Publishing Research in Obesity Journals

Description

This 1-hour webinar was developed specifically for early career obesity researchers and included expert guidance on the processes involved in publishing manuscripts in high-impact journals. Led by Professor David Stensel, Editor-in-Chief of the International Journal of Obesity (IJO) and Professor of Exercise Metabolism at Loughborough University, UK, and Waseda University, Japan, attendees gained insights into strategies for manuscript publication, peer review processes, and practical tips to enhance manuscript quality. The webinar was hosted by EASO ECN board members and included an active question and answer session with Professor Stensel. More information here: https://easoarchive.easo.org/publishing-research-in-obesity-journals/

Transcript

Transcripts are auto generated, if you spot an error, please email enquiries@easo.org

And we'll just get going in the interest of time. So thank you all so much for attending this afternoon and joining. My name is Niamh Arthurs.

I'm one of the board members from the European Association for the Study of Obesity's Early Career Network, and I'm also a senior paediatric dietician and researcher in child and adolescent obesity, and I'm based in Dublin in Ireland. And I may have had the pleasure of meeting some of you at the European Congress for Obesity last year, which we hosted in Dublin, and I look forward to hopefully meeting some of you in May in Venice at the very first European Congress on obesity. And if you are going to Venice in May to Eco 2024, please let us know in the chat so we can make sure that we look out for you, and hopefully we can meet up and have a chance to chat in person at Eco in Venice in a month, one month to go.

So you're all very welcome to today's EASO Early Career Network eLearning Hub, and the event title for today is Publishing in Obesity Journals. This webinar series is supported by an unrestricted educational grant from Boeing or Eichelheim. And just to remind you that today's event will be recorded, so please feel free to pop back and watch it again, and please definitely feel free to share the recording of this event and encourage as many as you can to join the Early Career Network, and they have full free access to all of these resources, and also to things like grants, travel grants, and to be able to go to congresses such as Eco and others related in the field.

So we've lots to gain from being a part of this network in addition to our schools, so our winter school, and also masterclasses and other resources. So I just want to introduce some house rules for this webinar today. It's quite informal, so you can ask questions either by raising a virtual hand at the end of the talk, and feel free to ask your question orally, or you may pop your question into the chat box as you're going along, but we will keep questions and answers to the end of our fabulous speaker's presentation.

And there'll also be a feedback form at the end of the webinar, and we'd greatly appreciate if you could please complete this feedback form as soon as you can, just while it's fresh in your head, because this helps us to inform and plan future events, and that's really, really important to know what topics that you might suggest that we could present and cover in future e-learning series webinars. This is the last e-learning series of this semester, so the next e-learning series webinar will be in September, but all of our previous webinars have been recorded and are available on the EASO YouTube channel. And finally, I'm just going to hand you over to Lisa to introduce a few links and a few other helpful things to save and go back to maybe at another time.

Thanks, Niamh. Hi everyone, my name is Lisa. I'm just going to quickly run through some important dates that are of interest to Early Career Network members.

If you are joining us at ECO 2024, which is the 12th to the 15th of May, there are a few sessions that you might want to look out for. We have the ECN Best Thesis Award session, which is on Monday the 13th. You're specifically invited to come along and join this, because this is a competition for ECN members.

We've already got the top three finalists, and in this session we will select the winner. So please do come along to that one and show some support for the top three, and also meet other ECN colleagues. We also have an ECN lounge at the Congress, so there's going to be a specific area where ECN people can come along and use as a kind of open area for meeting others, and you can also eat your lunch in this area.

Throughout the Congress, we're going to have a kind of informal session to meet others on the 12th of May. Then on the 13th, we're going to have a networking workshop where we'll have kind of more structured ways to meet other people and other researchers. And then on Tuesday, we're going to have some interviews with researchers and also representatives of ECPO, and they're going to be on the importance of networking.

I think that's it for me for now. Like Niamh said, this is the last webinar of the session. Please keep an eye out for the 2024 to 2025 schedule, which is going to kick off in September of this year coming.

And if you haven't yet registered for EECL, but you would like to come, please do register using the link that I'm going to send you in the chat. And standard rate registration is open until the 26th of April, so you've got a few days to get that sorted. That's it.

I'll hand over to Niamh and looking forward to David's session. Brilliant. Thank you so much, Theresa.

It's a great pleasure to welcome on behalf of the ECN board, Professor David Stinsell, who is the co-editor-in-chief of the International Journal of Obesity and Professor of Exercise and Metabolism in both the School of Sport, Exercise and Health Sciences at Loughborough University in the UK, and also the Faculty of Sport Sciences at Waseda University, Japan. And I hope, did I pronounce that right, David? Correct. Brilliant.

So I'm going to hand over to David if you'd like to share your screen and get going. Thanks so much, everyone. Enjoy.

Okay, thank you for that introduction. Can you just confirm that my screen is showing properly? Yeah, I can see it full screen. Thanks, David.

Perfect. So thank you, Lisa and Niamh, for your very warm and kind invitation. It's a pleasure to be here.

So I'm going to speak, aim to finish at about quarter to five, so speak for about 40 minutes and leave time for questions, as Lisa and Niamh said at the start. So title of the talk, Publishing Research in Obesity Journals. I'm going to cover five main things here.

So I'm going to talk about the research publication process, and I'm going to do this, I guess, mostly through my experiences over 10 years of involvement with the International Journal of Obesity. I guess I have experience over 30 years now of actually trying to publish papers, some of which were relevant to the field of obesity, not all. So I'm going to talk about what it's like to be on the other side of the fence, I guess, as an editor and reviewer.

And then I'm going to talk about a bit about manuscript preparation before you submit it. But I was also asked to talk about writing tips. So I'm going to spend quite a bit of time talking on that topic, components of writing abstracts, introductions, et cetera, other components of papers, and then towards the end, rebuttal letters and reviewing research papers, which hopefully many of you will get involved with in your career.

So starting then with the research publication process, which as this cartoon indicates, particularly when you've not been through it before, or not been through it frequently, can seem a rather perilous sort of process. And I know certainly the first one or two papers that I submitted as a PhD student, I couldn't believe the, I guess one word for it would be apparent bureaucracy, but it's all part of the rigour. So I'm doing this largely now what I'm about to go through from my experience, as I've mentioned at the start with the International Journal of Obesity.

So this is one of many obesity journals, and I'm not sanctioning this as, you know, I'm speaking about my experiences with this journal, but not leading you specifically to this journal. There are many different obesity journals, all with good reasons to submit to them, but they're big endeavours, journals are big endeavours. So you can see here we have, this journal is the publisher is Springer Nature, and there's a large administrative team that I liaise with on a weekly basis, as well as with my co-editor in chief, Professor Nicol Durandahar in the States.

And then we have eight associate editors with varying experiences in different areas, including paediatrics and statistics, approximately 80 editorial board members. And one of the reasons when we look at why review at the end, one of the reasons for reviewing is if you do that frequently, you could get invited to be an editorial board member of a journal, which can be a good experience. And then we have approximately close to 1000 academic reviewers per year, typically academics working in the field.

So what I'm going to do on this slide is go through the process of what happens to your papers when they're submitted to the journal. This is relevant, I think, for practically every journal I can think of, but this I'm going through very specifically for IJO here. So the authors submit the manuscript includes their files, their cover letter, and any reviewer suggestions that they have and might get questions on this, we do actually take up reviewer suggestions very often, we would not send the paper only to the reviewers that have been suggested by the authors.

But we will often look at reviewers that have been suggested. Authors might be surprised that many times the people they've suggested to review the paper will decline to review it for one reason or another. But we do take those up.

Your paper firstly will be seen by the administrative team at Springer Nature. And so they will check the formatting, we'll do plagiarism checks, we have a tool called cross check, which will give us an immediate percentage overlap between your paper and any paper that's out there already published or in a preprint server as well. Sometimes those can be as high as 40, 50, 60%.

And we will look at those very carefully when there is such a high overlap. But it's not always for any bad reasons. For example, you typically can get a lot of overlap with methodologies and referencing and so on.

So if it's incorrectly formatted, it goes back to the authors with specific comments as to what needs changing, and then it gets resubmitted. And then it first lands after that the Springer Nature team will assign that to one of our associate editors, who will look at the paper and make a decision of whether to send that paper out to review. And typically about a third of the papers submitted to the journal go out for review, or whether to reject it without review.

And unfortunately, if it's rejected without review, the authors don't get any feedback on that. They just simply get a message that we regret to inform you that an editorial decision was made, that the manuscript didn't achieve sufficient priority rating. I'll say a bit more about the reasons for this.

But one of the key reasons actually is just simply the volume of papers that are submitted to the journal. I mean, in heavy years, we get something like 130 papers a month. So that's very challenging to deal with.

And if we think the chances of success through peer review are not high, as a courtesy to the authors, we want to get it back to them quickly, rather than making the authors wait months to get what we think might be the same decision. The authors don't get that decision before it's checked by an editor-in-chief, either myself or Nicol. So two people will see the paper before that decision.

If we do decide to reject without sending the paper to review, it will have been seen by an associate editor and an editor-in-chief. So at least two people will have made that decision jointly. And considerations will be about the scope of the paper.

Is it relevant to the journal? We do get some papers that are quite peripheral. Is it a priority, even if it is relevant? And then obviously the quality, the quality of the research in it, and also the quality of the writing. So once the editor-in-chief has confirmed the decision of the associate editor, and it's occasionally we will go back to the associate editor and say, I can't see why you don't want to send this out.

And we will discuss that. And subsequently, the associate editor may make their reasons more clear, in which case the editor-in-chief might agree. Or the associate editor in discussion may change their mind, and we may send that out.

But usually we're consistent. So that goes back to the admin team, and the admin team feed that decision back to the authors, if it's a reject without review. We aim to do that, if we do reject without review, we aim to do that within a week.

And now that doesn't always happen, because obviously you've got admin staff having to assign papers, you've got an associate editor having to make a decision, then an editor-in-chief, and then back to the admin team. So there's four sort of points in the chain there. Sometimes people are traveling, sometimes people are unwell, and so on and so forth.

So we do often get back to authors within a week, but sometimes it's longer. Hopefully, you don't get rejected without review, hopefully your paper goes out for review. So in that scenario, about 33% of papers, we then have probably the most challenging aspect of the peer review process is A, finding suitable reviewers who have experience in the area, and then B, getting those reviewers to actually accept the invite to review.

And I can share with you that say, if we're lucky, we might identify five or six reviewers, and we get two of those five or six that agree to review. But there are cases where it's really, really challenging. I mean, I've had cases where we've made 40 invites and not a single person has accepted the invite to review a paper, a particular paper.

So you can see why sometimes it takes, well, weeks or months even for us to process the paper. We do try to call on editorial board members where paper's been in the system for a long time, or even do a formal review ourselves. But obviously, we've got a limited capacity to do that.

So we aim to get a two-week turnaround, but often we fail in that aim. Once it's been reviewed, and you may not be able to see all of this, and as an author, you won't see this table, but here you can see this is reviewer one and reviewer two here. In this particular case, they make a recommendation.

In this case, their recommendation is major revision. So what the options that the reviewers have is to accept the paper, that'd be very rare, to accept without any revision, to reject the paper, to ask for major revisions, or to ask for minor revisions. And you can see some headings here.

You might not be able to make these out, but the reviewers are asked things like, is the paper within scope? Is the abstract adequate? Are the results novel? Have the authors confused correlation with causation? A particular problem with cross-sectional studies and observational studies, where the writing in the paper is saying that X causes Y, where they can't say that. They can only say that X is associated with Y. And are there concerns about the statistical analysis? If there are, we then need to identify a third statistical reviewer, and that will slow the process further. But we do do that, you know, if there are concerns.

Are the results important? So that, you know, the results might be valid, but we might not think they're particularly important. So the reviewers are asked that. And then they're asked questions about the references.

Is it worth highlighting in an editorial? And we try to commission editorials on papers if we think so. And very important, another aspect that the authors don't see is a rating. How would you rank this paper? So I don't know if you can make out this column here, but how would you rank it? We have a ranking.

Is it the top 10%, top 25, top 50, or bottom 50? We don't typically share this information. From experience, we can get into tremendous lengthy discussions with disgruntled authors who say it's not the bottom 50, it's the top 50, or the top 25, or the top 10. We don't have the capacity to enter into those sort of negotiations with the authors.

So this information is useful, and we get some confidential comments as well. But to reassure authors, we don't take everything the reviewers say at face value. So we understand that reviewers have their biases, we get good reviews, and we get bad reviews, we get comprehensive reviews, and we get limited reviews as well.

So the reviewers' comments and ratings are only one thing that we consider. We also consider, we look through the paper ourselves as editors and associate editors, and as editor-in-chief, I consider the comments of the associate editors. So the associate editor looks at the reviewer ratings, and then the associate editor decides whether to make a reject or a revise decision.

And that decision comes to the editor-in-chief, who then ratifies the decision and passes that to the admin team, who pass that back to the authors. So in the case where your paper has been out for review, there's four people that have had an impact on the decision. The two reviewers, occasionally three if we send it to statistical review, and the associate editor and editor-in-chief.

And the holy grail would be a manuscript, for authors, would be to get their manuscript accepted without any revisions. I would tell you that's very occasional. It's very rare for that to happen.

It does occasionally happen. But more usually, the authors are asked to revise their paper and then resubmit it, and it goes through the same process again. So it goes back to the original reviewers, and the original reviewers then review the revised edition.

In most cases, one revision is enough. Sometimes the one or both of the reviewers will want a second revision. And rarely does it go beyond that.

There are occasions where the revision won't be deemed to be adequate, and then it will be rejected. I've shown some stats in a minute that will show if you do get invited to review the paper, you've got about a 50% chance of subsequently getting it accepted. So this same table is filled out again, and we go through the same process, associate editor, after the reviewers, associate editor, editor-in-chief, admin team, feeding back to the authors.

So as I say, sometimes that even after the review, the paper will then be rejected. It's made jointly by the associate editor and the editor-in-chief, that decision. The reviewer comments are considered, but they don't provide the verdict.

We occasionally, not often, but occasionally we'll have appeals, and the authors think we've just taken everything that the reviewers have said at face value. That is not the case. I can sometimes tell that a reviewer has been very fair, very balanced, and I can sometimes tell that a reviewer seems to have been overly critical, and so I won't then take all of those comments at face value, and if the reviewers sometimes made a comment that I feel was unreasonable, I will do a bit of extra homework to check whether what they've said is valid.

We don't share confidential reviewer comments with the authors. Again, it potentially will upset the authors. I mean, the confidential comments are very rarely things that we couldn't share.

They're very rarely cutting. Occasionally, we will get some confidential comments that will say that I've seen this paper submitted to other journals and so on, or it's a plagiarized paper, and we will follow up then and do due process for that, but normally the confidential comments are sort of fairly harmless, but just give us a bit extra context, and our decision to reject would be about the overall rank, the importance of the results, the novelty of the scope. We sometimes reject papers.

There's nothing actually wrong with the paper. It's just somewhat confirmatory. I mean, all research to some degree is confirmatory, but we've just made a decision that although there's nothing particularly wrong with it, it's not high enough impact.

We sometimes make mistakes. We do reject papers that go on to get accepted in other journals and cited well, and the holy grail is not to do that, is to select the papers that are going to be most impactful and most highly cited, but it's not a perfect process. Common reasons for rejection, lack of novelty, and an incremental increase in knowledge.

I mean, that's true of most research, my own included, but it's a matter of how much is the increment. Could be a problem with the methodology. I'm not saying questionnaire studies are bad, but for example, if I give an example of my own work, which looks at physical activity, we would really expect some objective, what we call objective device-assisted measures now, with accelerometry, for example, to supplement questionnaire-based work.

Self-reported data, observational and cross-sectional findings. By far, the majority of the work submitted to the journal is of that nature. So, if you have that kind of work, it's fine, but it needs to be really strong methodologically or sample size or the angle that it's taking.

Intervention studies that are bespoke to obesity, we really like these studies, but ideally we want, you know, reasonably long studies. I think there's information on the website recommending an hour, sorry, recommending a year, but we will look at shorter studies if they're novel. And then aspects of clarity and presentation and fit to the journal.

So, there are some statistics there. We're typically having a thousand papers submitted a year at the moment, but there are some years where it's over 1,600, about 130 a month. Overall acceptance rate varies year on year, but about 20%.

So, we have 60% rejected without review, and of the 40% that are reviewed, about 50% of those are rejected. And timelines there are about one to four weeks for first decision, but sometimes it does take longer if we have difficulties finding reviewers. And submission to acceptance two to four months, again, sometimes it does take a bit longer.

So, that is a quick overview of the publication process from the inside, at least with the International Journal of Obesity. I'm going to talk now a bit about manuscript preparation, and I guess state the obvious, but it's obvious to me when I read papers that many people either haven't read the guidelines to authors, or they've read them and often ignored them or ignored sections of them. So, my recommendation, regardless of where you're submitting, is read the guidelines to authors.

If it's IJO, you can find this web link here. And adhere to them. Formatting, word length, font size, otherwise it delays the process.

If it's over length, or if you haven't adhered to key formatting guidelines, these aren't all of them here, just a couple of examples, then it's going to be sent back to you, or likely to be sent back to you. Important about page and line numbers. I think actually these, if you haven't got line numbers, I think they sometimes make it through the system, but they're really helpful to reviewers when reviewers are wanting to highlight or recommend bits of the manuscript that they want changes in.

It's useful if they can cite the page and line numbers. We at IJO, we ask you to use SI units, but again, papers do get through the system without using SI units, but it's really helpful if you do adhere to that. I try to pick up on that if reviewers and associate editors haven't.

Abbreviations. This is a plea to use abbreviations sparingly. You may well be familiar with the abbreviations you're using, but they really can confuse authors that are unfamiliar with the abbreviations.

Sorry, readers, not authors, which is most people reading your manuscript won't necessarily be familiar with the abbreviations. At IJO, we say don't use abbreviations if you're not using the term more than four times. I would say use them for lengthy words.

As an example, non-esterified fatty acids, four words, you abbreviate as NEFA, N-E-F-A, and if you're using that term frequently, fine, then abbreviate it. But often we get papers littered with abbreviations, they're not always defined, and it just confuses readers. We're also asking authors to use people-friendly language.

I'm not going to say a lot about this. We had a presentation on this with this format a month or so ago, but we're using appropriate language, people with obesity, rather than talking about obese people, for example. There's more to it than just that, but we're asking you to adhere to that.

We're now starting to send papers back to authors before they're assessed if they haven't used this language. Another issue is sex versus gender. I think mostly authors mean sex, but they're often using the term gender, and those two are different things.

I'm not going to go into detail now, but think about that when you're submitting your papers. Know what the paper should look like. Often there are guidelines for things like randomized trials, consort guidelines, observational studies, strobe guidelines, systematic reviews, and meta-analysis, PRISMA guidelines.

We will say on the journal website, or other journals should say the same, which guidelines they are wanting you to adhere to, or journals will often tell you that. Often there are templates for you to complete and submit with your journal manuscript, so look out for those. I'm not going to say a lot about AI.

This is what's on the IJO website, and you can read that yourselves, but suffice to say we do not consider CHAT-GBT to satisfy our authorship criteria. There is a bit more information on the Springer Nature website about AI, but if you're going to use AI at all, you need to reference carefully how you've done that, and how it's been used in the methodology section, if there is a methodology section in the type of paper you're submitting, or if not, another suitable part of the paper. So just be careful with AI.

Look at the journal website for IJO or another journal, and what is permitted and what's not permitted in terms of AI. We are getting papers submitted about the use of AI in research, and some very interesting papers there. For example, recently a paper that used AI to prescribe diets and compare how well AI was doing the dietary prescription compared with five qualified dietitians, and how well those things compared.

For some conditions, diseases, the AI did very well, and for others, less well. So it's a very topical and interesting thing, but be careful in how you use AI if you're using it to write your papers, and we don't consider AI to have authorship criteria. Okay, I'm going to move on to the third part of my talk now, which is tips for writing papers.

I'm aware that the audience may have varying levels of experience with this, so I'll go through sort of fairly basics here. So to start with, there are a lot of resources out there, and I'm sure other journals have resources. IJO, Springer Nature, they have author tutorials on writing a journal manuscript, and these you have to register, but I believe the tutorials are free, you don't need to pay.

Also, if you're not a native English speaker, Springer Nature offer a tutorial in writing in English. So there's good resources out there with Springer Nature and other publishers that you can use. When I was a PhD student, I used this book, How to Write and Publish a Scientific Paper.

I don't know if they're on the 8th edition, and now this is the 8th edition that was published in 2016. I think that might be free online now, so if you're new or relative novice to this process, that book is really helpful. They have chapters on how to write an introduction, a methodology, so on and so forth, and many other things, how to write grant applications, etc.

There are also papers that are written. I mean, this is one example, I'm just giving this to you as an example, Writing the Title and Abstract for a Research Paper. So there are whole papers you can find just on that topic, and some of these can be really, really useful.

So I'm going to go through these sections, slide by slide, relatively quickly, just to give you some pointers. So recognize that the title is probably going to be the most read part of your paper. Might be read by thousands of people.

You'll be lucky if thousands of people read your paper. Might be used to categorize or index your paper, so just be aware of that. So all words should be chosen with great care.

Question, what is a good title? Answer, the fewest possible words that adequately describe the contents of your paper. I once heard that the most brief title was E equals MC squared. I'm not sure whether that is a title of a paper, but I've been told that story.

Avoid waste words. So an investigation of the effects of should just simply be the effects of, you know. Avoid abbreviations in titles.

There might be exceptions. I'm not sure, for example, if MRI, commonly accepted abbreviation for magnetic resonance imaging, you know, there might be some permissible times, but generally avoid abbreviations in titles. You do get titles that tell you the key finding in the title.

So here's an example. No effect to vitamin C supplementation on cold symptoms. So you know, reading the title, what that paper is going to tell you.

Those are called assertive sentence titles. I don't think IJO has got a stance on those. Some people don't like them.

Some scientists think that readers should be left to make their own mind up about the conclusion of a study after reading the study, but some people like to use these. And often you'll be asked as an author to give a short title, which is used at the top of each page. A very brief short title.

So that's titles. Abstracts, usually the first part of the paper to be read, obviously after the title. And if the abstract is poorly written, and I can tell you this as a reviewer, you know, you very quickly lose interest if the abstract is poorly written.

IJO, we request a structured abstract, which means you've got an introduction, a methods, a results, and a conclusion or summary. Ideally, I would recommend, we don't mandate it, that you include some data in the abstract. You can't obviously include all the data, but some data.

There shouldn't be anything in the abstract. So data or a conclusion that isn't included in the paper. So do make sure you're not saying something in the abstract, which is not mentioned anywhere else.

Again, I would avoid abbreviations. You can use them in the abstract. And sometimes, if you're frequently repeating a term, you use it.

But do be aware that copious use of abbreviations inhibits readability of your work. A good abstract is usually followed by a good paper and vice versa. And I can usually tell, having read the abstract, whether the paper is going to be suitable.

I don't approve this, but some reviewers will only read the abstract. And even one of my associate editors once said they only read the abstract, which I was disappointed before they make that decision about whether to send out the review or not. But it is really, really important, the abstract.

Okay, so I'm moving on to the introduction. Start with brief background, nature and scope. Why is the area important? Very brief literature review with up-to-date references.

What's the gap in the literature? What's the rationale for your study? What's the purpose of your study? We don't always see hypotheses stated, but you can do. Please cite literature carefully. Some analysis was done, which said sort of quite a high proportion of citations.

The paper isn't actually showing what the authors have said it's showing. So we want primary referencing, referencing primary source papers, not secondary referencing. So if you want to make a specific point, ideally, you're not using a review paper to make that point.

You're using the original source. And you can think of the introduction as a funnel shape. You start broad, and you end up narrow.

And I'll say this, when we look at the discussion, it's the opposite. For the discussion, you start narrow, and you end up broad at the end. The take-home message of the paper broadens out to the wider area.

And we write introductions in present tense. Moving on to the methods. Obviously, they need to be sufficient that the experiment can be repeated.

Be consistent with headings and subheadings. We sometimes get, you know, different formats for different, for the same, the same level of heading in different formats, and so on. So be consistent with those.

And abbreviation. So a couple of trivial examples, but liter, is it a capital, or is it a lowercase l, or is it hr, or just h? You often find inconsistencies in the use of abbreviations in papers. Many readers will skip this section, but not good reviewers.

So you need to be detailed with it, and careful. Actually, I don't know why I put this about spellchecking. This applies to the whole paper, not just the methods.

But spellcheckers don't always, they won't pick up, for example, from versus form, and other words like that. So you need to proofread carefully. And methods are usually written in past tense.

So, obviously, you're including participant characteristics. But things we don't always see, how did you recruit the participants? We do want to see statements about informed consent and ethical approval. I'm actually, just last week, we rejected, sorry, we retracted a paper that was published before my involvement with the journal, where it was called out for not having appropriate ethical approval.

This was a paper published, I think, 15 years ago. And it was called out, and they didn't have appropriate ethical approval in place. So we do look at that at the time of review, but some have obviously, in the past, slipped through the system.

If it's a clinical trial, is it registered? And give us the details. If it's a systematic review, Prospero details. And if appropriate, a protocol diagram is really helpful.

Statistical analysis, obviously, you'll know that you need a statistical analysis section. But things like sample size calculations, how you're displaying the data, how are you dealing with missing data? We don't often get authors explaining that, but most research has missing data. How do you deal with outliers? And what's your definition of an outlier? What software are you using? And this just, you know, this might be, you might think this is a trivial example, but better to write just two extra words, ultrasonic treatment, cells were broken down by ultrasonic treatment, then cells were broken down as previously described.

So in the former case, I actually know what method you're using. I don't know that in the latter case, I've got to go to the paper to find the method. So just a little bit of care with two or three words can make a huge difference across the whole paper.

So moving on to the results, obviously, that's the core of the paper. You want to use representative data. So you don't have to use all of the data that you've got.

Your job as the author is to show us, the readers, representative data. You're not cherry picking here. You are displaying the most important data, but it must be representative.

If you've got lots of extra data that you think is important, you can include that as supplementary material. Obviously, you want to strive for clarity. Don't include interpretive comments in the results section, leave those for the discussion.

And don't include data in the text if you're presenting it in figures and tables and vice versa. You don't need to duplicate there. And finally, you're writing the results in past tense.

Make good use of tables and figures. Journals will have their guidelines about how many you're allowed to use. But you know the term, a picture paints a thousand words.

So think carefully about how to present the data and do use those. As I've already mentioned about duplicating, don't duplicate data in tables in a figure and vice versa. You can use multi-panel figures to maximise your data presentation if you want to, if you've got a lot of data to present that you think all needs to be seen.

You should make sure that every figure and table is cited in the text. And you should include clear figure and table legends that ideally stand on their own so that the reader can read the figure or table legend without reference to the text and have a reasonable understanding of what the figure or table is conveying. And things like presentation, font size being large enough and including units etc.

As I said, design the figures and tables to be understandable without the text. So I'm running out of time a little bit. I'm going to hopefully try and wrap this up within another five minutes now.

So write in the discussion, briefly summarise the key findings, show how the results and interpretations agree or contrast with previously published work. Don't stray too far from your own data. We don't want long descriptions of a mechanistic explanation for your findings if you haven't actually addressed those mechanisms in your paper.

So stick largely to your own data, make brief mention to other relevant data to explain mechanisms but not long detailed explanations. Point out exceptions or lack of correlation. Don't cover up data that you've got that doesn't quite fit.

Be open about that. It's important to have that out there. Discuss the theoretical implications, practical applications and conclusions as clearly as possible but don't overstate your conclusions.

Keep them within what you can conclude from your own data. And ideally the so what question. So you found this, so what, who cares, what are the implications of your finding or what might the implications be.

The introduction and the discussion, I think I mentioned this at the start, they're like a pair. So after your introduction the discussion should ideally refer back and answer the questions posed in the introduction. So as I said the introduction was like a funnel shape, the discussion is an inverted funnel.

You might start by sharing your key findings but as you go through the discussion you end up with a broader picture. You often include strengths and limitations in the discussion, usually towards the end of the discussion and you might want suggestions for future research although if you've got a really good future research question you might want to keep that for your next study and you might be reluctant to share that. And there's a couple of quotes here from the book by Garcel and Day about discussions which I'm not going to read to you but you know quite helpful about how to view a discussion.

So that last bit about you in the intro you invited the reader into your research venue after the discussion you usher them out being well informed about your research. There are some, these are just a few examples but think carefully about your language. These are some examples of long-winded terms and preferred.

So I mean I was taught this when I was doing my PhD by my PhD supervisor. You get a number of, you still see that everywhere even on the BBC, you know, if it's a number of you either mean many or you mean some probably. So just use one word instead of three.

A majority of, that's most. A small number of, that's few. Accounted for by the fact that it's just because, you know.

So these are some nice examples here where you can just be really concise with your language and it does make a difference across the whole paper. So just think carefully when you write. It's like, you know, be a craftsman skilling your wordsmith in your paper.

I'm not going to spend too long on this because I want to leave some time for questions but we don't need a three-page cover letter and we don't need the abstract copied into the cover letter. We very briefly need to be convinced why should your paper be sent out for review. So just the key finding highlighted in there in a cover letter.

I would say often a page is enough for a cover letter. Possibly a bit more but certainly not long cover letters. I'll be very honest with you, often they won't get read in detail because we don't have the time.

But yeah, you need to convince the editor that your paper is worth sending out for review. Right, just quickly through rebuttal letters. Often authors are frustrated about reviewer comments but I've never published a paper that hasn't been improved by the reviewer comments.

They always improve the paper. Appreciate reviewers have done their job for free. They provide a bit of quality control.

It's not a perfect system but it does provide some form of quality control. Reviewers, if they've read your paper, will like to see that their comments have been adhered to. That doesn't mean you can't challenge them.

You can but it's unwise to just rebut all of them. So a few tips. Thank the reviewers.

Be clear and polite. Address all their points even if you back them back. Pick your battles wisely.

So, you know, if it's a trivial thing that you disagree with but it's easy enough to change, then change it. Only battle out the points you really disagree with and if you really disagree with them, do it politely but stand your ground. And make the reviewer's life easy by responding to each point in turn.

So there's an example of, you won't be able to see this, but you've got the reviewer comments down the left-hand side and the author responses down the right-hand side and the changes are highlighted in the text. So make it easy for the reviewers when your paper comes back. And yeah, I've mentioned the importance of page and line numbers and if you disagree with a comment, provide a clear and precise rebuttal.

And I'm going to skip this last section so that there's time for comments. So there wasn't much in here but reviewing research papers can be really good when you're writing them because you get to see the other side of the fence. So if you're invited to review a paper and, you know, you can't, as your career goes on, you're not going to be able to have the time to do all of these.

But if you can review some papers, they're a really good way of learning. You'll be able to see these slides in the, when it's posted subsequently. But in the interest of time, to give you some time for questions, I'm going to stop there.

So I'm going to thank you for listening and hopefully answer any questions you've got. And I will stop sharing now. Brilliant.

And if we can have a virtual round of applause in the room using your emoji for Professor Daniel Stencil. That was excellent. And just while everyone else is thinking about questions to either come off mute, you can ask or yourselves, or you can type it into the chat.

I just have something that I'd love to hear any tips and tricks, Professor Stencil, that you might have for when you get rejected, when your paper gets rejected. And sometimes this is even after you've worked on all the reviewers' comments and feedback and it still gets rejected and you've spent so much time. And, you know, I think it's, I know it's not personal, but sometimes it's hard not to take it personally.

I feel like there's always one reviewer as well that's particularly harsh, that reviewer too. So please, any encouraging words of wisdom to share. Yeah.

So yeah, it does happen. The first thing to say is we don't like doing it. It's very, it's quite rare.

We don't like doing it. I shouldn't really share this with you, but anybody that appeals to, if the appeal comes to me, I will look into it and I will give a longer rationale for why it's happened. Very occasionally, and it is very occasional, and again, I hesitate to say very occasionally, we will change our decision if there is an appeal.

It only happens if we feel you've been really unfairly dealt with and we've missed something. And I'd like to say that we don't miss things, but I, you know, I can't guarantee a hundred percent. So that, that's, but it's very rare.

I would say mostly the appeal will be unsuccessful, but if, if, if there is an appeal, I will, I will always look into it and give a considered response to the authors. Why does it happen? Sometimes the, sometimes the authors have rebutted too much the reviewer comments that they've just rebutted everything without changing anything. It's fine to rebut if, if you, and it's right to rebut if you feel that the comments are unfair, then it's right to rebut if you can justify your rebuttal, you know, but if you rebut everything, that usually doesn't, doesn't go down too well.

Sometimes new issues come to light. I mean, here's an example. We had a paper probably last year where the review was really, really thorough, but it came to light on the second round of the review that actually only half the sample that they said that that said they had a sample of X number, but actually it came to light in the second round of reviews, that sample was much lower once the exclusions had gone through, for example, and it made us much less certain about the findings.

So stuff comes to light sometimes, which you didn't realize earlier on. And sometimes you get particularly harsh reviewers and then the, a good editor will make sure that, that, that they don't listen just to that reviewer. Here, here's an example.

I think I had one where the, the reviewer said that these authors were publishing the same, basically the slightly tweaking their paper over and over again and publishing. And that paper went back to the author and the author, we rejected the paper. The author appealed to me and said, I'm really upset about that comment.

And I reassured them that that wasn't the only reason for rejection. And I did, I actually did go and look at the multiple versions of this paper. And I could see that there were, they were different enough to justify publishing a different sort of a similar topic, but, but slightly, slight nuances on the question.

So, but we don't like to, I don't like doing it because I, I know that there's an increased chance of an appeal with that, that kind of thing. But, but it does happen for good reason at times. I hope I've given you some scenarios why it happens.

Yeah, no, definitely. That's really insightful. And it's actually really nice to know how much support there is from the likes of the journal editors like yourself, that we can appeal.

I wasn't as aware of that. Yeah. Yeah.

I hesitate, I'm not encouraging it. I mean, my heart sinks when we get appeals, but as a courtesy to anyone that appeals as a courtesy, I will look into that definitely. And, and you will get a response.

Well, it might not be the response you want, but you will get a response and an explanation. That is really reassuring to know. There is a question from our audience who would like to remain anonymous.

And they've asked, I would like to ask how about questions in the title, or would you advise us to write the study design as cross-sectional or RCT in the title? You can include those in the title. You know, I mentioned about how you should carefully choose the word, wording in your title. So is there enough, you know, word limit to put if cross-sectional or RCT, I suppose you look at all the things you want to say in the title, because that's the one sentence that conveys your study.

And how high up are those in the title? I would say, particularly for RCTs, because they're rarer, I would say, you know, it's good to include that in the title, if the word limit allows. And yeah, so it's okay to include those, particularly for RCTs. It's a matter of what other things you want to emphasize about the paper and how high up the pecking order, the fact that it's cross-sectional or an RCT is.

Okay, thank you very much. We have another question. How do you see papers with partially randomized samples? So I would probably, yeah, I don't, it'd be interesting to find out a bit more about that.

I'd probably look at, yeah, I don't know if the person is on to actually elaborate a bit on that question about how they're partially randomized. If I had concerns, we'd get a statistical editor to look a bit more closely. Or if the reviewers hadn't picked up on it.

Okay, I'm not sure if I've answered that well, but I might need to know a bit more about the context. Can I elaborate on it? Please do. Yeah.

Thank you very much, Professor. So in my case, I have a trial that we did a physical activity program on people living with obesity for a duration of six months. Yeah.

And so we had the control group and a group that followed that trial, but we observed also the outcomes with comparison of those that they did the operation, the bariatric operation. But of course, when we went seeing the groups, those that they were, they undertook the operation, they were a bit heavier. So statistically they showed a little difference.

And there we said, so here we are not randomizing who we randomized where the control and the physical activity. So this is the case of partially randomized. So that's really helpful.

So I think if there's an occasion where it's impossible to fully randomize for good reasons, that you just need to be clear about that in the methodology and clearly state that that's a limitation. But if there's some novelty and some originality in the work that you're doing and some interesting findings, I think, obviously I can't comment without seeing more fully the paper, but I think that that would be acceptable as long as you've stated clearly what you've done and you've stated the limitations of what you've done. And if there was some novelty and value in the findings, I think that would be acceptable.

But obviously, but probably, you know, depend on what the reviewers said. And we might, if we had some concerns, get one of our statistical reviewers to look at it. But from what you've said, I think that there are occasions when that's acceptable.

It is because those that they go and they take the bariatric dilution treatment, while always they are not so much keen to follow a program because they have taken the decision because as you know, now the conditions of who can take the bariatric treatment went lower in BMI. So they are choosing it. Yeah, I think you just have to be clear about what you've done and flag any potential limitations.

Definitely. Thank you very much. You're welcome.

Thank you. We just have maybe time for two more questions, which is actually from the same person. And so Natasha asks, thanks so much, ESO, ECN and Prof Stencil.

Just wondering, would you definitely include the line numbers, even when it's not suggested in the journal's author guidelines? No, if it's not included by the journal, then yeah, I would adhere to whatever the journal guidelines are. Yeah. Yeah.

Sorry, I should have clarified. In our case at IJO, it's really useful. And sometimes we get reviewers vent frustrations on the editors that the papers, our team hasn't vetted the paper closely enough and we get complaints they haven't included line numbers.

But if the journal doesn't ask for it, I wouldn't worry. Although I don't think it should be a major issue if you have included line numbers when they're not requested. But yeah, conform to what's been asked for by the particular journal.

Brilliant. And Natasha also asks, for qualitative papers, what's your view on using participant quotes as titles? So I love that. So that's a good, that's a very good question.

And we do include such papers in the journal. But I, I'd have, I don't know the answer to that. I don't have a view on it myself.

I would probably need, I would, if I got a paper like that, I can't recall having one, but I've got in my, you know, where I work, I have colleagues that specialise in qualitative research, and I would probably seek their, their views on that. That's a good question. Yeah.

Sorry, I can't answer that properly. Diederik, would you like to answer something or ask something? Or answer the question. Yeah, from a qualitative point of view, I love titles with a nice quote, because they speak a lot.

So I would totally recommend that. Good to know. Yeah.

And then I just have a comment in the chat from Andy who says, sometimes it seems some papers are rejected because the PhD, PhD student is unknown. But if a renowned researcher submits a similar topic, the paper is accepted. Professor Stenslow, what do you think about this? Yeah, so that's a really good question, because we don't do blind peer review at IJO.

So we, the reviewers and us as associate editors and editor-in-chief, we see the names on the paper. You know, hand on heart, I try not to, I pride myself on being a fair person and try not to let that affect me. But obviously, that's not a good answer to you.

I don't know why, we haven't had the discussion at IJO. Some journals do do blind review. I'm going to admit that when I see a paper, as an example, with Claude Bouchard's name on it, you know, who probably everyone here is familiar, he's an extremely renowned researcher.

You're going, before you read the paper, aren't you, you're going to be thinking that this is from one of the gods of obesity research, it's going to be a good paper. But I don't think we would reject something from an unknown author. We won't know if there are, well, I guess we, I don't look closely enough to see is this author a PhD student or not.

I just see the name and I may or may not recognise the name. I don't think we'd reject it just because they're a PhD student. But so we have our checks in place, you know, with the associate, the editor-in-chief confirming the associate editor's decision if we reject without review.

If it goes to review, you've got four people who have contributed to that decision. But I can't categorically say that that isn't a factor if you see a name on a paper. I don't think we would reject just because it's a PhD.

I don't even think we know if it's a PhD. I mean, I guess if you look at the somewhere in our system, it might say that somewhere. I don't think we're looking at that level, though.

But yeah, clearly names of papers influence you. But sometimes that goes against you. I think sometimes our associate editors and reviewers can be overly harsh on renowned researchers because they're expecting more, you know.

So we try not to, you know, but I guess we're all human. But I don't think it would be rejected just because it's a PhD student. OK, that's really helpful to know.

And it's actually really encouraging to know as well, because sometimes when you're, you seem like a little fish in a massive ocean, just trying to swim your way. And usually they're teams of people. You know, it's very rare for us get sole authored papers.

We are sometimes a bit suspicious and we do get reviewers sometimes saying when they're sole authored papers, regardless of who it is, that they're a bit suspicious, particularly if they're big data or whatever, because normally we work in teams and different people have got their strengths, you know. But we would still take it at face value. But we do sometimes get reviewers questioning sole authored papers.

Not if it's a perspective, but if it's original research. Brilliant. Well, I just want to wrap up and just say thank you so much, Professor Stenthal again.

And just to say to everyone, if you could, please complete the evaluation questionnaire that's going to pop up once you exit off this webinar today. This is the last webinar for this semester. So we'll see you bright eyed and bushy tailed back in September after a lovely summer and hopefully see a lot of you at EECO as well.

And as I did mention in the chat, please come and chat to us the EACO ECN at our EACO booth during EECO. Or if you see us bopping about, please grab us and have a chat with us and get to know us and join our social events and activities. There's a few links in the chat there.

Please continue to follow us on socials to keep up to date with our activities, such as the winter schools and other e-learning opportunities or other webinars or masterclasses. And, of course, our exciting winter school that will be coming next toward the end of the year. But in the meantime, thank you all so much for attending today.

Thank you so much for your engagement, as always, for supporting one another. That's really important that we do that as a network. We're here to support one another and have open these questions, open these platforms, have these conversations, because I guarantee if you're thinking something or wondering something, someone else is probably either thinking the same thing or may have an answer or may have some guidance or direction.

Thank you so much. Hope to see you at EECO. And please complete our evaluation after the webinar and let us know what you would like to feature in our future e-learning webinars.

I'm Eve Arthurs. I'm closing out on behalf of the ECN board. And again, thank you so much, Professor David Stencil.

Thank you for the invitation. Nice to meet everybody. Thank you.

Thanks, everyone. Bye. Bye-bye.

Bye.