor.

How do you determine whether an article qualifies as a peer-reviewed journal article?

First, you need to be able to identify which journals are peer-reviewed. There are generally four methods for doing this

• Limiting a database search to peer-reviewed journals only. Some databases allow you to limit searches for articles to peer-reviewed journals only. For example, Academic Search Complete has this feature on the initial search screen - click on the pertinent box to limit the search. In some databases, you may have to go to an “advanced” or “expert” search screen to do this. Remember, many databases do not allow you to limit your search in this way.

• Locate the journal in the Library or online, then identify the most current entire year’s issues.
• Locate the masthead of the publication. This oftentimes consists of a box towards either the front or the end of the periodical and contains publication information such as the editors of the journal, the publisher, the place of publication, the subscription cost and similar information.
• Does the journal say that it is peer-reviewed? If so, you’re done! If not, move on to step d.
• Check in and around the masthead to locate the method for submitting articles to the publication.  If you find information similar to “to submit articles, send three copies…”, the journal is probably peer-reviewed. In this case, you are inferring that the publication is then going to send multiple copies of the article to the journal’s reviewers. This may not always be the case, so relying upon this criterion alone may prove inaccurate.
• If you do not see this type of statement in the first issue of the journal that you look at, examine the remaining journals to see if this information is included. Sometimes publications will include this information in only a single issue a year.
• Is it scholarly, using technical terminology? Does the article format approximate the following - abstract, literature review, methodology, results, conclusion, and references? Are the articles written by scholarly researchers in the field that the periodical pertains to? Is advertising non-existent, or kept to a minimum? Are there references listed in footnotes or bibliographies? If you answered yes to all these questions, the journal may very well be peer-reviewed. This determination would be strengthened by having met the previous criterion of a multiple-copies submission requirement. If you answered these questions no , the journal is probably not peer-reviewed.
• Find the official website on the internet, and check to see if it states that the journal is peer-reviewed. Be careful to use the official site (often located at the journal publisher’s website), and, even then, information could potentially be inaccurate. Unfortunately, there are online journals that claim to be peer-reviewed that aren’t. These are often created by publishers that are described by librarians as “predatory publishers.” To a great extent, you can avoid using articles from predatory publishers by finding them in database that are supplied by your library.

If you have used the previous four methods in trying to determine if an article is from a peer-reviewed journal and are still unsure, speak to your instructor.

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How to Find Scholarly, Peer-Reviewed Journal Articles

How to Identify a Scholarly, Peer-Reviewed Journal Article

• Peer Review & Academic/Scholarly Journals
• Finding Academic/Scholarly Journal Articles in Library Databases

Terms & Definitions

Scholar: A highly educated specialist who conducts research in a particular branch of study.

Periodical: A type of publication produced as an open-ended series at regular intervals, or “periods,” such as daily, monthly, quarterly or annually.

Scholarly/Academic Journal: A type of periodical that includes original research articles written by researchers and experts in a particular academic discipline, providing a forum for the production and critique of knowledge.

Research Article: A formally written article that describes new knowledge or ideas based on original research, analysis and/or interpretation.

Peer Review: The process by which scholars critically evaluate each other's research article before publication in an academic journal.

Editor: An individual who reviews, corrects, and determines the final content of a publication.

Scholarly Communication:  "The system through which research and other scholarly writings are created, evaluated for quality, disseminated to the scholarly community, and preserved for future use. The system includes both formal means of communication, such as publication in peer-reviewed journals, and informal channels, such as electronic listservs" (ACRL)

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Scholarly, peer-reviewed articles will have most of the characteristics listed below. Ask yourself these questions and look at the article to check if the way it looks and is written indicates it is a reliable, accurate source:

#wrapbox164195. headerbox { display: none; }

• Example of a Peer-Reviewed Journal Article
• Identifying Peer-Reviewed Research Articles
• Clues an Article is NOT Peer-Reviewed
• Types of Publications: Scholarly, Trade & Popular

The following terms and characteristics indicate an article is news or opinion-based information or published in a trade or professional journal. 

      •  Short title and abstract with simple, plain language 

      •  Provides advice, information and/or news of interest to a professional or practitioner of the discipline, field or industry

      •  Short or no reference list, footnotes and/or endnotes

      •  ​Advertising targeted at individuals or companies associated with the profession. For example: job boards, industry supplies/equipment

      •  Professional, educational, and opinion-based terms, such as:

• << Previous: Peer Review & Academic/Scholarly Journals
• Next: Finding Academic/Scholarly Journal Articles in Library Databases >>
• Last Updated: Jan 25, 2024 10:44 AM
• URL: https://bowvalleycollege.libguides.com/scholarly-articles

For Authors

• Why Publish in JAMA
• Instructions for Authors
• Submit Your Manuscript
• Author Reprints
• Permissions Requests

Editor in Chief

Kirsten Bibbins-Domingo, PhD, MD, MAS

Gregory Curfman, MD

Executive editor.

JAMA , published continuously since 1883, is an international peer-reviewed general medical journal. JAMA is a member of the JAMA Network, a consortium of peer-reviewed, general medical and specialty publications.

Journal Reach. JAMA is the most widely circulated general medical journal in the world, with more than 125,000 recipients of the print journal, more than 2.6 million recipients of electronic tables of contents and alerts, and over 30 million annual visits to the journal's website. JAMA 's reach includes a growing social media presence (more than 1.3 million social media followers [Facebook, X, Instagram, LinkedIn]) and vast international news media exposure.

Frequency of Publication and Access. JAMA is published 48 times per year in print/online issues, and new articles are published every weekday online. Without any author fees, all research articles are made free access online 6 months after publication on the JAMA website. In addition, the online version is freely available or nearly so to institutions in low- and middle-income countries through the World Health Organization's HINARI program.

Editorial Information. JAMA 's acceptance rate is 13% of the more than 10,000 annual submissions and 6% of the more than 5,000 research manuscripts received. JAMA 's Journal Impact Factor is 63.1, among the top 5 journals in medicine and science. For information about JAMA ’s reach and impact, decision and publication timelines, and author services, see below and the JAMA Editorial . For more information on the types of articles published and editorial policies, see the journal's Instructions for Authors .

Editorial Team. The Editor in Chief of JAMA is Kirsten Bibbins-Domingo, PhD, MD, MAS. See the Editors & Publishers for additional information on the journal's Editors and Editorial Board.

JAMA is a member of the International Committee of Medical Journal Editors , cosponsors the International Congress on Peer Review and Biomedical Publication , and is a member of the African Journal Partnership Project and is partnered with the Malawi Medical Journal .

JAMA 's Key and Critical Objectives

Key objective.

To promote the science and art of medicine and the betterment of the public health

Critical Objectives

• To maintain the highest standards of editorial integrity and quality independent of any special interests
• To publish original, important, valid, peer-reviewed articles on a diverse range of medical topics
• To promote and address diversity, equity, and inclusion within the journal and in medical research, clinical care, health policy, and society
• To foster responsible and balanced debate on important issues that affect medicine, health, health care, and health policy
• To provide physicians with continuing education in basic and clinical science to support informed clinical decisions and ongoing career development
• To enable physicians to remain informed in multiple areas of medicine, including developments in fields other than their own
• To improve health and health care internationally by elevating the quality of medical care, disease prevention, and research
• To inform readers about the various aspects of medicine and public health, including the cultural, sociopolitical, ethical, legal, environmental, economic, structural, and historical
• To recognize that, in addition to these specific objectives, JAMA has a social responsibility to improve equity and the total human condition, promulgate truth in science and medicine, and promote the integrity of science
• To achieve the highest level of ethical medical journalism and to produce a publication that is timely, credible, and enjoyable to read
• To use technologies to drive innovation and improve the communication of and access to journal content

JAMA ISSN 0098-7484 (Print) ISSN 1538-3598 (Online)

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Why Publish in JAMA ?

Published since 1883, JAMA offers unparalleled reach and an author-friendly approach from manuscript submission through publication. JAMA reaches physicians, other health professionals, researchers, policy makers, librarians, journalists, and others interested in medicine and public health throughout the world. JAMA provides the following:

Impact and Reach

• Journal Impact Factor of 63.1, among the top 5 journals in medicine and science
• Broad reach, with more than 2.6 million recipients of electronic alerts (eTable of Contents and Online First) and more than 1.3 million social media followers (Facebook, X, Instagram, LinkedIn)
• Over 62 million annual article views and downloads and the largest print circulation of any general medical journal, with more than 125,000 recipients worldwide
• Extensive press coverage, with over 122,000 media mentions in 2023 and 2024 in outlets such as The New York Times , The Washington Post , The Wall Street Journal , CNN, and the BBC
• Top Altmetric scores— JAMA published 14 of the top 50 articles among general medical journals
• Highlights of your article via weekly JAMA issue summary podcasts, audio and video interviews, and visual abstracts

Prompt Decisions and Rapid Publication Timelines

• Highly selective peer review and editorial evaluation, with 13% acceptance rate of the more than 10,000 annual submissions; 6% acceptance of the more than 5,000 research papers
• Median time to first decision: 3 days without external peer review; 31 days with review
• Fast publication: Median time from acceptance to online first publication for research manuscripts, 37 days; 47 days from acceptance to print publication
• JAMA Express: Expedited peer review and online publication within 4 weeks of submission for late-breaking research to be presented at major scientific meetings and those with time-sensitive findings of major clinical or public health importance.
• Coordination with meeting presentation:  Opportunity to publish new research simultaneously with your presentation

Author Service

JAMA offers unparalleled reach and an author-friendly approach, from manuscript submission through publication.

• User-friendly manuscript submission system and process
• Prompt, expert review and consideration from JAMA 's experienced editors
• Highest editorial standards followed to improve your accepted manuscript's accuracy, reliability, and readability
• CME credit available for lead authors who publish in JAMA
• Opportunity for your work to be augmented with expert illustration, interactive features, video, audio, and visual abstract
• Display of content on fast, device-responsive website
• Citations, views, and Altmetric score displayed with every article
• Free public access: All research articles are freely available 6 months after publication on the JAMA website
• Deposit to PubMed Central: The journal deposits all published research articles into PubMed Central (PMC) for authors
• Authors may post accepted research manuscripts in public repositories on or after publication provided that they link to the published article on the journal website
• JAMA Network advantage: Authors of papers not accepted by JAMA may have the option to have their papers and reviewers' comments automatically referred to one of the JAMA Network Specialty Journals and/or JAMA Network Open
• Dedicated media team to promote your article to the news media and on social media

Commitment to Equity

• JAMA Network journals welcome manuscript submissions on equity, diversity, and inclusion (EDI).
• For more information, see the JAMA Network EDI Editors, Policies, and Topic Collection

For more information, see JAMA's Mission and Objectives and Instructions for Authors .

Submit your manuscript at https://manuscripts.jama.com .

Questions? Contact us at [email protected] or call 312-464-4444.

Updated July 2024

JAMA Network Attendance at Conferences

JAMA Network attends a variety of medical conferences across specialties throughout the world. Learn more

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What is a peer-reviewed article?

"Peer-reviewed articles, also known as scholarly or refereed articles, are:

• Are written by experts in the field
• Are written for other researchers/scholars
• Are reviewed by the scholar's peers to determine whether they are high-quality pieces of work
• Use terms and language that are discipline-specific
• Usually include in-text citations and a bibliography of cited sources
• May include graphs, charts, etc., related to the topic
• Are published by a professional organization or society, university, research center, or scholarly press"

*Answered by  Woodruff Library Reference at Emory University

Primary Sources

What are Primary Sources?

Primary sources are documents, images or artifacts that provide firsthand testimony or direct evidence concerning an historical topic under research investigation. 

• archives and manuscript material
• photographs, audio recordings, video recordings, films
• journals, letters and diaries
• published books, newspapers and magazine clippings published at the time
• government publications
• oral histories
• records of organizations
• autobiographies and memoirs
• printed ephemera
• artifacts, e.g. clothing, costumes, furniture
• research data, e.g. public opinion polls

(information taken from UCI Libraries:  https://www.lib.uci.edu/introduction-primary-sources )

Using Key Words

Why Key Words Matter

Despite all the advances in web and database searching, computers still don't do well with meaning.

When you type a word into a search box, the computer looks only for the word you typed, not the concept you had in mind. To you, that word is an idea. To the computer, that word is a bunch of letters. 

So, the burden is on you, the researcher, to choose the best keywords with which to search. The keywords you choose have a direct and measurable effect on the results you get back. Even a small change in your keywords can lead to a big change in results.

Generating Key Words

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Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia

Bee-Ah Kang Roles: Conceptualization, Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Habtamu Tamene Roles: Conceptualization, Investigation, Methodology, Project Administration, Supervision, Validation, Writing – Original Draft Preparation Yihunie Lakew Roles: Investigation, Methodology, Supervision, Validation, Writing – Original Draft Preparation Daryl Stephens Roles: Writing – Review & Editing Rajiv Rimal Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation

Disproportionate uptake of and access to maternal and child health services remain significant challenges across and within countries. Differing geographic, economic, environmental, and social factors contribute to varying degrees of vulnerabilities among individuals, which manifest as disparities in maternal and newborn health outcomes. Designing solutions according to need is vital to improve maternal and child health outcomes. In this paper, we describe our study protocol on evaluating the effectiveness of an intervention package developed through a human-centered design (HCD) process in improving maternal health service uptake among vulnerable pregnant women in rural areas of Ethiopia.

The study has two distinct phases. For both phases, solutions will be developed leveraging HCD approaches to improve institutional delivery and antenatal care uptake among vulnerable pregnant women. Final solutions will be implemented in collaboration with community health workers and health officers. A community-based, quasi-experimental, mixed-method study design is used to assess differences between intervention and control arms. A panel sample will be enrolled after screening for pregnancy and vulnerability level and surveyed at baseline and midline in Phase 1. In Phase 2, a post-only study will be conducted in the same intervention and control sites. Pregnant women will receive refined solutions for six months, which will be evaluated using end-line assessment. Qualitative interviews will be conducted among vulnerable pregnant women and healthcare providers.

Conclusions and Implications

Our sequential approach to evaluating initial solutions, which in turn will be used to inform the enhancement of solutions, will provide practical insights into how solutions are accepted among vulnerable women and how they can be better integrated into women’s lives and health systems. Our findings on program effectiveness and implementation research will be disseminated to the Ethiopian Ministry of Health and its partners to inform large-scale implementation at the national level.

maternal and child health, vulnerability, human-centered design, research protocol

Introduction

Reducing maternal mortality ratio (MMR) has been one of the major priorities on the global health agenda. With the launch of the Sustainable Development Goals (SDG) in 2015, the World Health Organization (WHO) and partners reached a consensus on endorsing Target 3.1 that aims to reduce the global MMR to less than 70 per 100,000 livebirths by 2030. The target has shown a steady progress with its 34.3% reduction between 2000 and 2020 1 . However, such aggregated outcomes in health indicators often obscure disparities across countries and within sub-regions.

Ethiopia has shown steady improvements in many maternal and child health indicators over the past two decades. In 2000, the MMR was 871 deaths per 100,000 livebirths, and declined to 412 in 2016 2 . Between 2005 and 2019, under-5 mortality also decreased by 52% 3 . Despite this substantial progress, Ethiopia faces persistent health challenges. The MMR in-country accounts for 3.6% of global maternal mortalities 4 . Twenty-five percent of female deaths from the 2016 data were found to be from pregnancy-related causes 2 , and the neonatal mortality rate also increased by four points per 1,000 livebirths between 2016 and 2019 3 .

To achieve faster and more equitable improvements in maternal and child health outcomes, the government of Ethiopia has implemented a three-tiered health system with an intensive Health Extension Program, which takes a community-based approach to improving health knowledge, health-related skills, and access to primary healthcare 5 . In addition, the Health System Transformation Plan (HSTP-II) is being implemented from 2020 to 2025 with an overall objective to improve the population’s health status by accelerating progress towards universal health coverage, protecting populations during health emergencies, transforming woredas toward zero home delivery, and improving health system responsiveness 6 . The HSTP-II has a target to reduce the MMR to 279 per 100,000 live births and under-5 and neonatal mortalities to 44 and 21 per 1,000 live births, respectively 6 . Under these national goals, providing pregnant women with essential maternal health services, including institutional delivery (i.e., childbirth occurred at health facilities with skilled birth attendants), antenatal care (ANC), and iron and folic acid (IFA) supplementation, has been a key strategy for optimizing maternal and child health outcomes in Ethiopia. These maternal health services can significantly reduce the risk of maternal, perinatal and neonatal mortality in low- and middle-income countries (LMICs) and alleviate health disparities worldwide 7 – 9 .

Nevertheless, there remains an urgent need to address disproportionate uptake of and access to maternal health services in Ethiopia. Taking institutional delivery coverage as an example, women’s use of health facilities for childbirth greatly varies by region and sociodemographic characteristics. With the national average being approximately 48%, the percentage of institutional delivery use ranges from 23.3% in Somali Region to 94.8% in Addis Ababa, the capital city 3 . Also, 79% of women in the lowest wealth quintile delivered a baby at home; the corresponding figure for women in the highest wealth quintile was 14%. Parity is also associated with home delivery: women having six or more births are more likely to deliver at home, compared to those delivering for the first time.

Prior evidence suggests that women’s use of maternal health services is shaped by multiple factors at the socio-ecological continuum. Barriers to maternal health service uptake among pregnant women reside at multiple levels, including at the individual level (having poor knowledge of obstetric complications and danger signs, low risk perceptions, high parity, and no birth preparedness plans) 10 – 12 , social level (social and gender norms, support from family, decision-making power) 11 , 13 , 14 , cultural level (respect for elders, perception about pregnancy-related matters as women’s privacy, relationship with traditional birth attendants in the community) 3 , 15 – 17 , structural level (distance to health facilities, transportation and road infrastructure, costs for traveling) 11 , 15 , 18 , and those that are service-related (lack of services that respect women’s privacy and preferences, disrespectful treatment by health workers, and staff and medical supply shortages) 10 , 15 , 19 , 20 .

Understanding vulnerabilities of key target populations has important implications for developing and implementing tailored programs and policies 21 . Nevertheless, less attention has been paid to how vulnerability is defined, conceptualized and operationalized in the realm of maternal health service coverage 22 . Indeed, despite remarkable improvements in disease-focused service coverage, global health programs have been highlighted as neglecting inequity by not reaching the most disadvantaged population, straining weak local health systems, and distorting local health priorities and agendas 23 , 24 . Our project is based on the assumption that accurate and comprehensive assessment of vulnerability in maternal service uptake can help identify vulnerable pregnant women with the lowest likelihood of accessing necessary health services, which will subsequently help generate evidence and provide guidance on effective policies and interventions. Therefore, identifying the most vulnerable pregnant women and engaging them in program development would enhance the applicability, viability, and effectiveness of an intervention. Adopting user-oriented strategies, our study attempts to render vulnerable pregnant women an opportunity to take ownership of their problems and participate in generating solutions with the study team to cater to their unique needs, challenges, and hopes.

Furthermore, we argue for the need for conducting implementation research, given that determining true program effectiveness necessitates evidence on how an intervention fits in “real world” settings beyond a controlled study environment. Implementation research is distinguished from monitoring or process evaluation efforts due to its focused goals to explore 1) a program’s likelihood of being adopted and scaled up in real-world settings, 2) contextual factors that may facilitate or hinder implementation, 3) implementation strategies (rather than intervention strategies), 4) and the engagement of stakeholders to achieve successful implementation 25 . Well-designed implementation research provides an insight into whether an intervention would likely be integrated into its target environment, and more broadly, into health systems beyond study duration and scope. Implementation research also generates evidence that helps policy makers and implementers foresee challenges, contributing to saving costs and resources for future programs. Although there is no scientific consensus on what elements and principles are necessary for conducting implementation research, the WHO guide 26 encourages researchers to outline implementation research questions, use a framework that describes implementation research outcomes, and select a study design and methods that are most pertinent to understand how implementation occurs in a given context.

Study objectives

The objective of this study is to evaluate the effectiveness of an intervention package, developed through a human-centered design (HCD) process, in improving maternal health service (institutional delivery and ANC) uptake among highly vulnerable pregnant women living in rural areas of Ethiopia. Specifically, the study objectives are:

1. To assess whether changes in women from baseline to end-line in the intervention arm are significantly greater than corresponding changes in the control arm in the following outcomes: (a) institutional delivery and (b) ANC visits.

2. To explore how social and behavioral factors, including social norms, gender norms, women’s empowerment, and spousal dynamics, are associated with maternal health service uptake.

3. To understand the extent to which the intervention meets key implementation research outcomes, including fidelity, acceptability, feasibility, and sustainability, among pregnant women and health workers in the intervention arm.

Study setting

Our study sites are in Oromia, the most populous region in Ethiopia. Within this region, we selected two woredas (administrative units below the zone, which is below the region) for our intervention sites. Sirraro and Shalla woredas were selected as intervention arms, and Gera and Shebe woredas as control arms. The study sites were not randomly selected due to the on-going security issues in Ethiopia.

Study design

A community-based quasi-experimental study design was chosen to assess differences in key variables between the intervention and control arms. We chose a quasi-experimental design for several reasons. We lacked information about clear randomization unit given the characteristics of individuals or clusters (woredas), and it was likely that many woredas in Oromia region are not homogenous towards our outcomes of interest. Another reason was due to resource constraints, as we did not have a sufficient number of woredas in our study to conduct a randomized trial design. The study included two waves of data collection from a panel of recruited pregnant women at Phase 1. We attempt to leverage Phase 1 findings to inform the development of study tools and identify factors affecting implementation to provide insights into the improvement our intervention at Phase 2. This study is registered at ClinicalTrial.gov (NCT05907720).

We conducted the baseline survey of pregnant women enrolled in intervention and control arms in January 2024 and are in the process of conducting a midline assessment for Phase 1. After the baseline survey, we implemented a set of HCD prototype solutions in the intervention arm only, keeping standard of usual care intact in the control arm. After the 4-month period of HCD solution implementation, we are conducting the midline survey among the same women in the panel from both the intervention and control arms. The midline assessment includes in-depth interviews with purposively selected pregnant women from the panel and health workers who engaged in implementation.

In Phase 2, we will conduct a post-only study with a new sample of vulnerable pregnant women who will be recruited after the implementation of refined HCD solutions. We will apply the same recruitement procedures as those for Phase 1. We will compare outcomes between the intervention and control arms at end-line, and the end-line findings will also be compared with baseline to identify whether refined solutions bring greater impact than initial solutions did in Phase 1. Thus, our overall study design includes a total of three assessments, baseline and midline assessments in Phase 1 and end-line assessment in Phase 2. The study design is further described in Figure 1 .

Figure 1. Quasi-experimental evaluation study among vulnerable pregnant women.

Our primary target participants are vulnerable pregnant women aged 15–49. For consent administration, we segmented adult pregnant women aged 19 and above, pregnant adolescent girls aged 15–18, and service providers. Service providers, such as midwives, Health Extension Workers (HEWs) and Health Development Armies (HDAs) who engage in the study will be recruited for qualitative assessment at midline (Phase 1) and end-line (Phase 2). Table 1 below summarizes inclusion and exclusion criteria for each sample population.

Table 1. Summary of inclusion and exclusion criteria of study sample.

Sample size calculation

We considered institutional delivery (a major outcome variable) as a basis for the sample size calculation. To estimate sample size, we took account of our longitudinal design that measures the same subjects before and after the intervention and assumed an intervention effect of 9% in improving institutional delivery beyond the current 48% 3 . Assuming a p-value of 0.05, interclass correlation coefficient (ICC) of 0.009, a power of 80%, a total of 240 pregnant women from the intervention arm and another 240 pregnant women from the control arm are needed, for a total sample size of 480 pregnant women in each study phase. The assumptions of sample size also took account of feasibility and sample characteristics. The number of enumeration areas (EAs) this phase can reach is 80 per study arm, and approximately 5 women are expected to be eligible in each EA. Based on the cross-sectional study design in Phase 2, we assumed 9% detectable difference between the study arms with an 80% power, which led to a sample of 531 for each study arm, taking account of 10% non-response rate. Approximately 106 EAs will be reached from given the number of eligible women in each EA. Both intervention and control arms will have an equal sample size in each phase, having 1:1 ratio of women between the intervention and control arms. As such, the total number of women to recruit across study phases is 1542.

For qualitative assessments, a total of 32 health workers engaged in implementation will be purposively sampled for in-depth interviews at post-intervention assessment in each phase. The interviews with health workers will explore the feasibility, acceptability, and scalability of the prototype solutions along with perceived program effects. An equal number of health workers will be interviewed at midline (post-intervention of Phase 1) and end-line (post-intervention of Phase 2). The interviewees selected for Phase 2 may be the same service providers recruited from Phase 1 depending on their availability and engagement in the program. We have chosen 32 as the target sample size based on our best estimate about achieving data saturation. In each phase, we will also interview 20 pregnant women from the panel who recently delivered and were exposed to our HCD solutions. The qualitative iterviews will be conducted only in the intervention sites.

Recruitment

After obtaining a list of all interested women from HEWs and HDAs, data collectors will visit the women in person to screen their pregnancy status and vulnerability level to assess their eligibility. With the woman’s verbal consent, the data collector will administer the pregnancy screening tool to identify her pregnancy status. Only women 5+ months of pregnancy and aged 15–49 are considered eligible. If eligible, she will then be screened for her vulnerability level, assessed through the vulnerability screening tool. Those considered to be moderately to highly vulnerable are eligible and entered into the sampling frame. All responses to the screening questions will be entered into the data collectors’ mobile phone application that automatically determines pregnant women’s eligibility during the visit. Women who score at most 13 out of the maximum 20 vulnerability screening questions will be identified for the study participant. For the qualitative assessment, recently delivered women who receive our intervention and health workers in the intervention sites will be recruited. Purposive selection of the sample will take into account the extent to which women are exposed to the intervention. We will prioritize recruiting women in earlier gestational ages (5 th month or earlier) since women in late pregnancy terms may not be fully exposed to our solutions.

All eligible women will be entered into our sampling frame. After listing eligible pregnant women, we aim to recruit approximately three women per EA to achieve our target sample size. If an EA has five or fewer eligible women, they will be all contacted for recruitment. If there are more pregnant women than the minimum required number of pregnant women, we will randomly select the required number. If a woman is not interested or available for participation, we will contact the next randomly selected woman for recruitment. Recruitment will continue until our sample size is reached, expanding to other EAs if necessary. Recruitment in Phase 1 has been completed in this way, and Phase 2 recruitment will follow this procedure.

Data collection and measurement

Survey interview . All participant from Phase 1 and 2 will undergo a one-on-one survey interview to assess sociodemographic information, psychological factors, social and structural factors, and maternal health service utilization. A structured interview will be administered by a local data collector in the local language. The survey will capture the self-reported place of the most recent childbirth along with uptake and frequency of ANC visits during the most recent pregnancy. Secondary outcomes include knowledge, attitudes, and perceptions about maternal health service utilization, social norms, gender norms, spousal dynamics, decision-making, and community and structural factors. Midline (post-intervention in Phase 1) and end-line (post-intervention in Phase 2) assessments will additionally include questions measuring program exposure.

Qualitative interview . Purposively selected women from the study participants (n=20) along with health workers (n=32) engaged in the program will participate in an in-depth interview. Given the 4-month duration of program implementation among pregnant women in their 5 th or higher months of pregnancy, interviews will be administered to recently delivered women inquiring about their perceived effects of the intervention on the place of childbirth and ANC uptake during pregnancy. Additionally, the interview guides for women and health workers will contain question around key implementation research outcomes, including acceptability and feasibility, to identify any similarities and differences arising across different types of interview participants.

Intervention

HCD workshop procedure . In Phase 1, prior to the HCD process, an extensive desk review and secondary data analysis were conducted to identify key drivers of vulnerability affecting uptakes of maternal and child health services. Vulnerability driving factors, such as women's illiteracy, distance from health facilities, high parity, decision making power, exposure to media, and lack of household assets were identified as major barriers to maternal health service use. Based on these factors, a vulnerability screening algorithm was developed to identify the target population of rural vulnerable pregnant women. From the evidence synthesis, the two initial design challenges focusing on ANC and institutional delivery were also prioritized: 1) reimagining how to support pregnant women to attend ANC, and 2) reimagining how to support pregnant women to deliver in a health center. Then, a five-stage design thinking process was implemented, using empathy, definition, ideation, prototyping, and testing stages. In this process, we engaged key stakeholders, such as vulnerable pregnant women, their husbands, and healthcare providers in co-creation workshops.

The co-creation workshops were separately organized for vulnerable pregnant women, husbands of vulnerable pregnant women, and healthcare providers to form homogeneous groups and avoid power dynamics for better flow of information and ideas. A total of eight design teams, each comprising six to eight design team members, went through the design thinking process for three days. A core team that involved senior design staff further synthesized the outputs of the workshops. Insights around limited household support for pregnant women, low awareness on importance of healthcare services, demotivated healthcare providers, and poor service quality were harvested from these workshops.

Development of HCD solutions . In the prototyping phase, our team prioritized potential prototype solutions based on an impact and feasibility matrix. The matrix served as a grading system to narrow down prototype solutions from those that were initially ideated among workshop participants based on the two dimensions. According to participants’ perceived impact (low or high) of solutions on institutional and ANC uptake, along with perceived feasibility level (less or more likely to be implemented) pertaining to resource constraints, three solutions were selected: audio programs that encourage couple communication, visual print materials, and home-to-home visits by community health workers.

The study team developed two pre-recorded audio programs containing real stories of pregnant women in the local language of the target area. The first audio session focuses on the importance of ANC through the narration of a couple's story, highlighting their communication and the husband's support in household tasks, as well as accompanying the wife to ANC visits. The second audio session focuses on the importance of institutional delivery from a story of a pregnant woman. It describes her first childbirth at home, which was a painful and difficult experience. The story then progresses to her second childbirth experience at a health facility, where she was well-prepared and supported by her husband. Furthermore, the solutions included two visual print materials (pamphlets) with contents that reinforced the audio messages about ANC and institutional delivery. These prototypes were tested through focus group discussions with pregnant women, their husbands, and community volunteers, and then refined based on user feedback. All five of the design thinking stages were implemented in the two study sites (Shalla and Siraro) of Oromia regional state.

For Phase 2, we aim to leverage implementation research data obtained from midline qualitative interviews at Phase 1 to finalize our HCD plans. Solutions from Phase 1 will be revisited by a newly organized design team to collectively explore the most effective and feasible implementation strategies. We will conduct the five-stage HCD process, sharing Phase 1 findings with workshop participants and engaging prior end-users. Since Phase 2 will focus on refining and strengthening the existing solutions, some of the HCD activities (e.g., “How Might We” statements and ideation) are expected to center around establishing strategies for improving the materials, delivery, and format of the solutions, ultimately to integrate our solutions into the existing health system.

Implementation plan

As part of the implementation of the interventions in Phase 1, the study team conducted an orientation training for HEWs and HDAs (known as Hadha Gare locally) to equip them with the skills needed to identify vulnerable pregnant women using a vulnerability screening tool and to effectively implement the solutions. The prototype solutions were delivered by the trained HDAs with the help of HEWs for a duration of four months from February to May 2024.

Prior to implementation, HDAs identified vulnerable pregnant women within their catchment area. They then scheduled an appointment to facilitate family discussions about the prototype solutions. The audio programs and print materials were intended to be delivered throughout five home visits by HDAs. For women whose gestational age was high (8-9 months), we aimed to provide audio and print materials on institutional delivery only through three home visits.

In the first visit, HDAs provided the household with an audio device containing the pre-recorded ANC program and gave instructions on how to engage in couple communication. After two to three days, HDAs revisited the household to inquire about questions or concerns from the couple, collected the device, and provided a print material to reinforce the audio content. HDAs then conducted a third visit to gather feedback from the couple and provided the second audio device that contains a story of institutional delivery. At the fourth visit, HDAs collected the second device and provided the second print material to reinforce institutional delivery messages from the audio program. Finally, HDAs conducted the follow-up visit, encouraging the pregnant woman to utilize health services until she delivers and addressing remaining concerns among the couple. All of the home visits required husbands’ presence given that the solutions were designed to facilitate couple communication, which would in turn optimize male involvement in maternal health service potentially through shifting social and gender norms.

To ensure seamless implementation of the interventions, the study team conducted close monitoring of activities that included site review meetings with implementing partners at the primary health care unit (PHCU) level and on-site supportive supervision to identify gaps, provide technical support, and address any identified implementation challenges. Key implementation outcome indicators, such as the number of pregnant women reached with ANC and institutional delivery audio programs and print materials, were regularly collected through the KoboCollect mobile platform.

The Phase 2 implementation plan may follow a similar procedure. Detailed plans will be determined based on information about how the current implementation scheme was acceptable and feasible among health workers and implementing partners. Specifically, the Phase 1 qualitative interview data on implementation research indicators will inform Phase 2 strategies.

Data analysis plan

Quantitative data analysis . First, we will conduct a series of bivariate tests, including chi-square and t-tests, across treatment and control arms based on baseline and endline data. The purpose of conducting bivariate tests is to identify differences between the study arms for each potential confounding factors, given the possibility of quasi-experimental design not ensuring baseline matching between intervention and control arms. If any differences are observed, they will be controlled for in subsequent regression analyses. We will also identify types of missing data to determine whether missingness occurs in a systematic manner, which will help us determine the appropriate remedial measure to adopt.

Since this project will conduct various implementation activities at the PHCU level, the analysis will take account of clustering at the level. Further, because kebeles (akin to villages) are clustered within PHCUs, we will also consider clustering at the kebele level. Given the nested nature of this study, multi-level modeling (MLM) is considered appropriate because it provides both cluster-specific and population-averaged estimates simultaneously by defining both random effects and fixed effects, respectively. Prior studies that represented similar scenarios, however, have shown that estimated coefficients and standard errors are usually not biased, even with a sample size as low as 5 to 10 at Level 1 27 , 28 , and with many independent variables and interaction terms 29 .

Nevertheless, this study will use an MLM framework to assess the intervention effect based on a difference-in-difference analysis by computing differences between baseline and midline within each arm, and then test this difference between intervention and control arms. A fixed effects model will first be used to observe this effect of the intervention. Kebele and PHCU will then be included as random intercepts to account for clustering within these levels. The estimated variance for random effects will show the amount of variability in the outcome that is explained by the clusters (i.e., how much of institutional delivery uptake is attributed to a kebele). If the coefficient of the interaction term is significant with the significant model fit, we will observe significant program effects. The identical analyses will be conducted with 4+ANC visits as the outcome variable. Other covariates will be included by comparing goodness-of-fit statistics (e.g., AIC, BIC) to improve the model fit. Proper model specification and diagnostic tests will be conducted to enhance the robustness of the results. Phase 2 data analysis focus on comparing service utilization between intervention and control arms. Since we expect that study effectiveness will be stronger in Phase 2 with the implementation of enhanced solutions, we will additionally compare the study outcomes with baseline at Phase 1, controlling for potential key covariates including women’s education, parity, financial stability, geographical areas, and distance to health facilities.

Qualitative data analysis

Translated transcripts of the in-depth interviews will be uploaded to a qualitative software package that will be used to facilitate data management and organization. After reading over a few of the interview scripts for each type of stakeholder, two analytical frameworks (one for pregnant women and one for health providers) will be developed using deductive and inductive approaches. The frameworks will describe themes, any sub-themes, codes, and illustrative quotes that would supplement each identified theme/sub-theme. Along with the interview data, field notes from monitoring visits, scheduled 4 times throughout implementation, will additionally reviewed since they can provide rich context for the implementation process itself. Field notes would capture the trajectory of implementation as to how stakeholders engage with the process over time and whether specific implementation strategies would effectively address any challenges arising from the field.

Codes related to implementation research outcomes will be pre-defined, but iterative coding will allow new ideas to emerge. Other themes related to change in social factors are expected to emerge from data and will be identified through a process of open coding. Throughout the coding process, memo writing will be conducted simultaneously. Memo writing refers to systematic and continuous note-making during analysis 30 . While it has been primarily used in grounded theory, it is useful for a wide variety of qualitative methods because it provides researchers with an opportunity to critically reflect on how they view and treat data as well as any changes in decisions made 31 . Iterative coding and memo writing would enable constant comparisons of the data and other reflections over the course of the analysis. Two to three coders will analyze the data to achieve inter-coder reliability. The qualitative data management and analysis will adhere to the Consolidated criteria for reporting qualitative research (COREQ) guideline 32 .

Ethics approval

This study was approved on October 5, 2023 by the Ethiopian Public Health Institute (EPHI), a governmental public health institution located in Addis Ababa, Ethiopia (EPHI-IRB-510-2023). The first phase of the study was also reviewed and approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board (IRB00024473) on July 18, 2023, and the approval was extended for Phase 2 on July 16, 2024. In order to conduct HCD processes, we obtained ethical approval for public health practice by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board (IRB00023366) on January 4, 2023. Any changes to study protocol will be communicated with these regulatory entities for approval immediately.

Study dissemination

We will disseminate our work at conferences and peer-reviewed academic journals. We will also share our findings with program stakeholders, including government officials, health workers, and community workers.

Participant consent and confidentiality

All participants will be interviewed at their convenient location to ensure privacy. Informed consent will be obtained in Amharic or Afaan Oromo by local data collectors who are externally hired and trained by the Center for Communication Programs (CCP) Ethiopia study team. Data collectors will read the consent document to participants, who will then give verbal consent. Participants under the age of 19 are required to obtain the permission of one parent or legal guardian. Obtaining verbal consent is considered appropriate given the low level of literacy and education among study participants. The ethics committees from the team’s primary institutions approved administrating verbal consent. All data from participants will be de-identified by the study team and stored in secure, password-protected computers accessible only by the study team and its affiliates.

Discussions

The primary goal of the study is to determine whether, and to what extent, an intervention designed and implemented by adopting human-centered design principles can improve institutional delivery and 4+ ANC visits. While many interventions have been conducted to make an impact on these outcomes, two features of the current work are particularly noteworthy. First, the project adopts HCD principles throughout the life of the intervention, from the initial program design phase all the way to implementation and evaluation. A recent review indicates that most interventions identified as adopting HCD approaches do not do so in a holistic manner, limiting the HCD component predominantly to intervention design (Kang et al., under review). While adopting HCD principles throughout the project is often time consuming, requiring frequent reappraisals and adjustments, this project will provide some indications about the strengths (and limitations) of this approach to inform future projects.

The second innovative aspect of the current project is the extra effort we are expending on reaching women perceived to be most vulnerable. Given the high maternal mortality rate in Ethiopia, one can make the case that most women in the country are, in fact, vulnerable. Nevertheless, we make important distinctions between those who are vulnerable, writ large, and those whose individual, social, cultural, and environmental realities intersect in particularly devastating ways.

The rationale for this approach is our observation that, although maternal health outcomes are steadily improving in Ethiopia, there is a group of women who need support and approaches that are different from those being used to reach the larger majority, and we need interventions specifically tailored for this most-at-risk group. It is this belief that has resulted in a particular design of our study: we only include women whose vulnerability scores are moderate to high. It is likely that this approach requires extra resources, particularly if the most vulnerable women are geographically dispersed from each other and from the health services that they need to access. We suspect, however, that in the long run, these extra resources will turn out to be highly cost-effective, and we hope that dimensions will be designed to assess the cost-effectiveness and cost benefit of this approach.

The HCD solutions we are implementing in this project (e.g., delivering audio devices and supporting print materials) are, indeed, rather labor intensive and involve the adoption and distribution of new hardware. This intensity and the tailored approach, we anticipate, will be impactful among women who are exposed to the intervention. From a scale-up perspective, however, this may appear to be an approach that the government would be reluctant to adopt, given the required training and resources. We note that this approach is not meant to be scaled up for everyone; rather, the idea is that, for women whose life circumstances put them at the highest levels of risk, we need alternative approaches: ones that may be cost intensive but are, nevertheless, cost-effective. We hope to shed light on this tension between intervention intensity and its scale-up potential through the findings and recommendations that will emerge from this study.

Study status

Our study is currently at the post-intervention evaluation stage of Phase 1. We completed the baseline data collection and intervention implementation. The midline (post-intervention) assessment of Phase 1 is ongoing.

Data availability statement

No data are associated with this article.

Extended data

OSF: Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia. https://doi.org/10.17605/osf.io/cmnps 33 .

This project contains the following underlying data:

Appendix 1_Screening Tool. Pregnancy and vulnerability screening tool.

Appendix 2_Survey questionnaire. Baseline and midline survey guide.

Appendix 3_Qualitative guide Phase 1_Pregnant women. Qualitative questionnaire for pregnant women.

Appendix 4-6_Qualitative guide Phase 1_Providers. Qualitative questionnaire for health care providers.

Reporting guidelines

OSF: SPIRIT Checklist for “Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia.” https://doi.org/10.17605/osf.io/cmnps 33 .

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Acknowledgements

The authors would like to thank Nandita Kapadia-Kundu, Sanjanthi Velu, and Paula Stauffer for contributing to study planning and Biruk Melaku Ayalew and Tewabech Tesfalegn Sheno for facilitating the HCD process and all workshop attendees in Phase 1.

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• Open access
• Published: 26 August 2024

Causal associations of obstructive sleep apnea with Chronic Respiratory Diseases: a Mendelian Randomization study

• Ping-Yang Hong 1 , 2 , 5   na1 ,
• Dong Liu 3   na1 ,
• Ang Liu 4 ,
• Xiao-Bin Zhang 2 , 6 &
• Yi-Ming Zeng 1  

BMC Pulmonary Medicine volume  24 , Article number:  409 ( 2024 ) Cite this article

Metrics details

This study aimed to elucidate the causal relationship between Obstructive Sleep Apnea (OSA) and Chronic Respiratory Diseases (CRDs), employing Mendelian Randomization (MR) to overcome limitations inherent in observational studies.

Utilizing a two-sample MR approach, this study analyzed genetic variants as instrumental variables to investigate the causal link between OSA and various CRDs, including chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis, and idiopathic pulmonary fibrosis (IPF). Data were sourced from the FinnGen Consortium (OSA, n  = 375,657) and UK Biobank, focusing on genome-wide associations between single-nucleotide polymorphisms (SNPs) and the diseases. Instrumental variables were selected based on strict criteria, and analyses included a random-effects inverse-variance weighted method supplemented by several sensitivity analyses.

The study suggests a protective effect of OSA against COPD (OR = 0.819, 95% CI 0.722–0.929, P-value = 0.002), which becomes non-significant after adjusting for BMI, indicating a potential mediating role of BMI in the OSA-COPD nexus. No significant causal links were found between OSA and other CRDs (asthma, IPF, bronchiectasis) or between COPD, asthma, and OSA.

Conclusions

Our findings reveal a BMI-mediated protective effect of OSA on COPD, with no causal connections identified between OSA and other CRDs. These results emphasize the complex relationship between OSA, BMI, and COPD, guiding future clinical strategies and research directions, particularly in light of the study’s genetic analysis limitations.

Peer Review reports

Introduction

According to conservative estimates, the prevalence of obstructive sleep apnea(OSA) is 3% for women, 10% for men in the 30- to 49-year-old age range, and 9% for women and 17% for men in the 50- to 70-year-old age range [ 1 ]. The characteristic features of OSA include the episodic collapse of the upper airway, which depends on the sleep state [ 2 ]. This leads to periodic decreases or cessations in breathing, which can cause hypoxia, hypercapnia, or arousal from sleep [ 3 , 4 ]. Nocturnal hypoxemia is often present in OSA and especially in overlap cases with COPD because the result of hypoxia is the development or worsening of cerebro-cardio-vascular, metabolic and other diseases, which cause a high risk of death [ 5 , 6 ]. As noted by Tondo, et al. [ 6 ], OSA is closely associated with these health risks, underlining the need for effective management and intervention strategies.

Chronic respiratory diseases (CRDs) continue to be the main cause of death and disability worldwide [ 7 , 8 ]. There were 544,9 million chronic respiratory disease sufferers globally in 2017, a 39.8% increase from 1990 [ 7 ]. Some of the most common chronic respiratory diseases are chronic obstructive pulmonary disease (COPD) and asthma [ 9 ]. The concurrent prevalence of CRDs, such as COPD [10 11], asthma [ 12 ], bronchiectasis [ 13 ], and idiopathic pulmonary fibrosis (IPF) [ 14 , 15 ] has been repeatedly highlighted by modern observational research, highlighting a significant clinical overlap with OSA.

The prevalence of OSA is estimated to be 10–30% in patients with COPD [ 16 ] and 20–60% in those with asthma [ 17 , 18 ]. OSA exacerbates chronic respiratory diseases such as COPD, asthma, interstitial lung disease, and pulmonary hypertension [ 19 ]. OSA with CRDs not only deteriorates the progression of these diseases but also adversely affects the quality of life of the affected individuals.

These ongoing findings point to a significant convergence in the clinical characteristics of these illnesses. Nevertheless, a thorough definition of the causal link between OSA and CRDs is still pending.

Mendelian randomization (MR), an innovative statistical approach, offers a method to appraise the causal links between OSA and CRDs, utilizing genetic variants as instrumental variables [ 20 ]. MR analysis can eliminate potential unmeasured confounders and reverse causation, a significant limitation of evidence from observational studies because the genetic variants are assigned randomly at conception [ 21 ]. In this work, we used MR techniques to assess the causal relationship between OSA and CRDs.

Study design and data sources

This study encompasses a comprehensive review of supporting information within the article. Employing a two-sample MR approach, we investigated the causal relationship between OSA and CRDs (Fig.  1 ). In our MR framework, genetic variations serve as instrumental variables to ascertain if exposure significantly influences disease development. This method offers robust causal inferences, mitigating the impact of unmeasured confounders. Our MR design adhered to three critical criteria for credible causal estimations: (1) Instrumental variables must exhibit a substantial association with the exposure; (2) The instrumental variables should be independent of known confounders. The exposure is the sole pathway through which the instrumental variables influence the outcomes; (3) Genome-wide association studies (GWAS) have demonstrated associations between single-nucleotide polymorphisms (SNPs) and exposure. The data utilized were derived from publicly available GWAS summary statistics, thus obviating the need for additional ethical approval or informed consent. GWAS data for OSA were obtained from the FinnGen Consortium (G6_SLEEPAPNO _INCLAVO) (gs://finngen-public-data-r9/summary_stats/finngen_R9_G6_SLEEPAPNO_INCLAVO.gz), comprising 41,704 cases and 335,573 controls. OSA diagnosis was according to the International Classification of Diseases, Tenth Revision (ICD-10) and Ninth Revision (ICD-9) codes (ICD-10: G47.3, ICD-9: 3472 A), which was based on subjective symptoms, clinical examination, and sleep registration applying AHI ≥ 5/h or respiratory event index ≥ 5/h. The CRDs outcomes were COPD, asthma, bronchiectasis, IPF, and pulmonary hypertension. Genetic instruments for COPD (25,054 cases and 392,709 controls), asthma (2,365 cases and 453,983 controls), bronchiectasis (583 cases and 455,765 controls), IPF (1,369 cases and 435,866 controls) were obtained from the UK Biobank ( https://gwas.mrcieu.ac.uk/ , COPD GWAS ID: ebi-a-GCST90042687, asthma GWAS ID: ebi-a-GCST90044072, bronchiectasis GWAS ID: ebi-a-GCST90044075, IPF GWAS ID: ebi-a-GCST90399723) (Table  1 ). COPD was defined using post-bronchodilator spirometry according to modified GOLD criteria in both studies.

Mendelian randomization model of OSA and CRDs. Abbreviation OSA, obstructive sleep apnea; CRDs: chronic respiratory diseases

Instrumental variable selection

In this study, SNPs were meticulously selected for each exposure factor in accordance with the principal assumptions underpinning MR. Initially, SNPs achieving genome-wide significance ( p  < 5 × 10^−8) were considered for inclusion. Subsequently, to identify independent instrumental variables (IVs), we selected variants demonstrating the lowest p-values, ensuring minimal linkage disequilibrium (LD) as evidenced by an r ^2 threshold greater than 0.1, based on the European 1000 Genome reference panel. Finally, the robustness of these instrumental variables was quantified using F -statistics [ 22 ], with an F -statistic value exceeding ten generally deemed suitable for MR analysis.

Statistical analysis

In this investigation, for binary exposures, causal estimates were articulated as odds ratios (ORs) with 95% confidence intervals (CIs) per logarithmic odds increment in the genetically predisposed risk of the exposures. Regarding continuous exposures, the causal estimate was denoted as an OR accompanied by a 95% CI for each standard deviation (SD) increase in exposure. MR analysis employed the primary analytic approach of the random-effects inverse-variance weighted (IVW) method. This was chosen to estimate the potential bidirectional causal relationships between OSA and CRDs, offering robust causal estimations in scenarios devoid of directional pleiotropy. Complementary analyses incorporated methods such as the weighted median, simple mode, weighted mode, and MR-Egger. Directional horizontal pleiotropy was assessed using the MR-Egger intercept test. Heterogeneity in MR-Egger regression and the IVW method was evaluated through Cochran’s Q statistics and funnel plot analyses [ 23 ]. Additionally, sensitivity was examined via leave-one-out analysis. Post hoc power assessments for MR leveraged online resources ( https://sb452.shinyapps.io/power/ ) [ 24 ]. All statistical procedures were executed using the TwoSampleMR packages within R (version 4.1.2, www.r-project.org/ ). All p-values were two-tailed. A Bonferroni-adjusted p-value threshold of < 0.004 (0.05/12) was set for determining statistical significance in MR analyses. In contrast, p-values < 0.10 were deemed significant for MR-Egger tests and heterogeneity assessments.

In the initial phase of our analysis, we rigorously selected SNPs that demonstrated a robust association with the exposure, applying stringent criteria ( p  < 5 × 10^−8, F-value > 10) and ensuring independence (r² < 0.001 within a 10,000 kb physical window). This process yielded 22 SNPs from the FinnGen Consortium (G6_SLEEPAPNO_INCLAVO) designated as IVs after excluding SNPs with LD (r 2  > 0.001). No proxy SNP was missing for other CRDs outcomes. Detailed information for each SNP for OSA used in the current study can be found in the supplementary file (Supplementary material, Table S1 ).

The causal effect of OSA on CRDs

The results of the MR analyses are shown in Fig.  2 ; Table  2 , and the scatter plots and forest plots are presented in Supplementary Figure S1 and Figure S2 , respectively. In the univariable IVW analysis, genetically predicted OSA is negatively associated with COPD [IVW: odds ratio (OR) = 0.819, 95% CI 0.722–0.929, P-value = 0.002]. The Cochran’s Q value suggested a moderate level of heterogeneity (Q = 37.207, p  < 0.05) obtained from individual variants. Furthermore, the leave-one-out analysis suggested that the observed association was not significantly changed after removing any single variant (Supplementary Figure S3). In order to exclude the influence of confounding factors, we used multivariate Mendelian randomization analysis (MVMR). The MVMR estimates remained unchanged after an BMI adjustment accounting for multiple testing (P-value = 0.434). No genetic association of OSA with asthma, IPF, and bronchiectasis was found with all P values > 0.05.

The causal effect of OSA on chronic respiratory diseases. Abbreviation OSA, obstructive sleep apnea; SNP: single-nucleotide polymorphisms; COPD: chronic obstructive pulmonary disease; MVMR: multivariate Mendelian randomization analysis; BMI: body mass index; IPF: idiopathic pulmonary fibrosis

The causal effect of CRDs on OSA

As shown in Supplementary Table S2 , the scatter plots (Supplementary Figure S5), and forest plots (Supplementary Figure S6), the MR results showed COPD and asthma were not causally related to OSA, with ORs close to 1 ( p  > 0.05). Egger’s test showed that no potential horizontal pleiotropy exists. Cochran’s Q test indicated no heterogeneities. The leave-one-out analysis also revealed the stability of the results (Supplementary Figure S7). Insufficient SNPs were present in IPF and bronchiectasis to facilitate a conclusive Mendelian analysis.

In this investigation, we present what we believe to be the inaugural bidirectional MR study elucidating the impact of OSA on a spectrum of CRDs. Our analysis discerned a diminished and statistically non-significant association between OSA and COPD upon adjustment for BMI. Importantly, no significant causal linkage was observed between OSA and other respiratory conditions such as asthma, IPF, and bronchiectasis.

Furthermore, our data suggest that OSA may act as a protective factor against COPD, a relationship that loses significance upon BMI adjustment. This finding highlights the complex interplay between BMI and respiratory diseases, suggesting that BMI may mediate the relationship between OSA and COPD. Similarly, Tondo, et al. [ 25 ] found BMI significantly modulates the impact of OSA on various comorbidities, providing an observational perspective that complements our Mendelian randomization approach. A body of extant observational studies buttresses this hypothesis. Shin, et al. [ 26 ] reported heightened exacerbation risks in COPD patients with a BMI below 25 kg/m², in contrast to those with higher BMI values. Complementing this, a substantial Japanese cohort study demonstrated an inverse relationship between BMI and COPD mortality risk, evidenced by a hazard ratio of 0.48 per standard deviation increase in BMI. This study also highlighted the inverse correlation between weight gain post-age 20 and COPD mortality risk, underscoring the prognostic significance of BMI and weight trajectories in COPD [ 27 ]. Moreover, the causal relationship between OSA and BMI [ 28 ] emerges as a positive prognostic factor in COPD patients within our study’s context. Obesity significantly increases the risk and severity of OSA due to mechanical, physiological, and inflammatory factors that compromise airway patency and respiratory function [ 29 ]. Nevertheless, a higher BMI can indicate better nutritional status, which is crucial for patients with advanced COPD who often experience weight loss and muscle wasting [ 30 ]. These reserves provide essential energy to support breathing and other physical activities, potentially slowing the progression of disability [ 31 ]. The intricate interplay between OSA, BMI, and COPD warrants further investigative efforts to elucidate the underlying mechanisms.

This investigation discerned no causal link between OSA and several CRDs, namely asthma, IPF, and bronchiectasis. This absence of causal association diverges from the conclusions of previous observational studies, potentially attributable to confounding variables inherent in such study designs. Moreover, our findings did not identify a causal relationship in the reciprocal analysis concerning COPD, asthma, and OSA. However, it is crucial to note that the validity of these results may be constrained by the limited number of SNPs utilized in the study. The limited SNP count potentially undermines the robustness of these findings, indicating the necessity for further research with a more extensive genetic dataset to corroborate or challenge these preliminary observations.

A major strength of this MR study lies in its ability to circumvent reverse causality and minimize residual confounding. Additionally, the study boasts significant investigatory power and accuracy in estimating effect magnitudes by employing the most comprehensive dataset for exposures and the most extensive summary-level data for OSA risk and CRDs. Nonetheless, there are limitations. Firstly, the functions of the genetic instruments and their impact on risk factors are not completely understood. Secondly, potential pleiotropic effects, possibly obscured by a limited number of genetic instruments or small sample sizes, remain a concern, although the MR-Egger intercept indicates minimal horizontal pleiotropy. Thirdly, our study did not differentiate the impacts of various BMI ranges on both OSA and COPD, a limitation we aim to address in future research.

In summary, our study elucidates a potentially protective influence of OSA on COPD, an effect that appears to be mediated through BMI. These findings underscore clinicians’ need to consider the interplay among OSA, BMI, and COPD in clinical practice. Such awareness could inform more nuanced diagnostic and therapeutic approaches, enhancing patient outcomes in managing these conditions.

Data availability

The datasets generated and/or analysed during the current study are available in the FinnGen and UK Biobank ( https://r9.finngen.fi/ and https://gwas.mrcieu.ac.uk/ ).

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This work was supported by the National Natural Science Foundation of China (82170103), Young people training project from Fujian Province Health Bureau (2020GGB057), Fujian Provincial Health Technology Project (2023QNB008), Xiamen Medical and Health Guidance Project (3502Z20214ZD1043, 3502Z20224ZD1058).

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Ping-Yang Hong and Dong Liu are co-first authors

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Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine of Fujian Province, The Second Affiliated Hospital of Fujian Medical University, No.950, Donghai Street, Fengze District, Quanzhou, Fujian Province, China

Ping-Yang Hong & Yi-Ming Zeng

Department of Pulmonary and Critical Care Medicine, School of Medicine, Zhongshan Hospital of Xiamen University, Xiamen University, Xiamen, Fujian, China

Ping-Yang Hong & Xiao-Bin Zhang

Department of Civil Engineering and Smart Cities, Shantou University, Shantou, Guangdong, China

Department of Anesthesiology, Heze Municipal Hospital, Heze, Shandong, China

Department of Cardiology, School of Medicine, Xiamen Cardiovascular Hospital of Xiamen University, Xiamen University, Xiamen, Fujian, China

Ping-Yang Hong & Xin Su

The School of Clinical Medicine, Fujian Medical University, No.201, Hubin Nan Road, Siming District, Xiamen, Fujian Province, China

Xiao-Bin Zhang

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Conception and design: P-Y Hong, D Liu and A Liu. Collection and assembly of data: X Su and X-B Zhang. Data analysis and interpretation: P-Y Hong and Y-M Zeng. Manuscript writing: All authors. Final approval of manuscript: All authors.

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Hong, PY., Liu, D., Liu, A. et al. Causal associations of obstructive sleep apnea with Chronic Respiratory Diseases: a Mendelian Randomization study. BMC Pulm Med 24 , 409 (2024). https://doi.org/10.1186/s12890-024-03228-x

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Unveiling missed nursing care: a comprehensive examination of neglected responsibilities and practice environment challenges

• Somayeh Babaei 1 ,
• Kourosh Amini   ORCID: orcid.org/0000-0003-2363-894X 2 &
• Farhad Ramezani-Badr 3  

BMC Health Services Research volume  24 , Article number:  977 ( 2024 ) Cite this article

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Metrics details

The global variable of missed nursing care and practice environment are widely recognized as two crucial contextual factors that significantly impact the quality of nursing care. This study assessed the current status of missed nursing care and the characteristics of the nursing practice environment in Iran. Additionally, this study aimed to explore the relationship between these two variables.

We conducted an across-sectional study from May 2021 to January 2022 in which we investigated 255 nurses. We utilized the Missed Nursing Care Survey, the Nursing Work Index-Practice Environment Scale, and a demographic questionnaire to gather the necessary information. We used the Shapiro‒Wilk test, Pearson correlation coefficient test, and multiple linear regression test in SPSS version 20 for the data analyses.

According to the present study, 41% of nurses regularly or often overlooked certain aspects of care, resulting in an average score of 32.34 ± 7.43 for missed nursing care. It is worth noting that attending patient care conferences, providing patient bathing and skin care, and assisting with toileting needs were all significant factors contributing to the score. The overall practice environment was unfavorable, with a mean score of 2.25 ± 0.51. Interestingly, ‘nursing foundations for quality of care’ was identified as the sole predictor of missed nursing care, with a β value of -0.22 and a p -value of 0.036.

Conclusions

This study identified attending patient care interdisciplinary team meetings and delivering basic care promptly as the most prevalent instances of missed nursing care. Unfortunately, the surveyed hospitals exhibited an undesirable practice environment, which correlated with a higher incidence of missed nursing care. These findings highlight the crucial impact of nurses’ practice environment on care delivery. Addressing the challenges in the practice environment is essential for reducing instances of missed care, improving patient outcomes, and enhancing overall healthcare quality.

Peer Review reports

Introduction

Missed Nursing Care (MNC) is the failure to provide any necessary aspect of patient care, partially or entirely, or delay in delivering it [ 1 ]. MNCs can have severe side effects on patients, including safety threats [ 2 ] and even mortality [ 3 ]. It also significantly decreases the quality of nursing care [ 4 ]. MNC can also have adverse and destructive effects on nurses, including decreased job satisfaction, increased absenteeism, and the intention to leave their jobs [ 5 ]. As a result, MNCs have become a key focus of nursing researchers in recent years and are widely recognized as a significant global problem [ 6 ].

A literature review revealed that MNCs are multidimensional and vary significantly in frequency and elements across different research communities [ 7 ]. In Iran, information regarding MNCs is limited. According to our search, only one reliable study [ 8 ] has been conducted on this topic in the last five years. Chegini et al. conducted a study that showed that the percentage of participants who missed care was 72.1%. The most common tasks of missed nursing care included patient discharge planning and teaching, emotional support for patients and their families, interdisciplinary care conferences, and patient education regarding their illness, tests, and diagnostic procedures. Although the study by Chegini et al. has provided valuable information, the generalizability of its results is limited due to its small sample size. The study included nurses from only medical-surgical wards and used the census sampling method.

MNC is influenced by various individual and organizational factors [ 9 ]. In a systematic review, Chiappinotto et al. identified significant factors contributing to MNC, such as low nurse-to-patient ratios, high workloads, and poor work environments. Moreover, stress, job dissatisfaction, and inadequate education among nurses were recognized as crucial elements. Furthermore, patient clinical instability was found to further worsen MNC [ 10 ]. However, some researchers argue that organizational and environmental factors are more influential in causing MNC than individual factors [ 11 ].

Another influential organizational variable on nursing performance is the practice environment (PE) [ 12 ]. PE in nursing is inclusive of material and human resources, a cooperative environment, and other elements related to the environment that directly or indirectly affect how care is provided [ 13 ]. PE is involved in nurses’ burnout [ 14 ], job satisfaction, stay in nursing [ 15 ], and overall quality of nursing care [ 16 ]. Like in MNCs, evidence suggests that PE varies across different hospitals and wards within a hospital [ 17 ]. For instance, a study conducted by Choi & Boyle in the U.S. demonstrated that pediatric wards had more favorable PEs than did medical-surgical wards. However, previous studies have shown that MNCs differ across poor, moderate, and suitable PEs. Weak PE has been found to increase MNCs [ 18 ], while optimal PE reduces MNCs [ 17 ]. Due to the global significance of MNCs and PEs for quality of care and the variability of these two variables due to different sociocultural factors, it is essential to understand the weaknesses of MNCs and PEs in every community thoroughly. Therefore, this study aimed to determine the status of MNCs, the characteristics of PEs, and the relationships between these two variables among nurses working in two teaching hospitals.

The present study was cross-sectional from May 30, 2021, to January 19, 2022. The study was conducted according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The study included nurses employed in the medical-surgical, emergency, and intensive care units of two major teaching hospitals in Zanjan Province. This province is situated in the northwestern region of Iran and has a population of approximately 1,016,000 people. To be eligible for participation in the study, the nurses needed to meet the following specific inclusion criteria:

A minimum of three months of work experience in the desired ward.

Holding a bachelor’s degree or higher.

Consent to participate in the study was obtained.

We utilized Formula 1 for a finite population to determine the sample size. The values used in this formula were N (total population) = 553, power (the probability of correctly rejecting the null hypothesis) = 0.80, standard deviation (SD) = 13.97, d (margin of error or precision) = 1.2, and Z (standardized value for the corresponding level of confidence) = 1.96. The formula indicated that a minimum sample size of 246 was required based on these variables. During the research, we found that a recent study comparable to our work was conducted by Park et al. [ 18 ]. For our research, we utilized the standard deviation of the variables in Formula 1. Their study recorded the mean and standard deviation of the MNC and PE as 84.06 ± 13.79 and 2.92 ± 0.25, respectively. We included the higher standard deviation (related to MNCs) to ensure a larger sample size. We prepared 270 questionnaires and distributed them among the selected nurses. We also considered the possibility of spoiled questionnaires and distributed extra questionnaires accordingly. Fifteen questionnaires were excluded from the study due to incomplete data, leaving a total of 255 questionnaires that were used for data analysis out of the 270 that were distributed.

We utilized a systematic random method to select the nurses for the study. In the first step, a list of nurses working in the desired wards was taken, and the sampling frame was prepared. In the second step, each nurse was assigned a number from a table of random numbers. This process generated a new sampling frame. In the third step, we calculated the distance between the study samples, denoted as ‘K’, using the formula K = N/n.’ We computed K by dividing the total population (N) of 553 by the sample size (n) of 270, approximately 2. To select the participants, we utilized a systematic random method. A new sampling frame was generated in the first step, as described earlier. The first nurse was selected randomly from this new sampling frame, and the subsequent samples were taken at a distance of two people from the previous nurse.

To collect the data, we used three different questionnaires: (a) a demographic profile form, (b) the Missed Nursing Care (MISSCARE) Survey, and (c) the Nursing Work Index-Practice Environment Scale (NWI-PES). The demographic profile included various variables, including sex, age, marital status, educational degree, work experience, position, shift work, employment type, and ward type.

In this study, we utilized the MISSCARE survey (MISSED) to assess MNC. We chose the MISSED based on its extensive utilization and strong psychometric properties, as evidenced in the literature. As noted by Chiappinotto et al. [ 10 ], 34 out of the 58 studies reviewed utilized a version of the MISSCARE survey, highlighting its reliability and validity in assessing MNC. The MISSCARE Survey consists of two parts: Part ‘A’ and Part ‘B’. Part ‘A’ included the most missed care components, while Part ‘B’ included the reasons for missing nursing care. We utilized part ‘A’ of the questionnaire, which constituted 24 items of the MISSCARE Survey. Each of the 24 items comprises five answer options: 1) rarely or never missed, 2) occasionally missed, 3) frequently missed, 4) always missed, and 5) nonapplicable. Kalisch & Williams included the option of ‘nonapplicable’ to account for nurses who operate in situations where certain care activities may not be performed [ 19 ]. The total score range of this survey is 24–96, where higher scores indicate a greater probability of missed care. In line with the findings of a previous study [ 17 ], we considered the combination of “frequently missed” and “always missed” options as missed care to demonstrate the frequency of missed nursing care. The MISSCARE Survey has undergone psychometric analysis, and its applicability has been approved for the nursing community in Iran [ 20 ]. The internal consistency of the tool was measured based on Cronbach’s alpha coefficient (α = 0.88) in this study.

The psychometric analysis of the NWI-PES has been conducted, and its usage has been approved [ 21 ]. Developed by Lake in 2002 and authorized by the National Quality Forum (NQF), this scale comprises thirty-one items and operates on a four-point Likert scale, with scores ranging from four to one. The response options were strongly agree = 4, somewhat agree = 3, somewhat disagree = 2, and strongly disagree = 1. According to [ 22 ], the possible score range of the whole scale and its subscales is one to four. The NWI-PES comprises five subscales:

The nurses’ participation in hospital affairs was evaluated with nine items.

‘Staffing and resource adequacy’, which includes four items.

The three items used were “Collegial nurse‒physician relations”.

‘Nursing foundations for quality of care’ with ten items.

The five items asked about nurses’ ability, leadership, and support.

A scale midpoint greater than 2.5 is considered an acceptable PE [ 22 ]. The NWI-PES demonstrated high internal consistency, with a Cronbach’s alpha of 0.93. The Cronbach’s alpha for each of the subscales of the NWI-PES was computed. The results were as follows: ‘nurse participation in hospital affairs,’ α = 0.88; ‘nursing foundations for quality-of-care,’ α = 0.72;‘staffing and resource adequacy,’ α = 0.87; ‘collegial nurse‒physician relations,’ α = 0.90; and ‘nurse manager ability, leadership, and support of nurses,’ α = 0.84.

We computed the means and standard deviations of the MNC and PE scores and utilized the Shapiro‒Wilk test to determine the normality of the data distribution. The results revealed that the data followed a normal distribution. We employed the Pearson correlation coefficient to determine the correlation between PEs and MNCs. Furthermore, we conducted a multiple linear regression test to examine whether changes in the MNC score, as the dependent variable, were associated with changes in the PE subscale scores. Before conducting the multiple linear regression analysis, we confirmed that the assumptions were met and evaluated. We confirmed the assumption of independent errors by using the Durbin–Watson test. Homoscedasticity and linearity assumptions were assessed through P-P plots. The hypothesis of multicollinearity was examined by determining the variance inflation factor (VIF) and tolerance [ 23 ]. The VIF ranged from 1.006 (TOL = 0.99) for ‘collegial nurse‒physician relations’ to 1.04 (TOL = 0.96) for ‘nursing foundations for quality-of-care.’ Independent t tests and ANOVA were used to evaluate the associations between demographic variables and MNCs. The statistical analysis of the data was conducted using SPSS software version 24, and a P  value lower than 0.05 was used to indicate statistical significance.

Participants’ characteristics

The majority of the participants were females (84.3%), were married (68.2%), and were employed on a 5-year contract (46.7%). The majority of the participants were females (84.3%), were married (68.2%), and were employed on a 5-year contract (46.7%).

In addition, almost all of the participants (95.7%) had a Bachelor of Science in Nursing (BSN) degree, and a significant proportion (45.8%) worked in medical-surgical wards. Most of the respondents (91.4%) were staff nurses, and 89.8% of them worked in rotational shift work. The.

The participants’ average age and work experience were 33.94 ± 7.40 and 9.25 ± 7.14, respectively (Table  1 ).

Missed nursing care

The overall mean score for MNCs, with a score ranging from 24 to 96, was 32.34 ± 7.43. Of the total nurses, 41% reported that they always or frequently missed at least one aspect of nursing care. Based on the findings, the items with the highest mean score in descending order were attending an interdisciplinary patient care conference, patient bathing or skin care, assisting with toileting needs within 5 min of request, mouth care, and feeding the patient when the food was still warm (Table  2 ).

The mean MNC score was significantly greater for male nurses than for female nurses (X̄1 = 36.25, X̄2 = 31.56; t = -3.738, p  < 0.001). Other demographic and occupational variables of the nurses, such as age, marital status, degree, work experience, position, rotational shift work, type of employment, and working place, had no significant association with MNCs ( p  > 0.05).

Practice environment characteristics

The overall mean score for PE was 2.25 ± 0.51. Among the different subscales of the PE scale, the highest mean score was observed for ‘collegial nurse‒physician relations’ (M = 2.45, SD = 0.72). Furthermore, the mean scores for “nursing foundations for quality of care”, “nurse manager ability, leadership, and support of nurses”, and “nurse participation in hospital affairs” were 2.43 ± 0.58, 2.23 ± 0.65, and 2.16 ± 0.58, respectively. The lowest mean score was observed for ‘staffing and resource adequacy’ (M = 1.81, SD = 0.64).

Correlations between practice environment characteristics and missed care

The study’s results indicate a significant and negative correlation between the mean score of PEs and the overall mean score of MNCs ( r = -0.18, p  = 0.002). There was a strong link between the overall mean score of MNCs and two of the five NWI-PES subscales: “nursing foundations for quality of care” ( r = -0.21, p  < 0.001) and “nurse manager ability, leadership, and support of nurses” ( r = -0.16, p  = 0.006).

Predicting missed nursing care based on practice environment subscales

According to Table  3 , linear regression analysis showed that only “nursing foundations for quality of care” (β = -0.22, p  = 0.036) of the five NWI-PES subscales could predict MNC.

The main objective of this study was to determine the status of MNCs, the characteristics of PEs, and the relationships between these two variables among Iranian nurses working in two teaching hospitals. The findings showed that 41% of nurses reported frequently or always missing at least one aspect of nursing care. A systematic review also reported that 55–98% of nurses missed at least one course of nursing care [ 24 ]. However, the overall mean score of MNCs in our study was 32.3. A literature review revealed that our study’s mean MNC score was lower than that reported in the United States, Turkey, and Australia, except for Iceland [ 25 ]. By comparing our study results with those from other countries [ 26 ], it can be concluded that low MNCs were reported in our study. Like in many previous studies, in this study, we used the self-reporting method. The reason for the lower mean score of MNCs in our study compared to that in other studies might be due to two biases: “acquiescence response style” (tendency to respond positively) and “social desirability bias” (tendency to present oneself socially to be acceptable, but it does not fully reflect the reality of the individual). Due to the two biases mentioned earlier, the ‘truth-telling’ in our survey might have been compromised. This is because we used the self-reporting method to collect data, and the nature of MNCs is one of the essential aspects of ethics in nursing. The study findings indicated that patients who participated in interdisciplinary conferences had the highest mean score. However, not attending training classes can decrease knowledge and make nursing care less updated, ultimately reducing the quality of care provided to patients [ 27 ]. This finding is consistent with that of another study conducted in Brazil [ 7 ]. Based on our field experiences and observations, several factors, including the following, seem to play a significant role in missing nursing care:

Time limitation due to a nursing shortage.

Inappropriate timing of training classes or conferences and conflicts in daily schedules.

There is a lack of support and encouragement from managers, especially hospital managers.

Inappropriate and nonequipped venues for classes.

Improper teaching methods and giving lectures instead of using new teaching methods.

There is a lack of proper alert reminders for nurses regarding the date, time, and place of meetings.

Our study revealed that the lowest scores for missed care were related to items such as ‘bedside glucose monitoring as ordered”, ‘peripheral IV/central line site care and assessments according to hospital policy’, and ‘vital signs assessments as ordered.’ The lower scores associated with this care could be attributed to the use of an accurate system for recording patients in patient files and additional unique records above patients’ beds in the current research environment, which helps staff remember and check this care more often. However, these care tasks are crucial parts of a patient’s vital nursing care and should be performed during each work shift to monitor the patient’s hemodynamic status. This information about each patient was provided to the assigned nurse during the shift handover. A lack of ‘blood sugar control’ was also indicated in the studies of Smith et al. [ 17 ] in the U.S.

Our study revealed a low PE score among the participating nurses. Given that nurses have greater responsibility for caring and have essential tasks such as performing technical procedures, making decisions, and leading patient care, such tasks are affected by poor practices. Consequently, patient and family satisfaction decreases, and adverse patient outcomes, such as mortality and infection, may increase. Azevedo Filho et al. also demonstrated a poor nursing practice environment in Brazil [ 13 ], consistent with our study results. In another study [ 17 ], the average PE score was significantly greater than that in our study and that of Azevedo Filho et al. [ 13 ]. The high score in the Smith et al. research population could be because the surveyed hospitals were magnet hospitals. In magnet hospitals, there is more focus on creating a healthier and more desirable work environment. Our study revealed a significant inverse correlation between PE characteristics and MNCs. In other words, missed nursing care increases significantly in patients with unfavorable PEs. However, this relationship was not strong. Several researchers have emphasized the importance of providing qualified nursing services and improving the nursing work environment [ 17 ].

Among the different dimensions of PE, “nursing foundations for quality of care” and “nurse manager ability, leadership, and support of nurses” had significant relationships with MNCs. These findings suggest that targeted interventions aimed at improving each dimension of PE can help reduce the incidence of MNCs. Additionally, the ability of nursing managers and leaders should be accompanied by reduced missed care because nursing managers are responsible for managing the working conditions of nurses, determining their duties, coordinating existing resources, and developing basic nursing settings for the quality of patient care [ 28 ].

Our study on the relationship between nurses’ occupational and demographic variables and MNCs contradicts the findings of Blackman et al. [ 29 ], who indicated that men’s mean score for missed care is significantly greater than women’s. A study conducted in Iran also showed that female nurses’ quality of nursing care is greater than that of male nurses [ 30 ]. Women tend to care for patients more carefully, and less missed care is provided by women. Except for gender, the results of our study suggested no correlation between MNCs and other occupational and demographic variables of nurses.

Limitations

The study offers insights into missed nursing care and its relationship with the practice environment. However, several limitations should be considered. The study’s cross-sectional design creates potential biases, which may limit our ability to establish causation. Additionally, the reliance on self-reports introduces the likelihood of response bias. Furthermore, the study focused on specific hospitals in Zanjan Province, which may restrict the generalizability of the findings to a broader context. Confounding factors, which are inherent to observational studies, might influence the observed relationships. Despite the abovementioned limitations, the study provides valuable contributions to comprehending the complex dynamics between the practice environment and missed nursing care.

According to our study, nurses consistently neglect a significant portion of nursing care, with patient-related team meetings and training sessions being the most overlooked. This is a noteworthy finding. The findings highlight a possible lack of awareness or inadequacy in planning critical sessions, which demands increased attention. Notably, basic nursing care is the second most commonly overlooked aspect of care. The unfavorable practice environment identified in the hospitals under study highlights the urgent need for improvement by planners and senior managers. Notably, our findings demonstrated a significant statistical relationship between the practice environment and unattended nursing care. This indicates that improving the practice environment could help reduce the number of missed care cases. Notably, managerial competencies, particularly leadership, are vital in preventing overlooked nursing care. These results provide essential insights for the field, highlighting the importance of targeted improvements in practice environments to improve patient care outcomes. Our research provides a foundation for future research and interventions to optimize nursing care delivery.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Analysis of Variance

Missed Nursing Care

National Quality Forum

Practice Environment

Variance Inflation Factor

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Acknowledgements

We want to thank all the nurses who participated in this study. Their invaluable contributions were crucial in making this research possible. We would also like to thank the hospitals in Zanjan Province for their cooperation and support during the data collection. Furthermore, we would like to acknowledge the Zanjan University of Medical Sciences’ Biomedical Research Ethics Committee for approving and overseeing the ethical aspects of this research. We are grateful for their collaboration and commitment to advancing healthcare research, which made this study possible.

This work was supported by the Research and Technology Deputy of Zanjan University of Medical Sciences, Zanjan, Iran (grant number: A-11-86-17).

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Study design: KA. Data collection: SB. Data analysis: KA, FR. Study supervision: KA. Manuscript writing: KA, SB, FR. Critical revisions for important intellectual content: KA, FR.

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The research proposal with the code IR.ZUMS.REC.1399.053 was approved by the Zanjan University of Medical Sciences’ Biomedical Research Ethics Committee (ZUMS.REC). We obtained written informed consent from all participants and preserved the confidential identity of each participant throughout the study. Before using the two MISSCARE Survey and Practice Environment Scale questionnaires, permission was obtained from the developers of the participants (Professor Kalisch and Professor Lake, respectively) through email.

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Babaei, S., Amini, K. & Ramezani-Badr, F. Unveiling missed nursing care: a comprehensive examination of neglected responsibilities and practice environment challenges. BMC Health Serv Res 24 , 977 (2024). https://doi.org/10.1186/s12913-024-11386-1

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The moderating effect of religiosity between climate change anxiety and death anxiety among a sample of Lebanese adults

• Jad Abou Jaoude 1 ,
• Sahar Obeid 2 ,
• Diana Malaeb 3 ,
• Fouad Sakr 4 ,
• Mariam Dabbous 4 ,
• Sami El Khatib 5 , 6 ,
• Souheil Hallit 1 , 7 , 8 ,
• Feten Fekih-Romdhane 9 , 10 &
• Rabih Hallit 1 , 11 , 12  

BMC Psychology volume  12 , Article number:  453 ( 2024 ) Cite this article

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Acknowledging the increasing worry over climate change and its psychological effects, the aim of this research is to clarify the dynamics between religiosity, climate anxiety and death anxiety, seeking to figure out the way religiosity mitigates the psychological effects of existential anxieties and climate related anxiety.

Using Google Forms, a questionnaire was developed and disseminated through a variety of messaging platforms, such as WhatsApp, Instagram, and Facebook Messenger. Through a snowball sampling technique, 763 participants were recruited in this cross-sectional during September 2023.

The subsequent variables were adjusted in the moderation analysis: age, gender, and place of living. The results suggested that religiosity levels moderated the association between climate anxiety and death anxiety (Beta = 0.02, t  = 1.97, p  = .05, 95% CI 0.001, 0.035). At low, moderate, and high levels of religiosity, higher climate anxiety was significantly associated with more death anxiety. In addition, at low levels of climate anxiety, individuals with higher levels of religiosity (22.66) had more decreased levels of death anxiety compared to those with lower levels of religiosity (11.99). As climate anxiety levels increase, inverted patterns can be observed, with highly religious individuals showing higher levels of death anxiety than those with lower levels of religiosity. Overall, the relationship between climate anxiety and death anxiety was found to be weakest at low levels of religiosity and strongest at high levels of religiosity.

Our findings suggest a possible beneficial effect of high religiosity at low levels of climate anxiety. This effect is reversed as climate anxiety starts to increase. Therefore, clinicians and policy-makers should bear in mind these complex interactions when designing strategies to mitigate mental health problems in the context of climate crisis.

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Introduction

The issue of climate change has emerged as one of the world’s most serious and pressing issues today. Concerns about climate change are becoming more widespread; a previous study showed that a median of 54% of the countries polled believe it to be a very severe issue, and 85% believe it to be at least somewhat serious [ 1 ]. Given the inextricable relationship between climate change and the rising frequency of catastrophic and devastating weather events, this growing fear holds merit [ 2 ].As the environment’s apparent deterioration digs deeper into the global community, the concept of “climate anxiety” is erupting as a tangible sign of widespread uneasiness and discomfort [ 3 ]. There are different definitions of climate anxiety in the literature, including “difficult feelings because of the ecological crisis” [ 4 ], “apprehension and stress about anticipated threats to salient ecosystems” [ 5 ], and “a chronic fear of environmental doom” [ 6 ]. Indeed, emerging research has shown that high levels of climate anxiety are likely to trigger mental health problems, including anxiety disorders [ 7 ]. A systematic review by Boluda-Verdu et al. [ 8 ] found that climate anxiety is significantly linked to worse self-rated mental health, including increased symptoms of anxiety. Nevertheless, studies investigating latent mental health issues that may possibly emerge from climate anxiety are still scarce and our knowledge of the processes involved remains limited. The present study proposes to focus of the relationship and pathways linking climate anxiety and another specific form of anxiety that can be experienced when facing an inescapability of death or mortality salience, i.e. death anxiety [ 9 ].

Death anxiety and climate change

Death anxiety, which has its roots in the fundamental human condition, remains a multidimensional phenomenon that humans of all cultures and religions encounter and occasionally struggle with [ 10 , 11 ]. Death anxiety, although ubiquitous, is not static. Rather, it changes as people age, shaped by their experiences, cultural values, and social mores [ 12 ]. For instance, higher degrees of death anxiety could arise because of worries regarding the growing environmental catastrophe [ 13 ]. People’s concerns about the environment are found to be strongly associated with anxiety of death [ 14 ]. Awareness about the climate crisis may face the individual with their own fragility and ineluctable mortality, contributing in turn to death anxiety [ 15 ]. Budziszewska & Jonsson [ 15 ] explored climate change-related concerns from an existential perspective through semi-structured interviews with affected Swedish patients who were under psychotherapy, and indicated that participants’ accounts of climate anxiety were related to worries about climate change becoming “death-extended”, “the death of humanity”, “existential crisis”, and “increased mortality salience”, Altogether, climate anxiety seems to worsen existential anxieties and worries about mortality [ 16 ]. Hence, individuals struggle in dealing with existential unease, which will then contribute to an increased death worry [ 3 ]. There appearsan intricate connection between existential fears, environmental concerns, and mental wellness consequences, underlining the critical importance of targeting existential issues in both mental health interventions and climate change mitigation [ 16 ]. Hence, a good understanding of the mechanisms underlying the associations between climate anxiety and death anxiety are needed to prevent and reduce distress in those who are the most exposed to climate challenges and are at-risk for suffering from climate worries. To participate in advancing knowledge in their field, and based on the literature available, our study sought to examine the role of a potential mediator, i.e. religiosity, in the association between climate anxiety and death anxiety.

Religiosity as a moderator between climate anxiety and death anxiety

Because religiosity is commonly used as an indicator of population health, involving mental health [ 17 ]* has a significant and crucial influence on the way individuals perceive and understand death [ 11 ]. It has been suggested from a theoretical point of view that, by supplying reassurance of tangible and concrete eternality, religion may furnish a distraction from the fear of dying, thus decreasing anxiety related to death [ 1 , 18 ]. Since the 70s, there has been empirical efforts to examine how religiosity relates to death anxiety. Results, however, have been mixed and inconclusive (for reviews, see Donahue (1985) [ 19 ] and Donovan (1994) [ 20 ]). Although some researchers pointed to lower death anxiety in more religiously committed people [ 21 ], [ 22 ], others could show no support for this finding [ 23 ], or even showed that levels of religiosity did not reduce or intensify death anxiety [ 24 ]. More recent studies have also led to inconsistent findings, reporting either positive [ 25 ], negative [ 26 ], or non-significant correlations [ 27 ]. Ellis et al. [ 28 ] reviewed 84 papers on the link between death anxiety and religiosity; they found a positive correlation in 27 studies, a negative correlation in 40 studies, and a lack of significant correlation in either direction in 41 studies. A more recent systematic review encompassing 100 studies observed an inverted-U relationship between religiosity and death anxiety, with death anxiety being at its lowest levels in both very religious and very non-religious people [ 29 ].Similar controversies surround the relationship between religiosity and climate anxiety. There is some evidence to suggest that religiosity can serve as a protective factor against worry and anxiety [ 30 ]. Although some previous findings indicated that less anxiety of climate change is linked to a stronger religious conviction [ 31 ], and certain researchers find a positive relationship between climate skepticism and religiosity [ 32 ], others suggest a less favorable outcome or even find no relationship at all [ 33 ]. However, to date, only limited understanding exists on the role of religiosity in facing anxiety caused by climate change and easing its detrimental effects on mental health. Another important consideration is that the majority of literature available was from western and Asian countries [ 20 ]. Given the evidence in favor of cultural variation in climate anxiety [ 34 ] and death anxiety [ 20 ], looking at the complex pathways linking climate anxiety, death anxiety, and religiosity in culturally and religiously diverse populations could help mental health practitioners in making informed decisions about climate distress interventions.

The present study

Lebanon is a Middle-Eastern country with a well-known vulnerability to climate change, which is firstly due to its geographic location [ 35 , 36 , 37 , 38 ]. Indeed, the Middle-East region emerges as one of the hot spots for, aridity conditions, drought and worsening extreme heat under climate change [ 36 ]. Other factors also play a role in the increased vulnerability of the Lebanese to climate change consequences, such as the country’s limited supply of land and water resources, as well as rising urbanization [ 39 ]. Furthermore, cross-cultural research has shown that Arab people, including Lebanese, exhibited higher levels of death anxiety than their counterparts from a Western context [ 40 ].In light of the points mentioned above, this study aims to examine the moderating role of religiosity in the association between climate anxiety and death anxiety, for the first time, in a vulnerable population group of community adults from a Middle-Eastern country.

Study design

Using Google Forms, a questionnaire was developed and disseminated thought a variety of messaging platforms, such as WhatsApp, Instagram, and Facebook Messenger. Through a snowball sampling, 763 participants were recruited in this cross-sectional in September 2023. In order to be eligible for participation, individuals needed to be Lebanese citizens residing in Lebanon and be 18 years old or older. Considering that an online survey was created for this study, internet access was a necessity, alongside a desire to partake in the research study. The study excluded participants who refused to answer the questionnaire. The assessment tools provided in the questionnaire were presented in a randomized order to mitigate any potential order-related biases. Participants were assured confidentiality and anonymity, while agreeing to complete the questionnaire voluntarily without any form of compensation.

Minimal sample size calculation

The G-power program was used to estimate a minimum sample size of 763 participants (F test, 5% multiple regressions, R [ 2 ] deviation from zero, ⍺ error = 5%, power = 80%).

Questionnaire and variables

The questionnaire took about fifteen minutes to complete, and it was sent in Arabic which is Lebanon’s native language. It was composed of multiple sections: the sociodemographic details in the first section, including gender, along with age, place of living, marital status, education level, Household Crowding Index which is computed by dividing the entire number of residents in a home—apart from a newborn—by the total number of rooms—apart from the kitchen and bathrooms—in that home [ 41 ]. Concerning their perceived financial burden, participants were requested to provide an answer on one question “How much pressure do you feel with regard to your personal financial situation in general?” on a scale from 1 to 10, with 10 referring to overwhelming pressure. The second section of the questionnaire contained the following scales:

Death Anxiety Scale , validated in Arabic [ 42 ], is a reliable tool to assess individuals’ anxiety regarding mortality. The 17 items on the Death Anxiety Scale are based on a Likert scale with five points, ranged from “totally disagree = 1” to “totally agree = 5” (e.g. Do you worry about dying? ; Does it bother you that you may die before you have done everything you wanted to do? ) [ 43 ]. Higher score translates an increased level of death anxiety [ 44 ] (α = 0.97 / ω = 0.97).

Central Religiosity Scale , This instrument evaluated the importance and of religiosity in individuals [ 45 ]. This brief version has five items with ratings on a Likert scale of five (1 = Never, 5 = Very Often) (e.g. How often do you think about religious issues? ; To what extent do you believe that God or something divine exists? ). The more a person is committed to their religious beliefs, the greater the score of this scale. This version is also validated in Arabic with sound psychometric properties [ 46 ] (α = 0.97 / ω = 0.97).

Climate Anxiety Scale is composed of 13 items and validated in Arabic [ 47 ]. This scale is used to measure people’s psychological reactions to climate change. The cognitive impairment and functional impairment subscales make up the two subscales of the climate anxiety scale [ 48 , 49 ]; Each topic is graded using a Likert scale that goes from “1” (strongly disagree) to “5” (strongly agree) (e.g., I have problems balancing my concerns about sustainability with the needs of my family) [ 49 ]. Higher scores match higher degrees of climate anxiety (α = 0.97 / ω = 0.97).

Statistical analysis

The SPSS software v25 was used to do the statistical analysis. Cronbach’s α / McDonald’s ω values were calculated for internal consistency. The death anxiety score was normally distributed since the skewness and kurtosis values were inside the − 1 and + 1 interval [ 50 ]. Two means were compared employing the Student’s t-test, and two continuous variables were correlated using the Pearson test. With PROCESS MACRO, the moderation analysis was carried out (an SPSS add-on) v.3.4 model 1 [ 51 ]. Interaction terms were probed by examining the association of climate anxiety with death anxiety at the mean, 1 SD below the mean and 1 SD above the mean of the moderator (religiosity). All variables with a p  < .25 in the bivariate analysis were entered as confounding variables in the moderation model [ 52 ]. Statistics were considered significant when P  < .05.

Sociodemographic and other characteristics of the sample

This study involved 763 individuals, whose mean age was 25.48 ± 10.98 years [min = 18; max = 82] and 63.4% females’ participation. Table  1 provides more sample descriptive statistics.

Bivariate analysis of factors associated with death anxiety

Tables  2 and 3 provide a summary of the findings from the bivariate analysis of the variables linked to death anxiety. According to the findings, women’s mean death anxiety scores were noticeably greater than men’s. Moreover, higher religiosity was notably related to less death anxiety, in contrast higher climate anxiety was strongly affiliated with higher death anxiety. Finally, higher religiosity was significantly associated with lower climate anxiety ( r  = − .18; p  < .001).

Moderation analysis

The following variables have been accounted for the moderation analysis: age, gender, and place of living. The outcomes demonstrated that religiosity moderated the association between climate anxiety and death anxiety (Beta = 0.02, t  = 1.97, p  = .05, 95% CI 0.001, 0.035) (Table  4 ). At low, moderate and high levels of religiosity, higher climate anxiety was significantly associated with more death anxiety (Table  5 ; Fig.  1 ). In addition, at low levels of climate anxiety, individuals with higher levels of religiosity (22.66) had more decreased levels of death anxiety compared to those with lower levels of religiosity (11.99). As climate anxiety levels increase, inverted patterns can be observed, with highly religious individuals showing higher levels of death anxiety than those with lower levels of religiosity. Overall, the relationship between climate anxiety and death anxiety was found to be weakest at low levels of religiosity and strongest at high levels of religiosity (Fig.  1 ).

Interaction climate anxiety by religiosity on death anxiety

This research looked into how religion could play a moderating role between death anxiety and climate anxiety across a group of Lebanese adults from the general population. The outcomes demonstrated that at low, moderate, and high levels of religiosity, higher climate anxiety was significantly associated with more death anxiety.

The correlation between death anxiety and climate anxiety has been found to be moderated by religiosity, according to our study. Thus, at all levels of religiosity, higher climate anxiety was strongly correlated with greater death anxiety. Looking more in depth into the moderation model, it appears that the relationship between climate anxiety and death anxiety is strongest at high levels of religiosity and weakest at low levels of religiosity. Additionally, patterns emerge suggesting that at low levels of climate anxiety, individuals with higher religiosity report lower death anxiety. However, as climate anxiety intensifies, this gap diminishes and even reverses at the highest levels of climate anxiety. Direct comparison of our findings with previous literature is challenging, because the evidence for any correlational relationship between religiosity and death anxiety is widely debated and largely controversial [ 19 ], [ 53 ], [ 28 ]. Historically, fear of death has been considered the chief cause of religiosity from the theorists of religion perspective [ 54 ]. The Terror Management Theory posits that religiosity may offer both symbolic and literal immortality in the forms of afterlife belonging [ 54 ]. However, several empirical findings did not provide any support for these theories, reporting, in contrast, either no association (e.g., (Bakan et al. 2019) [ 27 ] or a negative correlation (e.g., (Marin 2019)) [ 26 ] between religiosity and death anxiety. Leming [ref] argued that religiosity can be both arousing and relieving for death anxiety. For example, religion can arouse fear if it evokes thoughts about judgment after death and divine punishment for committed sins, but religion can also relieve anxiety in people who expect life after death. Some researchers attempted to resolve these controversies by suggesting a curvilinear relationship, such that the direction of the association varies as the person becomes more or less religious: at the lowest levels of religiosity, death anxiety may reduce irreligiosity, whereas at the highest levels of religiosity death anxiety can be at its lowest [ 28 ]. A systematic review posited that the relationship between religiosity and death anxiety follows an inverted-U pattern, with death anxiety being at its lowest levels in both very religious and very non-religious people [ 29 ].

On the other hand, the field of climate anxiety is evolving, but is still in its infancy. The relatively limited amount of research done in this area to date yielded mixed findings, showing negative [ 31 ], positive [ 32 ], or non-significant [ 33 ] links between climate anxiety and religiosity. Overall, our findings bring a new perspective to these relationships in a population and country shown to be vulnerable to both climate anxiety and death anxiety, and provide further support to previous literature that the role of religiosity is rather complex. Our moderation results suggest that religiosity could, at some extent, protect individuals from death anxiety, particularly when climate anxiety is still at low levels. However, religiosity seems to lose its protective role and to even exacerbate death anxiety at more severe levels of climate anxiety.

Clinical implications

According to the World Health Organization, climate change is expected to cause around 250 000 additional deaths per year between 2030 and 2050, with substantial direct damage costs to health [ 55 ]. Given the expected exacerbations of the climate crisis and its subsequent psychological responses over the next years, it appears urgent to foster research in this area, particularly in people living in areas highly susceptible to climate change, such as Lebanon. Such research can help inform policy makers’ decisions when preparing and responding to the climate crisis and its harmful effects on the population. The way that religiosity affects the relationship between climate anxiety and death anxiety appears to be complex. Our findings suggest a possible beneficial effect of high religiosity at low levels of climate anxiety. This effect is reversed as climate anxiety starts to increase. Therefore, clinicians and policy-makers should bear in mind these complex interactions when designing strategies to mitigate mental health problems in the context of climate crisis.

As our study is the first to explore the relationships between climate anxiety, religiosity and death anxiety, researchers are urgently called to replicate the study’s model in other countries using experimental and longitudinal designs to capture causality. This could allow to build on and confirm our findings’ applicability in other contexts, and will hopefully enable people’s psychological readiness to face the challenges of climate change. An enhanced understanding the moderating effect of religiosity between climate anxiety and death anxiety could aid in the development of personalized interventions [ 55 ].

Limitations

There are few limitations to be aware of. Despite the fact that this study offers valuable information regarding the intricate relationship among death anxiety, climate anxiety and religiosity, the cross-sectional nature of the study limits the capacity to determine the causality or deduce longitudinal connections between the variables we are examining. More convincing evidence regarding the directionality of the observed connections could potentially be give through future studies using experimental or longitudinal techniques. Furthermore, the inclusion of self-reported measures enhances the likelihood of bias, such as recall bias, which might distort the collected data. Because participants can possibly misinterpret a question, there could be information bias, which would have lowered the reliability of an answer. The snowball sampling technique followed for the recruitment may introduce potential biases due to its non-random nature since participants who took the survey are likely have similar social circles or religiosity background, which may introduce the moderator (religiosity) bias and possibly limit the generalizability of our results to the general population. Residual confounding bias is also possible since some factors (e.g. religion) were not considered in the survey.

To sum up, this study delivers a substantial contribution to our comprehension of the complex associations between climate anxiety, death anxiety and religiosity. In addition, it highlights the complexities of behavioral mechanisms that underpin the way individuals’ respond to existential hazards. The recognition of the enduring impact of climate anxiety on individuals and its potential link with death anxiety highlights the urgency of providing interventions that could enhance the well-being of individuals facing the anxiety evoked by the threat of climate change. Through analyzing the moderating effect of religiosity, we have uncovered empirical proof suggesting that religiosity can be protective against death anxiety in some circumstances, when climate anxiety is low. However, religiosity seems to lose its protective property when climate anxiety increases. Lastly, examining a different population could help researchers and clinicians better understand the effect of religiosity on the associations detected since religious beliefs are heavily impacted by individual and contextual variables.

Data availability

The datasets generated and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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Jad Abou Jaoude, Souheil Hallit & Rabih Hallit

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Sahar Obeid

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Diana Malaeb

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Souheil Hallit

Applied Science Research Center, Applied Science Private University, Amman, Jordan

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FFR, DM, SO and SH designed the study; JAJ drafted the manuscript; SH carried out the analysis and interpreted the results; SEK, MD and FS collected the data; RH and all authors reviewed the paper for intellectual content; all authors reviewed the final manuscript and gave their consent.

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Abou Jaoude, J., Obeid, S., Malaeb, D. et al. The moderating effect of religiosity between climate change anxiety and death anxiety among a sample of Lebanese adults. BMC Psychol 12 , 453 (2024). https://doi.org/10.1186/s40359-024-01942-z

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Patient and public involvement and engagement in the ASCEND PLUS trial: reflections from the design of a streamlined and decentralised clinical trial

• Muram El-Nayir 1   na1 ,
• Rohan Wijesurendra   ORCID: orcid.org/0000-0002-8261-8343 1   na1 ,
• David Preiss 1 ,
• Marion Mafham 1 ,
• Leandros Tsiotos 1 ,
• Sadman Islam 1 ,
• Anne Whitehouse 1 ,
• Sophia Wilkinson 1 ,
• Hannah Freeman 1 ,
• Ryonfa Lee 1 ,
• Wojciech Brudlo 1 ,
• Genna Bobby 1 ,
• Bryony Jenkins 1 ,
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• Graeme Thomson 2 ,
• Firoza Davies 2 ,
• Hameed Khan 2 ,
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Introduction

ASCEND PLUS is a randomised controlled trial assessing the effects of oral semaglutide on the primary prevention of cardiovascular events in around 20,000 individuals with type 2 diabetes in the UK. The trial’s innovative design includes a decentralised direct-to-participant invitation, recruitment, and follow-up model, relying on self-completion of online forms or telephone or video calls with research nurses, with no physical sites. Extensive patient and public involvement and engagement (PPIE) was essential to the design and conduct of ASCEND PLUS.

To report the process and conduct of PPIE activity in ASCEND PLUS, evaluate effects on trial design, reflect critically on successes and aspects that could have been improved, and identify themes and learning relevant to implementation of PPIE in future trials.

PPIE activity was coordinated centrally and included six PPIE focus groups and creation of an ASCEND PLUS public advisory group (PAG) during the design phase. Recruitment to these groups was carefully considered to ensure diversity and inclusion, largely consisting of adults living with type 2 diabetes from across the UK. Two members of the PAG also joined the trial Steering Committee. Steering Committee meetings, focus groups, and PAG meetings were conducted online, with two hybrid workshops to discuss PPIE activity and aspects of the trial.

PPIE activity was critical to shaping the design and conduct of ASCEND PLUS. Key examples included supporting choice for participants to either complete the screening/consent process independently online, or during a telephone or video call interview with a research nurse. A concise ‘initial information leaflet’ was developed to be sent with the initial invitations, with the ‘full’ information leaflet sent later to those interested in joining the trial. The PAG reviewed the content and format of participant- and public-facing materials, including written documents, online screening forms, animated videos, and the trial website, to aid clarity and accessibility, and provided input into the choice of instruments to assess quality of life.

Conclusions

PPIE is integral in ASCEND PLUS and will continue throughout the trial. This involvement has been critical to optimising the trial design, successfully obtaining regulatory and ethical approval, and conducting the trial.

Peer Review reports

ASCEND PLUS is an ongoing randomised placebo-controlled trial assessing the effects of oral semaglutide on cardiovascular and other outcomes in people with type 2 diabetes and no history of heart attack or stroke (NCT05441267). ASCEND PLUS will recruit approximately 20,000 participants in the UK. Potential participants are sent an invitation by post and the trial requires no in-person visits. Study medication is mailed directly to participants’ homes. This design represents a shift from the traditional concept of face-to-face interaction between research staff and participants at a clinical site and has become more common in recent years, perhaps accelerated by the COVID-19 pandemic [ 1 ]. Decentralised direct-to-participant designs, including that of ASCEND PLUS, offer the possibility to expand participation in clinical trials and increase the generalisability of results [ 1 ].

The ASCEND PLUS trial design was developed with extensive patient and public involvement and engagement (PPIE), to ensure that the participant experience is as good as it can be, the safety and wellbeing of the participants is protected, recruitment to the trial is successful, and the engagement and adherence of participants is maintained. ASCEND PLUS commenced recruitment in March 2023, and the estimated primary completion date of the trial is 2028.

PPIE is increasingly recognised as a key element in the development of all research [ 2 ], including clinical trial proposals and protocols. PPIE can harness the valuable insights of those living with and affected by a disease or health condition, and ensure that the trial findings are relevant to the needs of patients, and their relatives and carers [ 3 ]. “Involvement” can be defined as activities and research carried out “with” or “by” members of the public or patients, rather than “to”, “about”, or “for” them. In this instance, this refers to the active involvement of patients and members of the public in the development of the trial design and the conduct of the trial [ 4 ]. In contrast, “engagement” focuses on how the trial findings can be shared with patients and the public in a two-way process that encourages communication and interactions with researchers [ 4 ]. Despite the recognition of the importance and potential value of PPIE in clinical trials, implementation remains variable at present with inconsistency between trials [ 5 ].

Here, we aim to report the process and details of PPIE activity during the planning and initiation of ASCEND PLUS, evaluate how this helped to shape the final trial design, reflect critically on successes and aspects that could have been improved, and draw out themes and learning relevant to the implementation of PPIE in future trials.

Methods and results

Theoretical considerations.

The revised Guidance for Reporting the Involvement of Patients and the Public (GRIPP-2) long-form checklist [ 6 ] was used to guide the drafting of this report (see Supplementary Table 1).

Resourcing of PPIE activities

PPIE in ASCEND PLUS was organised by dedicated PPIE officers working within the communications team alongside the core trial team comprised of investigators, trial managers, and administrative staff at the Nuffield Department of Population Health at the University of Oxford (which sponsors the trial). An appropriate level of funding was available in the trial budget for PPIE activity, and all PPIE representatives were able to claim monetary compensation for their time, lived experience, and contribution, in line with guidance from the National Institute for Health and Care Research (NIHR) [ 7 ] and accepted best practice. Any out-of-pocket expenses (such as travel) incurred by PPIE representatives were reimbursed in full, and refreshments were provided at in-person meetings.

Format of PPIE activities

PPIE activity in ASCEND PLUS consisted of several linked components, beginning early in the design phase of the trial and is planned to continue through to trial completion and dissemination of the results.

Firstly, a series of six patient and public focus groups were convened to address specific issues. These focus group meetings largely involved people living with type 2 diabetes and included people from diverse backgrounds from across the UK.

Secondly, a trial-specific Public Advisory Group (PAG) was established. The PAG is responsible for providing feedback, advice, and opinions on many different aspects of ASCEND PLUS over the entire lifecycle of the trial.

Thirdly, in order to ensure patient involvement in the design and conduct of ASCEND PLUS at a strategic level, two members of the PAG who are individuals living with diabetes were also invited to join the Trial Steering Committee.

Steering Committee meetings, focus groups, and PAG meetings were largely conducted online using remote meeting software. Two in-person PPIE workshops were convened in Oxford. This combination of online and in-person meetings has been suggested to be favourable in a previous mixed methods study [ 8 ].

Recruitment and selection of focus groups and the PAG

The recruitment and selection of the focus groups and the PAG was carefully considered to ensure inclusivity and representation, for features including age, sex, and ethnicity. People living with type 2 diabetes were prioritised, given that ASCEND PLUS is a trial in this population.

The six focus groups were organised with support from the Nuffield Department of Population Health’s Public Advisory Group and four external organisations (Table  1 ). Each focus group was drawn from a specific geographic location (Leicester, Oxford, the north of England [two groups], Wales, and Scotland), to provide coverage of the areas of the UK in which ASCEND PLUS plans to recruit. The focus group based in Leicester was from the Centre for Ethnic Health Research and consisted of individuals of South Asian, Black Caribbean, and Black African ethnicity. The size of, and strategy used to achieve diverse representation within, each group was usually determined by the groups themselves.

Members of the PAG were invited from an existing departmental public advisory panel and the focus groups described above. The PAG was chosen to comprise a diverse group of patients and the public.

Involvement of PPIE panels and the PPIE advisory group in the research proposal

During the design phase of ASCEND PLUS, the six online PPIE focus groups (described above) were convened to address specific issues. Given the remote design of the trial with no in-person visits, the main topics discussed were the consent model and the recruitment/invitation methods. There was also discussion about other aspects of the trial design, including the active run-in, in which all participants receive the active drug prior to randomisation. These concepts were serially developed across the six focus groups, which took place between June and September 2021, with revisions made to the study design in response to the feedback received prior to the application for ethical approval.

Two people living with diabetes were next invited to join the Steering Committee. These individuals attended the first Steering Committee meeting in June 2021 and will continue to attend Steering Committee meetings until the completion of the trial. These patient and public contributors are members of the Steering Committee, contribute to discussions at meetings, and can vote on any decisions made by the Committee. They are also the joint senior authors of this publication (SD and JR).

The trial PAG was then assembled, including SD and JR amongst the members. The PAG contributed in detail to the design and review of all patient-facing study material, the online forms and videos used for the trial, and the trial website. This activity was organised through emails and online group meetings, as well as one face-to-face workshop in Oxford. The PAG will continue to contribute during the remainder of the trial, for example by reviewing planned patient newsletters and advising on local activities to aid recruitment. The PAG will also input on the interpretation of the trial results in due course, and specifically on their presentation and dissemination to patients and the public.

Impact of PPIE on ASCEND PLUS design and conduct

The six PPIE focus groups were critical to shaping the design and conduct of ASCEND PLUS. Full details of the composition and date of each of the six focus groups, the subjects discussed, and the feedback and impact are summarised in Table  1 .

Initially, it had been planned to invite all participants to complete self-directed online screening and consent, with an option of a telephone or video call if needed. A clear theme that emerged in the focus groups was support for choice in how participants interact with the trial: i.e. either online completion of study assessments on their own device (with the option to speak to a research nurse or study doctor at any time) or completion of study assessments during interviews with a research nurse. Therefore, recording of informed consent also needed to include both an online consent option (that can be completed by a participant independently) and the option to give consent during a telephone or video call with a research nurse. It was also felt to be important that participants can switch between these two methods of participation at any stage if they wish to. The exception to this concept was for non-English speakers, in whom a telephone or video call with a research nurse (aided by a translator) was recommended to ensure adequate understanding. In light of this feedback from the focus groups, the trial procedures were modified. The updated trial design now asks potential participants to indicate on the initial reply form which method (self-directed online versus telephone/video call with a research nurse) they prefer. Options have also been added to allow participants to change their trial interaction method during the course of the trial.

Another key impact on design and conduct of the trial resulted from feedback that the patient information leaflet was very long, due to the need to contain multiple items deemed mandatory by regulatory bodies. The focus group supported provision of an abbreviated “initial information leaflet” (rather than the “full” participant information leaflet) with the invitation letter, with the “full” patient information leaflet [ 9 ] subsequently supplied to those individuals who had declared interest in participating after reviewing the abbreviated leaflet.

The PPIE focus groups supported the proposed invitation method for ASCEND PLUS. In brief, this is conducted with the support of the NHS DigiTrials recruitment support service who undertake a search of electronic medical records to identify individuals who are potentially eligible (without individual patient consent at this stage). The name, address, and postcode of these individuals are then passed securely to a mailing house (who also handle patient letters for the NHS) who then send out study invitation letters. The details of potential participants are not disclosed to the ASCEND PLUS study team unless and until the participant returns the reply form, which includes the participant’s name and the details they add to it (such as telephone number, or email address). The reply form also contains a unique identifier which the ASCEND PLUS team send to NHS DigiTrials to obtain the participant’s name, address, sex, date of birth, NHS number, and GP surgery details from NHS records. The positive feedback from the PPI focus groups regarding the use of healthcare data in this way was cited in the application for regulatory approval. This recruitment method was supported by the Health Research Authority (HRA), who also followed advice from the Confidentiality Advisory Group (an independent body which provides expert advice on the use of confidential patient information). A separate data protection leaflet which is supplied to prospective participants covers all aspects of how data about ASCEND PLUS participants is processed [ 10 ].

The ASCEND PLUS PAG also undertook a detailed review of the three leaflets discussed above (initial information leaflet, full participant information leaflet, data protection leaflet), the trial invitation letter, and the study treatment information leaflets (one of which is included with each pack of study treatment mailed to a participant). Recommended text and content changes were made accordingly, ensuring that the text of each document remained consistent with trial processes. This extensive PPIE review and consultation process has resulted in documents which are easier to understand and more inclusive. This also included feedback about accommodating people with visual impairments. Examples of specific changes made to the text of study documents are shown in Fig.  1 .

Examples of specific changes made to the text of the ASCEND PLUS participant information leaflet after PPIE input

The PAG were then involved in co-developing an animated video to support the self-directed online consent process. The PAG initially contributed to the development of the script and then provided feedback on the images used in the storyboard, with many of the specific points raised implemented in the final version. For example, the images of potential participants in the video were updated to ensure greater diversity, and a border line was drawn on a map of the UK to highlight the geographical areas in which ASCEND PLUS plans to recruit.

The PAG was instrumental in the selection of quality of life questionnaires included in ASCEND PLUS. Whilst inclusion of the EQ5D questionnaire is commonplace due to its importance to the National Institute for Health and Care Excellence (NICE), several options existed for an additional questionnaire to capture diabetes-specific quality of life. The Problem Areas in Diabetes (PAID), Patient Health Questionnaire 9 (PHQ-9), Diabetes-Dependent Quality of Life questionnaire (ADDQoL), and the Diabetes Treatment Satisfaction Questionnaire (DTSQ) were all considered. PAG members ranked the questionnaires separately on whether they thought they collected a meaningful and relevant assessment for people with diabetes, and whether participants would be willing to complete them. The PAG members were also separately asked to consider the feasibility of participants completing the 36-Item Short Form Survey questionnaire (SF-36) compared to the 12-item version (SF-12). Following detailed feedback from the PAG, the SF-12 and the PAID questionnaire were included in the final ASCEND PLUS protocol.

The PAG also reviewed the text and format of the questions included in the draft screening form (to be completed either by participants on their own devices or by research nurses in conversation with participants) and provided detailed feedback. A number of changes were implemented based on this, including changes to the order in which questions are asked and revisions to the working of particular questions to make them easier to understand.

A summary of PPIE in ASCEND PLUS is included in a dedicated page on the trial website, which also includes a video of two public contributors discussing their experience [ 11 ]. This activity, and the impact that it has had on the final design of ASCEND PLUS, is also summarised in Fig.  2 .

Summary of Public Advisory Group activity and impact in ASCEND PLUS

Impact of PPIE on individuals involved, and wider impact

The impact of PPIE in ASCEND PLUS on the individuals involved and the wider impact was considered in detail at a workshop convened on 26 November 2022, which included ten members of the PAG as well as investigators, trial managers, research fellows, and PPIE officers from the Nuffield Department of Population Health.

The context and process of PPIE in ASCEND PLUS were considered in some detail. Themes that emerged in this discussion included the fact that PAG members reported an overall highly positive experience. They commented that on-boarding for new members worked well and that the process had been well organised, with all members having a clear idea of upcoming tasks with regular updates from the study team. Having a single point of contact (the PPIE team at the Nuffield Department of Population Health) to coordinate the PPIE for the study was felt to be a major advantage. The logistical aspects of PAG group meetings were discussed and the format of online meetings scheduled in the evenings or at weekends was felt to be beneficial in avoiding travel time and allowing individuals the flexibility of contributing from their own home. Many meetings took place during periods of COVID-19 lockdowns, and being able to hold online meetings enabled these to go ahead and brought people together at a time of isolation. The benefits of in-person events (such as the PPIE workshop) were also discussed, and it was felt that some aspects, such as the ability to arrive early for social discussion and remain behind after the main meeting to ask questions and have private conversations, could also be implemented using the existing features offered by major online meeting platforms.

The inclusive nature of the PPIE process in ASCEND PLUS was praised. Specifically, discussion focused on the decision to actively encourage the involvement of contributors without previous PPIE experience, as well as the expectation in PAG meetings that everyone is listened to equally and that there are “no silly questions”. Members of the PAG also reflected that external feedback on ASCEND PLUS documents (created with their input) has been very positive. For example, the Departmental Information Governance lead commented that the ASCEND PLUS data information leaflet was the best such example they had seen in their experience of advising on multiple trials over a number of years. Similarly, the process of conducting PPIE in ASCEND PLUS has been used as an exemplar in the MSc in Clinical Trials postgraduate course that is run by the Nuffield Department of Population Health at the University of Oxford for students from across the world.

Some areas that could have been improved were also identified. Occasionally, too much information could be presented in PAG meetings, and key questions cropping up towards the end of a meeting might have meant that they received less attention than they should have. It was also highlighted that technology can be a barrier for some people, particularly those lacking the digital skills or hardware to be able to participate in online meetings. For example, printed materials may need to be offered as not all individuals will have access to a printer. In a few cases, deadlines for responding to tasks were shorter than ideal, and it was recommended that circulation of slides and materials should be undertaken well in advance of a meeting to allow members enough time to consider them carefully. Finally, it was suggested that it would have been helpful to have a “global overview” of the planned PAG activities so that members had an idea of what had been completed already and what would be coming up next.

In terms of the effect on themselves as individuals, PAG members reported that they had found participation in PPIE activities for ASCEND PLUS highly enjoyable and reported that there was more “behind-the-scenes” activity than they had initially expected. There was consensus that it was highly rewarding being part of helping to create a study that may have a huge impact on people’s lives, and in ensuring that the study is accessible to people from all walks of life including groups who are traditionally under-represented in research. From a personal perspective, some members reported that they had found participation intellectually stimulating and that it helped them to keep up to date with diabetes research, and be more confident when talking about research in general.

Finally, it is recognised that this manuscript only presents qualitative reflections on PPIE in ASCEND PLUS. ASCEND PLUS is still early in recruitment at the present time, and presentation of quantitative data on recruitment and retention would not be particularly meaningful in the absence of a relevant control. Of note, a sub-study is planned to specifically evaluate consent in ASCEND PLUS, given the decentralised trial design.

Study design of ASCEND PLUS and the relevance to the PPIE strategy

At the outset of ASCEND PLUS, a number of challenges and opportunities were identified that would be critical to the success of the trial, including:

Gaining approval from the relevant bodies for an innovative, streamlined trial design that has no in-person visits and requires a non-traditional participant consent process.

Recruitment of a large number of people (20,000), aged 55 and over, living with type 2 diabetes from across the UK, who have not yet experienced a heart attack or stroke. In addition, ethnic diversity among trial participants is highly desirable, to ensure a trial population broadly representative of that of the wider UK.

Implementation of a trial where all interactions with participants would be conducted directly using innovative patient-centred web-based technology, supplemented by telephone, video-call contact and mailed letters.

A decentralised enrolment and consent process that is sufficiently flexible and adaptable to suit all participants, irrespective of preference for self-directed online interaction versus a telephone/video call with a research nurse.

A lengthy participation timescale of 5 years.

The role of PPIE was particularly critical in ASCEND PLUS, helping to optimise the trial design in the context of each of these points. As discussed in the above sections, various aspects of the trial design were altered in line with the public contributors’ feedback, sometimes in quite a major way such as the decision to allow choice in the method of interaction with the study.

Contextual and process factors influencing PPIE in ASCEND PLUS

PPIE in ASCEND PLUS has included several distinct phases, including six focus groups, the construction of a trial-specific PAG, and inclusion of two members of the PAG on the trial Steering Committee.

PPIE activity in ASCEND PLUS has been greatly enhanced by the recruitment of enthusiastic and dedicated members to the focus groups and PAG, coordination and organisation by experienced and professional PPIE officers, the willingness and desire of the trial investigators to modify the trial design in response to PPIE feedback, and adequate resourcing for PPIE activity in the trial budget. The use of digital technology and online meetings aided the efficiency and inclusivity of the process.

Some areas of difficulty were identified. The tight trial timeline meant that occasionally PAG members were under pressure to meet challenging deadlines for review of various materials, and some online sessions perhaps contained too much information. Adequate resourcing of PPIE activity is key to spreading the load on each individual member.

Influence of PPIE on the final ASCEND PLUS study design

PPIE greatly enhanced the final ASCEND PLUS study design. The changes made in response to the PPIE scoping exercises made the trial more inclusive, most notably in influencing the decision to give all participants a free choice in the method by which they interact with the study. The PPIE activity also heavily influenced almost all of the written and online material for the trial, making this more accessible and understandable, and also available in different formats and to those with visual impairment. Specifically, the experience afforded by individuals living with diabetes was highly valuable when considering the nature of the trial and the target population. The impact of PPIE activity on the study was evaluated by direct comparison of the final trial design to the initial proposals (with some examples included here), and by qualitative discussion with relevant stakeholders in a dedicated workshop convened for this purpose.

Learnings and recommendations for future large-scale clinical trials

Comprehensive and early PPIE is critical to gain input on all aspects of the proposed trial design and to optimise the relevance and acceptability to people living with diabetes. This involvement should start well before regulatory submissions, in order to allow time for changes to be made in response to PPIE group feedback. Involvement of dedicated and professional PPIE officers should be strongly considered to streamline the process, and adequate resourcing of PPIE activity is essential. Careful consideration should be given to how recruitment to focus groups and advisory groups is undertaken, making sure that assembled panels are inclusive and representative, and are able to work in a cohesive group and provide constructive comments and feedback in a timely manner. Feedback on participant- and public-facing supporting material such as information leaflets, animations, and the trial website helps to make these accessible and should improve recruitment and adherence, as well as the experience of recruited individuals. Inclusion of public contributors on the trial Steering Committee is important to ensure PPIE input to decision-making during the course of the trial. A summary of these recommendations is outlined in Fig.  3 . Finally, ASCEND PLUS is a UK-based trial, and there may be limited applicability to different healthcare systems and cultural contexts, or in resource-limited settings.

Learnings and recommendations for PPIE in future large-scale clinical trials

ASCEND PLUS is a large-scale trial with an innovative, streamlined design with a non-traditional participant consent process and no in-person study visits. Extensive PPIE has proven integral to the design and initiation of ASCEND PLUS and will continue throughout the trial. This involvement has been critical to optimising the trial design, successfully obtaining ethical and regulatory approvals, and conducting the trial.

Availability of data and materials

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Acknowledgements

The authors gratefully acknowledge the input from Parminder Hothi and other present and past members of the ASCEND PLUS Public Advisory Group who chose to remain anonymous and who are therefore not named as co-authors of this publication.

ASCEND PLUS is coordinated and sponsored by the University of Oxford and run with support from the National Institute for Health and Care Research. Novo Nordisk produces oral semaglutide and is providing the treatment for the study free of charge. Novo Nordisk has given a grant to the University of Oxford to help with the cost of running of the study but is not directly involved with either coordinating the study or analysing the results.

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Muram El-Nayir, Rohan Wijesurendra, Susan Dickie, and John Roberts contributed equally to this work.

Authors and Affiliations

Clinical Trial Service and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK

Muram El-Nayir, Rohan Wijesurendra, David Preiss, Marion Mafham, Leandros Tsiotos, Sadman Islam, Anne Whitehouse, Sophia Wilkinson, Hannah Freeman, Ryonfa Lee, Wojciech Brudlo, Genna Bobby, Bryony Jenkins, Robert Humphrey & Amy Mallorie

Public Advisory Group; ASCEND PLUS Clinical Trial, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK

Andrew Toal, Elnora C. Barker, Dianna Moylan, Graeme Thomson, Firoza Davies, Hameed Khan, Ian Allotey, Susan Dickie & John Roberts

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ME and RW: Lead authors of the manuscript with regular involvement in PAG meetings. DP and MM: Chief investigators of the ASCEND PLUS trial and the initiators of PPIE involvement throughout. Major contributors in writing and reviewing the manuscript. LT, SI, AW, SW and HF: PPIE officers for the ASCEND PLUS trial with substantial involvement in the recruitment and organisation of PAG meetings and collation of input obtained. RL, WB, RH, AM, BJ and GB: ASCEND PLUS Clinical & Administrative team involved in organisation of PAG meetings. AT, ECB, DM, GT, FD, HK and IA: PAG members who were major contributors in writing and reviewing the manuscript. SD and JR: Senior members of the PAG, who oversaw the writing of this manuscript. Major contributors in writing and reviewing the manuscript. All authors read and approved the final manuscript.

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Correspondence to Rohan Wijesurendra .

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El-Nayir, M., Wijesurendra, R., Preiss, D. et al. Patient and public involvement and engagement in the ASCEND PLUS trial: reflections from the design of a streamlined and decentralised clinical trial. Trials 25 , 554 (2024). https://doi.org/10.1186/s13063-024-08393-2

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The impact of study habits and personal factors on the academic achievement performances of medical students

• Mohammed A. Aljaffer 1 ,
• Ahmad H. Almadani 1 ,
• Abdullah S. AlDughaither 2 ,
• Ali A. Basfar 2 ,
• Saad M. AlGhadir 2 ,
• Yahya A. AlGhamdi 2 ,
• Bassam N. AlHubaysh 2 ,
• Osamah A. AlMayouf 2 ,
• Saleh A. AlGhamdi 3 ,
• Tauseef Ahmad 4 &
• Hamza M. Abdulghani 5  

BMC Medical Education volume  24 , Article number:  888 ( 2024 ) Cite this article

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Academic achievement is essential for all students seeking a successful career. Studying habits and routines is crucial in achieving such an ultimate goal.

This study investigates the association between study habits, personal factors, and academic achievement, aiming to identify factors that distinguish academically successful medical students.

A cross-sectional study was conducted at the College of Medicine, King Saud University, Riyadh, Saudi Arabia. The participants consisted of 1st through 5th-year medical students, with a sample size of 336. The research team collected study data using an electronic questionnaire containing three sections: socio-demographic data, personal characteristics, and study habits.

The study results indicated a statistically significant association between self-fulfillment as a motivation toward studying and academic achievement ( p  = 0.04). The results also showed a statistically significant correlation between recalling recently memorized information and academic achievement ( p  = 0.05). Furthermore, a statistically significant association between preferring the information to be presented in a graphical form rather than a written one and academic achievement was also found ( p  = 0.03). Students who were satisfied with their academic performance had 1.6 times greater chances of having a high-grade point average (OR = 1.6, p  = 0.08).

The results of this study support the available literature, indicating a correlation between study habits and high academic performance. Further multicenter studies are warranted to differentiate between high-achieving students and their peers using qualitative, semi-structured interviews. Educating the students about healthy study habits and enhancing their learning skills would also be of value.

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Introduction

Academic performance is a common indicator used to measure student achievement [ 1 , 2 ]. It is a compound process influenced by many factors, among which is study habits [ 2 , 3 ]. Study habit is defined as different individual behavior in relation to studying, and is a combination of study methods and skills [ 2 , 3 , 4 ]. Put differently, study habits involve various techniques that would increase motivation and transform the study process into an effective one, thus enhancing learning [ 5 ]. Students’ perspectives and approaches toward studying were found to be the key factors in predicting their academic success [ 6 , 7 ]. However, these learning processes vary from one student to another due to variations in the students’ cognitive processing [ 8 ].

The study habits of students are the regular practices and habits they exhibit during the learning process [ 9 , 10 ]. Over time, several study habits have been developed, such as time management, setting appropriate goals, choosing a comfortable study environment, taking notes effectively, choosing main ideas, and being organized [ 11 ]. Global research shows that study habits impact academic performance and are the most important predictor of it [ 12 ]. It is difficult for medical students to organize and learn a lot of information, and they need to employ study skills to succeed [ 1 , 2 , 5 , 13 ].

Different lifestyle and social factors could affect students’ academic performance. For instance, Jafari et al. found that native students had better study habits compared to dormitory students [ 1 ]. This discrepancy between native and dormitory students was also indicated by Jouhari et al. who illustrated that dormitory students scored lower in attitude, test strategies, choosing main ideas, and concentration [ 10 ]. Regarding sleeping habits, Curcio G et al. found that students with a regular and adequate sleeping pattern had higher Grade Point Average (GPA) scores [ 14 ]. Lifestyle factors, such as watching television and listening to music, were shown to be unremarkable in affecting students’ grades [ 15 , 16 ]. Social media applications, including WhatsApp, Facebook, and Twitter, distract students during learning [ 16 , 17 ].

Motivation was found to be a major factor in students’ academic success. Bonsaksen et al. found that students who chose “to seek meaning” when studying were associated with high GPA scores [ 18 ]. In addition, low scores on “fear of failure” and high scores on “achieving” correlated with a higher GPA [ 8 , 18 ].

Resource-wise, Alzahrani et al. found that 82.7% of students relied on textbooks assigned by the department, while 46.6% mainly relied on the department’s lecture slides [ 19 ]. The study also indicated that 78.8% perceived that the scientific contents of the lectures were adequate [ 19 ]. Another study found that most students relied on the lecture slides (> 83%) along with their notes, followed by educational videos (76.1%), and reference textbooks (46.1%) [ 20 ]. Striking evidence in that study, as well as in another study, indicated that most students tended to avoid textbooks and opted for lecture slides, especially when preparing for exams [ 20 , 21 ].

Several researchers studied the association between different factors and academic performance; however, more is needed to know about this association in the process of education among medical students [ 15 , 20 , 22 ], with some limitations to the conducted studies. Such limitations include the study sample and using self-reported questionnaires, which may generate inaccurate results. Moreover, in Saudi Arabia in particular, the literature concerning the topic remains limited. Since many students are unsatisfied with their performance and seek improvement [ 10 ], the present study was designed and conducted.

Unlike other studies in the region, this study aims to investigate the relationship between study habits and personal factors and measure their influence on academic achievement. The results of this study could raise awareness regarding the effect of study habits and personal factors on students’ performance and would also guide them toward achieving academic success. The study also seeks to identify the factors that distinguish academically successful students from their peers.

Study design, setting, and participants

This observational cross-sectional study, which took place between June and December 2022, was conducted among students attending the College of Medicine at King Saud University (KSU), Riyadh, Saudi Arabia. Its targeted population included all male and female medical students (first to fifth years) attending KSU during the academic year 2021/2022. Whereas, students at other colleges and universities, those who failed to complete the questionnaire, interns (the students who already graduated), and those who were enrolled in the university’s preparatory year, were all excluded from the current study. The sample size was calculated based on a study conducted in 2015 by Lana Al Shawwa [ 15 ]. Using the sample size formula for a single proportion (0.79), the required sample size was 255 using a confidence interval of 95% and a margin of error of 5%. After adding a 20% margin to accommodate non-responses and incomplete responses, the calculated sample size required for this study was 306. However, our research team collected a total of 336 participants for this study to ensure complete representation.

Study instrument

The research team developed and used an electronic questionnaire. The rationale is that no standardized questionnaire measuring the study objectives was found in the literature. However, the questionnaire was tested on a pilot of 15 students to test its clarity and address any possible misconceptions and ambiguity. The study questionnaire was distributed randomly to this cohort, who were asked to fill out the questionnaire. The students reported a complete understanding of the questionnaire’s contents, so the same questionnaire was used without any modifications. The questionnaire, written in English, consisted of three parts. The first part included eleven questions about the socio-demographic status of the participants. The second part contained twenty-one questions examining personal factors such as sleep and caffeine consumption. The last part included twenty-one questions regarding students’ study habits. The questionnaire was constructed based on an ordinal Likert scale which had: strongly agree, agree, neutral, disagree, and strongly disagree as possible answers. The questionnaire was sent to participants through email and social media applications like Twitter and WhatsApp to increase the study response. An informed consent that clearly states the study’s purpose was taken from all participants at the beginning of the questionnaire. In addition, all participants were assured that the collected data would be anonymous and confidential. Each participant was represented by a code for the sole purpose of analyzing the data. Furthermore, no incentives or rewards were given to the participants for their participation.

Study variables

Socio-demographic information (such as age, gender, and academic year), and personal factors (such as motivation, sleeping status, caffeine consumption, and self-management) were the independent variables. Study habits such as attendance, individual versus group study, memorization techniques, revision, learning style, and strategies were also independent variables.

Academic achievement refers to a student’s success in gaining knowledge and understanding in various subjects, as well as the ability to apply that knowledge effectively [ 23 ]. It is a measure of the student’s progress throughout the educational journey, encompassing both academic achievements and personal growth [ 3 , 24 ]. Academic achievement is judged based on the student’s GPA or performance score. In this study, students’ GPA scores, awareness, and satisfaction regarding their academic performance were the dependent variables.

We divided the study sample into two groups based on the GPA. We considered students with high GPAs to be exposed (i.e. exposed to the study habits we are investigating), and students with low GPAs to be the control group. The purpose of this study was to determine why an exposed group of students gets high grades and what study factors they adopt. Based on this exposure (high achieving students), we concluded what methods they used to achieve higher grades. Those in the first group had a GPA greater or equal to 4.5 (out of 5), while those in the second group had a GPA less than 4.5. The students’ data were kept confidential and never used for any other purpose.

Data analysis

The data collected were analyzed by using IBM SPSS Statistical software for Windows version 24.0. Descriptive statistics such as frequency and percentage were used to describe the socio-demographic data in a tabular form. Furthermore, data for categorical variables, including different study habits, motivation factors, memorizing and revising factors, and lifestyle factors, were tabulated and analyzed using the odds ratio test. Finally, we calculated the odds ratio statistic and a p-value of 0.05 to report the statistical significance of our results.

Ethical approval and consent to Participate

Before conducting the study, the research team obtained the Ethics Committee Approval from the Institutional Review Board of the College of Medicine, KSU, Riyadh, Saudi Arabia (project No. E-22-7044). Participants’ agreement/consent to participate was guaranteed by choosing “agree” after reading the consent form at the beginning of the questionnaire. Participation was voluntary, and consent was obtained from all participants. The research team carried out all methods following relevant guidelines and regulations.

The total 336 medical students participated in the study. All participants completed the study questionnaire, and there were no missing or incomplete data, with all of them being able to participate. As shown in Table  1 9.3% of participants were between 18 and 20, 44.9% were between the ages of 21 and 22, and 35.8% were 23–28 years old. In the current study, 62.5% of the participants were males and 37.5% were females. The proportion of first-year students was 21.4%, 20.8% of second-year students, 20.8% of third-year students, 18.2% of fourth-year students, and 18.8% of fifth-year students, according to academic year levels. Regarding GPA scores, 36.9% scored 4.75-5 and 32.4% scored 4.5–4.74. 23.8% achieved 4-4.49, 6.5% achieved 3-3.99, and only 0.4% achieved 2.99 or less. Participants lived with their families in 94.6% of cases, with friends in 1.2% of cases, and alone in 4.2% of cases. For smoking habits, 86.3% did not smoke, 11% reported using vapes, 2.1% used cigarettes, and 0.6% used Shisha. 91.4% of the participants did not report any chronic illnesses; however, 8.6% did. In addition, 83% had no mental illness, 8.9% had anxiety, 6% had depression, and 2.1% reported other mental illnesses.

Table  2 shows motivational factors associated with academic performance. There was a clear difference in motivation factors between students with high and low achievement in the current study. Students with high GPAs were 1.67 times more motivated toward their careers (OR = 1.67, p  = 0.09) than those with low GPAs. Furthermore, significant differences were found between those students who had self-fulfillment or ambitions in life they had ~ 2 times higher (OR = 1.93, p  = 0.04) GPA scores than low GPA students. Exam results did not motivate exposed or high GPA students (46%) or control students with low GPA students (41%), but the current study showed test results had little impact on low achiever students (OR = 1.03, p  = 0.88). Furthermore, 72.6% of high achievers were satisfied with their academic performance, while only 41% of low achiever students were satisfied. Therefore, students who were satisfied with their academic performance had 1.6 times greater chances of a higher GPA (OR = 1.6, p  = 0.08). Students who get support and help from those around them are more likely to get high GPAs (OR = 1.1, p  = 0.73) than those who do not receive any support. When students reported feeling a sense of family responsibility, the odds (odds ratio) of their receiving higher grades were 1.15 times higher (OR = 1.15, p  = 0.6) compared to those who did not feel a sense of family responsibility. The p-value, which indicates the level of statistical significance, was 0.6.

Table  3 shows the study habits of higher achiever students and low achiever students. Most of the high-achieving students (79.0%) attended most of the lectures and had 1.6 times higher chances of getting higher grades (OR = 1.6, p  = 0.2) than those who did not attend regular lectures. The current study found that studying alone had no significant impact on academic achievement in either group. However, those students who had studied alone had lower GPAs (OR = 1.07, p  = 0.81). The current study findings reported 29.8% of students walk or stand while studying rather than sit, and they had 1.57 times higher GPA chances compared to students with lower GPAs (OR = 0.73, p  = 0.27). High achievers (54.0%) preferred studying early in the morning, and these students had higher chances of achieving good GPAs (OR = 1.3, p  = 0.28) than low achiever groups of students. The number of students with high achievement (39.5%) went through the lecture before the lesson was taught. These students had 1.08 times higher chances of achieving than low achiever groups of students. Furthermore, students who made a weekly study schedule had 1.3 times higher chances of being good academic achievers than those who did not (OR = 1.3, p  = 0.37). Additionally, high-achieving students paid closer attention to the lecturer (1.2 times higher). In addition, students with high GPAs spent more time studying when exam dates approached (OR = 1.3, p  = 0.58).

Table  4 demonstrates the relationship between memorizing and revising with high and low GPA students. It was found that high achiever students (58.9%) studied lectures daily and had 1.4 times higher chances of achieving high grades (OR = 1.4, p  = 0.16) than the other group. It was found that most of the high achievers (62.1%) skim the lecture beforehand before memorizing it, which led to 1.8 times higher chances of getting good grades in this exam (OR = 1.8, p  = 0.06). One regular activity reported by high GPA students (82.3%) was recalling what had just been memorized. For this recalling technique, we found a significant difference between low-achieving students (OR = 0.8, p  = 0.63) and high-achieving students (OR = 1.83, p  = 0.05). A high achiever student writes notes before speaking out for the memorizing method, which gives 1.2 times greater chances of getting high grades (OR = 1.2, p  = 0.55) than a student who does not write notes. A major difference in the current study was that high GPA achievers (70.2%) revise lectures more frequently than low GPA achievers (57.1%). They had 1.5 times more chances of getting high grades if they practiced and revised this method (OR = 1.5, p  = 0.13).

Table  5 illustrates the relationship between negative lifestyle factors and students’ academic performance. The current study found that students are less likely to get high exam grades when they smoke. Students who smoke cigarettes and those who vape are 1.14 and 1.07 times respectively more likely to have a decrease in GPA than those who do not smoke. Those students with chronic illnesses had 1.22 times higher chances of a downgrade in the exam (OR = 1.22, p  = 0.49). Additionally, students with high GPAs had higher mental pressures (Anxiety = 1.2, Depression = 1.18, and other mental pressures = 1.57) than those with low GPAs.

Learning is a multifaceted process that evolves throughout our lifetimes. The leading indicator that sets students apart is their academic achievement. Hence, it is crucial to investigate the factors that influence it. The present study examined the relationship between different study habits, personal characteristics, and academic achievement among medical students. In medical education, and more so in Saudi Arabia, there needs to be more understanding regarding such vital aspects.

Regarding motivational factors, the present study found some differences between high and low achievers. Students with high GPA scores were more motivated toward their future careers (OR = 1.67, p  = 0.09). The study also indicated that students who had ambitions and sought self-fulfillment were more likely to have high GPA scores, which were statistically significant (OR = 1.93, p  = 0.04). This was consistent with Bin Abdulrahman et al. [ 20 ], who indicated that the highest motivation was self-fulfillment and satisfying family dreams, followed by a high educational level, aspirations to join a high-quality residency program, and high income. Their study also found that few students were motivated by the desire to be regarded as unique students. We hypothesize that this probably goes back to human nature, where a highly rewarding incentive becomes the driving force of our work. Hence, schools should utilize this finding in exploring ways to enhance students’ motivation toward learning.

The present study did not find a significant effect of previous exam results on academic performance (OR = 1.03, p  = 0.88). However, some studies reported that more than half of the high-achieving students admitted that high scores acquired on previous assessments are an important motivational factor [ 15 , 25 , 26 ]. We hypothesize that as students score higher marks, they become pleased and feel confident with their study approach. This finding shows how positive measurable results influence the students’ mentality.

The present study also explored the social environment surrounding medical students. The results indicated that those who were supported by their friends or family were slightly more likely to score higher GPAs (OR = 1.1, p  = 0.73); however, the results did not reach a statistical significance. We hypothesize that a supportive and understanding environment would push the students to be patient and look for a brighter future. Our study results were consistent with previous published studies, which showed an association [ 3 , 27 , 28 , 29 , 30 ]. We hypothesize that students who spend most of their time with their families had less time to study, which made their study time more valuable. The findings of this study will hopefully raise awareness concerning the precious time that students have each day.

The association of different study habits among medical students with high and low GPAs was also studied in our study. It was noted that the high-achieving students try to attend their lectures compared to the lower achievers. This was in line with the previous published studies, which showed that significant differences were observed between the two groups regarding the attendance of lectures, tutorials, practical sessions, and clinical teachings [ 31 , 32 ]. The present study found that most students prefer to study alone, regardless of their level of academic achievement (82.1%). This finding is consistent with the study by Khalid A Bin Abdulrahman et al., which also showed that most students, regardless of their GPA, favored studying alone [ 20 ].

The present study findings suggest that a small number of students (29.8%) prefer to walk or stand while studying rather than sit, with most being high achievers (OR = 1.57, P  = 0.15). A study reported that 40.3% of students with high GPAs seemed to favor a certain posture or body position, such as sitting or lying on the floor [ 15 ]. These contradictory findings might indicate that which position to adopt while studying should come down to personal preference and what feels most comfortable to each student. The present study also found that high achievers are more likely to prefer studying early in the morning (OR = 1.3, P  = 0.28). The authors did not find similar studies investigating this same association in the literature. However, mornings might allow for more focused studying with fewer distractions, which has been shown to be associated with higher achievement in medical students [ 3 , 15 , 33 ].

Our study also found that 39.5% of the academically successful students reviewed pre-work or went through the material before they were taught it (OR = 1.08, p  = 0.75), and 25% were neutral. Similar findings were reported in other studies, showing that academically successful students prepared themselves by doing their pre-work, watching videos, and revising slides [ 3 , 9 , 34 ]. Our study showed that 75% of high-achieving students tend to listen attentively to the lecturer (OR = 1.2, p  = 0.48). Al Shawa et al. found no significant differences between the high achievers and low achievers when talking about attending lectures [ 15 ]. This could be due to the quality of teachers and the environment of the college or university.

Regarding the relationship between memorizing and revising with high and low GPA students, the present study found that students who study lectures daily are more likely to score higher than those who do not (OR = 1.4, p  = 0.16). This finding is consistent with other studies [ 3 , 19 , 35 ]. For skimming lectures beforehand, an appreciable agreement was noted by high GPA students (62.1%), while only (42%) of low GPA students agreed to it. Similarly, previous published studies also found that highlighting and reading the content before memorization were both common among high-achieving students [ 15 , 36 ]. Furthermore, the present study has found recalling what has just been memorized to be statistically significantly associated with high GPA students (OR = 1.83, p  = 0.05). Interestingly, we could not find any study that investigated this as an important factor, which could be justified by the high specificity of this question. Besides, when it comes to writing down/speaking out what has just been memorized, our study has found no recognizable differences between high-achieving students (75%) and low-achieving students (69%), as both categories had remarkably high percentages of reading and writing while studying.

The present study has found no statistical significance between regularly revising the lectures and high GPA ( p  > 0.05), unlike the study conducted by Deborah A. Sleight et al. [ 37 ]. The difference in findings between our study and Deborah A. Sleight et al. might be due to a limitation of our study, namely the similar backgrounds of our participants. Another explanation could be related to curricular differences between the institutions where the two studies were conducted. Moreover, a statistically significant correlation between not preferring the data being presented in a written form instead of a graphical form and high GPA scores have been found in their study ( p  < 0.05). However, a study conducted by Deborah A. Sleight et al. indicated that 66% of high achievers used notes prepared by other classmates compared to 84% of low achievers. Moreover, their study showed that only 59% of high achievers used tables and graphs prepared by others compared to 92% of low achievers. About 63% and 61% of the students in their study reported using self-made study aids for revision and memory aids, respectively [ 37 ].

The present study also examined the effects of smoking and chronic and mental illness, but found no statistical significance; the majority of both groups responded by denying these factors’ presence in their life. A similar finding by Al Shawwa et al. showed no statistical significance of smoking and caffeine consumption between low GPA and high GPA students [ 15 ]. We hypothesize that our findings occurred due to the study’s broad approach to examining such factors rather than delving deeper into them.

High-achieving students’ habits and factors contributing to their academic achievement were explored in the present study. High-achieving students were found to be more motivated and socially supported than their peers. Moreover, students who attended lectures, concentrated during lectures, studied early in the morning, prepared their weekly schedule, and studied more when exams approached were more likely to have high GPA scores. Studying techniques, including skimming before memorizing, writing what was memorized, active recall, and consistent revision, were adopted by high-achievers. To gain deeper insight into students’ strategies, it is recommended that qualitative semi-structured interviews be conducted to understand what distinguishes high-achieving students from their peers. Future studies should also explore differences between public and private university students. Additionally, further research is needed to confirm this study’s findings and provide guidance to all students. Future studies should collect a larger sample size from a variety of universities in order to increase generalizability.

Limitations and recommendations

The present study has some limitations. All the study’s findings indicated possible associations rather than causation; hence, the reader should approach the results of this study with caution. We recommend in-depth longitudinal studies to provide more insight into the different study habits and their impact on academic performance. Another limitation is that the research team created a self-reported questionnaire to address the study objectives, which carries a potential risk of bias. Hence, we recommend conducting interviews and having personal encounters with the study’s participants to reduce the risk of bias and better understand how different factors affect their academic achievement. A third limitation is that the research team only used the GPA scores as indicators of academic achievement. We recommend conducting other studies and investigating factors that cannot be solely reflected by the GPA, such as the student’s clinical performance and skills. Lastly, all participants included in the study share one background and live in the same environment. Therefore, the study’s findings do not necessarily apply to students who do not belong to such a geographic area and point in time. We recommend that future studies consider the sociodemographic and socioeconomic variations that exist among the universities in Saudi Arabia.

Availability of data materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Grade Point Average

King Saud University

Institutional review board

Statistical package for the social sciences

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Aljaffer, M.A., Almadani, A.H., AlDughaither, A.S. et al. The impact of study habits and personal factors on the academic achievement performances of medical students. BMC Med Educ 24 , 888 (2024). https://doi.org/10.1186/s12909-024-05889-y

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