Write Medical Research Papers without a Lab | Hans Laski | Skillshare

Write Medical Research Papers without a Lab

Hans Laski, doctor + researcher

Write Medical Research Papers without a Lab

Hans Laski, doctor + researcher

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57 Lessons (7h 2m)
    • 1. Introduction

      3:05
    • 2. How to find the author guidelines

      6:28
    • 3. How to choose a journal

      9:56
    • 4. How to measure scientific success

      6:28
    • 5. Annoying aspects of publishing

      8:47
    • 6. How to install and use a reference manager (mendeley)

      4:48
    • 7. Software to use for research

      3:31
    • 8. Active vs. passive voice

      7:32
    • 9. 10 Common writing mistakes to avoid

      11:57
    • 10. My Mistakes When Writing Papers

      4:03
    • 11. General formatting recommendations

      1:30
    • 12. The parts of an article

      16:01
    • 13. The order of writing a scientific paper: overview

      15:53
    • 14. Results

      12:08
    • 15. Methods and materials

      5:16
    • 16. The Discussion and conclusion

      19:43
    • 17. Introduction

      5:51
    • 18. Abstract

      6:00
    • 19. Tackling peer review and writing the rebuttal letter

      4:27
    • 20. Authorship

      8:58
    • 21. CRediT authorship contribution statement

      1:36
    • 22. Timeline to publication

      11:38
    • 23. How peer-review works

      5:50
    • 24. What is a letter to the editor?

      13:42
    • 25. Examples of editorial letters

      6:45
    • 26. How to write an editorial letter (with template)

      8:55
    • 27. Example of editing a letter

      12:21
    • 28. Submitting your editorial letter

      7:45
    • 29. The Likert scale for surveys

      8:03
    • 30. Validated questionnaires and when to use them

      9:38
    • 31. Examples of survey based papers

      6:59
    • 32. Writing your Methods and Materials section for surverys

      9:08
    • 33. How to write a study proposal to your local ethics committee

      4:34
    • 34. The results section for surveys

      5:46
    • 35. What is a YouTube quality evaluation study?

      6:03
    • 36. Examples of YouTube quality analysis studies

      5:09
    • 37. The DISCERN, JAMA and GQS instruments

      9:15
    • 38. Database Template for recording your results

      10:28
    • 39. Common excel problems with solutions

      3:46
    • 40. The Methods section for a YouTube study

      4:13
    • 41. Making the figures: bar and pie chart

      8:10
    • 42. How to import your Excel file into Statistica

      1:03
    • 43. The count function

      2:28
    • 44. NORMALITY

      15:20
    • 45. Fisher's exact test and chi square test

      3:53
    • 46. How to switch windows in Statistica

      0:48
    • 47. What is Google Trends?

      6:00
    • 48. Examples of google trends studies

      16:05
    • 49. Statistical analysis for Google Trends studies

      6:39
    • 50. Basic descriptive statistics, plots, and time lag analysis

      2:50
    • 51. Limitations of Google Trends studies

      3:16
    • 52. What is a systematic review

      6:27
    • 53. Example 1 of a systematic review (about Google Trends)

      9:35
    • 54. Example 2 of a systematic review (about Google Trends)

      8:05
    • 55. How to conduct a systematic review Part 1

      1:53
    • 56. How to conduct a systematic review (Part 2)

      11:22
    • 57. Closing remarks

      4:28
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About This Class

From beginner to full scientist! Learn how to write research papers without a research lab and submit to be published in medical journals! I will teach you how to write 3 original papers, 1 letter to the editor and 1 systematic review! By following along and writing your own papers, you'll understand how scientific writing works and you may be published! With the skills of academic writing you will become a more competitive medical residency applicant no matter where in the world you want to work!

Join the Discord server to ask questions to me and to other peers like you! https://discord.gg/unp23sW

Meet Your Teacher

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Hans Laski

doctor + researcher

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Hello, I'm a medical student.

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Transcripts

1. Introduction: Hi, welcome to my sculpture course on how to write five medical research papers without a lab. So this course has made for doctors, medical students, pre-med students, but really for anybody who wants to learn how to do research or maybe get a PhD someday. So if you're a beginner, if you haven't read a paper in your life, if you have no idea where to start this course is for you. But even if you have published some papers, I still guarantee you'll learn something along the way. So high, I guess there's time for me to introduce myself. I'm a final year medical students and I have more than 20 biomedical publications on PubMed. And I've helped my friends and colleagues published for some years and now I want to help you. But it really wasn't like this three years ago. I was confused. I had no idea where to start, but I wanted to do research. Why? Because I wanted to get into a competitive hospital. I wanted to get into a competitive specialty in America. And that was really hard if you don't have research and medical school. Even though I spent thousands and thousands of dollars on it, didn't teach me anything about how to do research. It's beyond me, but that's how it is, and probably it is for you too. So what are you going to learn in this course? You'll start with writing an editorial letter, original papers and systematic reviews. And I'll teach you not only how to write it, but actually how to do all the statistics. You'll learn how to use Excel. You'll learn how to use other statistical programs for free. And you'll see that Biostatistics aren't as scary as they seem. And last of all, and I think this is the most important. You'll really get an understanding of how to do research and how to publish any other paper, not just these puppies that I teach you how to write, but other papers in the future, what do you need? You'll need a laptop, which you don't need though is funding prior research experience, a research lab, a fancy MD or PhD after your name, or lots of, lots of time. Because this course is meant for you to do while you are a student. But it is a long course. It is 60 lectures and that's more than seven hours. So I recommend that you watch it at two times speed. If you can still understand me actually speaking, you are going to get frustrated at some point. Research is hard. It doesn't come easy. So if you have any questions, we can message me on discord. There's a Q and a section, and I'd be happy to answer any of your questions. And there's a community of other peers just like you doing research, so you can ask them as well, okay? And this course is setup in a particular order, so please don't skip the videos. And last but not least, this course is constantly being updated and improved. So if you have any suggestions reached out to me, underscore, tell me, hey, you know, trouble with this. And then I'll add a lecture or a video, or some links helping you with that thing. Alright, so I know that research may be daunting, but I am so happy that you're here, that you found this place on the web. And I want to share this quote with you from Mark Twain. The secret of getting ahead is getting started and you have gotten started by watching this video. So congratulations, and I'll see you in the course. Welcome. 2. How to find the author guidelines: In this lesson, I'm going to show you how to find the author guidelines for a particular topic. So for example, let's say that you have written a paper on ischemic stroke and you want to try to find journals I would possibly published the article of yours. So one way to go about it is to go on PubMed and type an ischemic stroke and then look at the results. So in this case we have a couple of results here. I'm going to click the first link and OK. This is cool. I'm going to go on the full text links because I actually want to go on the actual website. If the actual upside doesn't. If this link isn't here, I can always remember, I can just copy and paste the DOI right in my browser, but I'm gonna try clicking this and see what happens. Alright, so I'm here and I can see the entire article. That's great. All right, but I still want to go to the actual journals, so I'm going to click this neurologic clinics, that's the name of this journal here to maybe go on the page, alright, some hair on the main journal page. And well, there are some important information here already that I can see. First of all, I can see the impact factor is 2.91, which is pretty good for neurology journal. Okay, but I'm looking for the guide for authors. Okay. It says, God for authors. I'm gonna click this. And all right, so now I get the aims and scopes so I can read this and I can see if maybe they would want to publish a paper about ischemic stroke. So okay, let's see, targeted towards the fields of neurology, family medicine, otolaryngology, and pediatrics. Okay, that's cool. Yeah, they might be able to publish a paper, but this doesn't contain that much information, so I'm going to click this. Alright, so I see a lot more information here that might be useful on the steps of submitting a manuscript. That's great. I see all the authorship guidelines and ethics. Alright, well that's not that important. Blah, blah, blah. Okay, this is important manuscript preparation. This will tell me exactly what I have to do to prepare my manuscript for this particular journal. What I what you should pay attention to is exactly what's on the title page. Okay. So I already told you about this. Usually it's pretty much the same. Okay. They don't have anything special about the references. Let's see order of references numerically within the tasky text using the AMA style. Okay, so now you know that the AMA style is what they're going to be using. And you can just use this in Mendeley, right? The AMA stands for the American Medical Association. And then it gives you more information about figures, tables, and boxes. Alright, so this is one way that you can find a journal that you want to submit to. And of course, before publication you would want to read through everything to make sure it fits. But all right, let's move on and let's try to see another way to find a journal. So over here, I'm at the NLM catalog for PubMed. And of course I can change this to whatever, but and I'll M is a way I can find journals. I'm gonna press search, I'm going to press hit stroke, a type stroke and press search. And so I see a bunch of these results. So all these are journals. I'm going to also very important to hit this checkmark here. So journalists currently indexed in MEDLINE, this will narrow down your searches and this is what you want. So all these journals are journals that have the word stroke in them and they're all indexed on PubMed. Okay, so cool. Stroke and vascular neurology. Alright, so maybe you want to learn more about this journal and see if it's possibly a good fit. So I'm going to hit that and you get on this page and you see a lot more information. Ok, well, most of the information here is kind of blah. Doesn't really tell me too much what, what is important about this page is right here. The broad subject terms. So Neurology, it's about neurology and vascular diseases. Okay, so ischemic stroke would fit. And then it also tells me about some topics of cardiovascular diseases, nervous system Diseases, and Stroke. Alright, so this would definitely be a journal that I would want to submit my paper to. Alright, so to see more information, I can hit one of these links. Ok, let's hit that first link. Alright, so now I'm actually at the home page of the journal. Alright, so cool. Now I can see more information, but this isn't really telling me much. So let's go over here, let's search, okay, authors. I'm going to hit that. Okay, so I'm at the author's page and great. Now I can see a lot more information about the paper. It contains some article processing charges that's important because hey, look, I have to pay a 150, sorry, not a 100 or 1500 great British pounds to actually publish in this journal. So that's important for me to know. If I don't have that money, I probably shouldn't submit to them. But okay. This is cool. Now I know that and now I have all the other guidelines that I need. So let's see. I don't know, over here, I can see all the different types of papers that they publish. They published case reports, reviews, correspondence letter, okay. For example, let's just hit correspond this correspondence letter. And I can see important information like the word count. And this case a 1000 words maximum, only one table or figure and a maximum of five references. So this is really important for me to know because I need to know this before I write my letter so that I can stick to the word count and I can stick to the references. Also, I can read some important information. Alright, it tells me that the paper should be submitted online by a scholar one. Okay. And that the letter should be submitted within eight weeks of the articles publication on line. Ok, so that's important for me to know. So as you can see in this way, looking at just journals on PubMed and journals indexed on L and, and my gosh, and L m. I can see all the journals that would fit my topic. And yeah. 3. How to choose a journal: Okay, so in this lesson you will learn how to choose a journal that you want to publish in. So first of all, why get published? I think you guys already know it, but I'll go over it real quick so it enhances your cv. It is better to have publications for job promotion. You can get into a more prestigious institution or hospital or get a higher paying academic job, and it shows your scientific competence. So that's why you should publish. And what can we published? The quick answer is literally everything, but the long answer is images, videos like surgeons having videos of how they, you know, open up the body or how they have a certain technique or whatever's the videos usually of surgeries, commentary about other articles that have been published. Case reports are just interesting cases that doctors have had that they say, oh, this is a unique report. And my report might help shed light on other cases that might be rare like this. Then you have your regular research articles, which is what you typically think of. These are your original papers when you answer a question like, I don't know, is is drinking too much coffee related to birth defects in pregnant women, something like that. Then review articles are articles where they don't have a research of their own. What they do is they look at hundreds or sometimes thousands of other articles that have been published about a certain topic. So let's say a review article. We'll look at all the articles that have been published in the last 20 years about woman drinking coffee during pregnancy. And from that, they'll try to summarize the findings and try to see, hey, is there correlation or not, or, you know, what, what the science currently know about this in a nice summary. Then there are opinion articles, which is literally how it sounds. It can be about any sort of opinion on any public health matter usually or, or even political matters that have to do with health or science. And last but not least, even can publish fictional or non-fictional stories and even poems. So there I think jama has a section on, on basically fictional stories where doctors can say about their experiences or, or, or, yeah, just even write poems about medicine, about the medical process. So literally everything can be published. And where to publish. The answer is PubMed. Alright, so this is PubMed. I think you're, you should be familiar with it by now, but if you aren't heard is PubMed.gov, this is where you go to find articles and this is also where you want to be published. And because everybody goes to PubMed to look for articles. Ok, so to actually find a journal, let's say you want to write a paper about stroke or something having to do with stroke, what you can do is go and PubMed.gov and type and stroke. And then you'll see a bunch of articles. And then over here. Underlined in red right here is the journal. And you can see, oh, okay, so maybe this journal I should submit to, or you can scroll down and look at all the other journals that publish topics having to do with stroke. The next way to go about it is to search the NLM catalog. The NLM catalog. This is another resource from PubMed. Basically, you go here to see all the journals that have that are indexed on PubMed. So over here you look at the articles, you searched the articles, right? And over here in the NLM catalog, he searched for the journals. So let's say you want to publish about stroke again, and you only want to find all the journals that publish in stroke and you're too lazy to go through all these. So that you can do is type in stroke and you'll see all the journals that have stroke in their name, right? So those are two ways you can search for articles, search for journals, right? So you might have heard some different terms like PubMed, MEDLINE and PubMed Central. Basically, it's not too, too important for you to know the difference. But what you should know is that you should try to publish in PubMed and Medline, as I'm showing in this diagram, is kind of a part of PubMed, but a smaller part of PubMed. And PubMed Central is almost all PubMed Central articles are also in PubMed. But PubMed Central is more of a open access platform. And here I've summarized the differences. So on PubMed, you often get articles that you have to pay for on PubMed Central. These are open access, so that means all the articles in PubMed Central or a completely free. So on PubMed usually it's higher quality. And on PubMed Central it's usually lower-quality, but the articles are free. But that being said, the difference is actually not that big because as I said, most of the articles that are on PubMed or also on PubMed Central and vice versa. And other factors you should consider when choosing a journal. So as you might have heard already, if the journal is open access or non open-access. Why does that matter? Well, open access articles are usually referenced more because more people have access to this article completely for free. So that means that your art, your journal article is going to be read more often and it's going to be cited more often. So it's going to have a higher impact on the scientific community. And you want your article to read more so you can publish open access for that reason. Or there's also non open-access. So you might be thinking, well, why doesn't everybody published open access then? Well, it depends on the journal. Some journals are open access only and some journals are none open-access only. But actually today, more journals are opting in for open access. So almost all, I think this is the future of medicine to really have all journals open access. The only downside of publishing in an open access journal is that it usually costs money. So that fee is usually around $2 thousand to publish in an open access article. Or it could even be more 3-4 thousand dollars depending on how long your papers, but it could be less. Anyways, other factors are the impact factor. The impact factor is what people look at a journal. The impact factor is how impactful, I could say the general is within that category. So for oncology journal and impact factor of 22 is it would be one of the best oncology journals in the world. Whereas an oncology journal with the impact factor of one would be not that big for you. I would. Whatever specialty you're trying to get into, trying to write, write your article for. I would aim for beginners, aim for impact factor of about three. Yeah, so if your article is big, very new finding, you can aim for a higher impact factor. But for now, I would aim for impact factor of about three. And then the last thing you should look at when trying to find a journal is the article type. Some journals accept only certain types of articles. So we had that slide before where I said that almost everything can be published. And that's true. But some journals only publish certain types of articles. So maybe only original papers and review papers, and not letters to the editors or maybe not videos or maybe not poems. So you have to look at each journal and what you can actually publish when to choose a journal. And this is a big question. When I talked to my fellow students. You should choose a journal, not after you write the article, but before you write the article and you should make a list of three potential journals. Why should you do this? Well, you need to know that the actual article that you're trying to publish can be published, right? You need to know where you can publish it. And it's good to know which journal you want to publish in so that you can write the article for that journal, right? You can have the correct layout. You can have everything that's needed so that you know beforehand and you don't have to scramble at last minute after you've written your article like, oh, I need to change this and this or are, you might find out that, hey, actually, it'll be almost impossible to publish this. Alright, so I just want to leave off with a quote. It's never too late to be, which you might have been. So if you're a complete, completely new beginner and you want to become a scientist, well, you're taking the right steps, so I'm rooting for you. I'll see you in the next lesson. 4. How to measure scientific success: Okay, in this lesson we're going to learn how to measure scientific success. Okay, so first of all, the strategy to becoming a successful scientists is to publish in high impact and prestigious journals, published in open access versus the paid subscription model journals. So more people can have access to your journal. Have attractive and friendly title for your journal. So shorter titles that are easy to read, not that technical, and also have shorter length manuscripts. Because no scientist wants to read through a ton of, you know, words, a ton of stuff they want to get right to the point and easy to understand paper that fast to read. The shorter your manuscript is. Of course, it depends on the journal. They have their own limits on the word counts and things. But generally the shorter and the more concise, the better it is. Ok, the article and scientist stats. So how do you measure success? Well, you can measure it in the number of publications, right? But the number of publications doesn't take into account things like, you know, because some papers can be published in bigger journals or some papers can be published in smaller journals. So the number of publications is good. Maybe if you have, you know, 50 publications, that's pretty good. Or if you have a 100 publications, that's okay. You can say that on your CV or whatever. But there are some other ways to measure it. You can look at the citations. So you can see the citations or how many times your paper was referenced by other scientific articles. Citations is a good way of measuring success because now you're seeing how many other people, other scientists, actually care about your findings, right? So that's, that's, that's a better measurement of scientific success. And then there's the H index and it's kind of a complicated, a complicated calculation, but it's also based on the number of citations that you have and your overall number of publications. So you can understand it as just a formula taking into account the number of publications and the citations that you have and the H index, a huge H, H index would be like 70. And beginner H index for, I don't know, a young budding scientists would be like five. Okay. And then there are other alternative measures of scientific stats. So these are the traditional ones, citations, the H index number of publications. But then there are other things like the readers, I'm on mendeley. Mendeley, as I might have mentioned before, is the reference manager. Also the shares on social media. So these are called ultimate tricks or alternative metrics. How many times people have shared your paper on social media. You know, scientists also have Twitter pages or, or Facebook pages that they share their findings on, or they share other people's findings on. And that can be a good way of determining if paper is pretty, pretty big or not. And also the score and shares on ResearchGate. So in this small lecture, I'm going to give you some examples of these. So here's a view of Mendeley statistics. So these are my statistics. So right now a total of 32 citations. And in the last month I got three more citations. And total views on Mendeley. So about 5 thousand people overall have viewed my publications there. Or this is just a random researcher. I just wanted to show you on ResearchGate what statistics you can get. Pretty cool, calculates your H index for you. So in this case five. And then it also shows your TOP cited research according to your H index, which is this one. And then it gives you like a ResearchGate score depending on other members on it. And it gives you kind of a good reference for how, how big of a scientist you are compared to other members across the world. So in this case, your score is higher than, I don't know, 57%. I wouldn't take this too seriously. This is not really, this is not something really official. But your agent X, you can definitely put on your CV or, you know, kind of I don't wanna say brag, but yeah, you can say it on an interview or your CV. This is my h index. Also Google Scholar. It can give you some good statistics on the citations. And when I recommend everybody makes Google Scholar account so you can keep track of your publications. And also last but not least, pub lawns per blondes is a way that you can keep track of things like h and x, but also look at a times that you have. We reviewed other papers, right? We talked before about peer review and how other doctors and scientists will read your paper and decide if it's worthy for publication. And well, you could be after you publish a paper to, you could be invited for peer review. And to keep track of the papers that you have read and peer reviewed, you can use problems because it kind of gives you proof and gives other people proved that, hey, you've actually peer reviewed these papers. Otherwise people won't be able to see that you have peer reviewed anything. So this guy is one of the biggest as of, as of today, 2020, he's one of the biggest reviewers. So you can see that he has 3 thousand, which is huge reviews, but he's done. So I recommend just to finish off that you make an account on Google Scholar. Unresearched gate if you want, and also on problems eventually when you're going to start doing peer reviews, that way you can keep track of where you are and how impactful your publications are. And also this is great to add on your CV because then other people, you can tell it to people. Oh, I have this many publications, as many citations and this is my h index. 5. Annoying aspects of publishing: Okay, in this lesson I want to talk about some of the pitfalls of publishing. Alright, so avoid these traps. First of all, avoid fabricating data or just making up data because OK, that's wrong and that can have a really bad implication for you because well, your paper can be retracted and you can have a bad reputation as a doctor or a scientist. And it's bad also for the medical community because, well, people will take your findings and they'll say, oh, well this is something new and it actually might change clinical guidelines. So you don't wanna do that. And there have been scientists that have fabricated data in the past, but they've been found out and basically publicly shamed. So that's not good to do even if we all as authors who want to get into the biggest journal, but that's not good, okay? Over hyping your conclusions, this is a big one that peer reviewers are going to tell you. You want to sell your article. You want to say that this is the best paper ever. These are the really big findings, but over-hyped and your conclusions is a mistake and your paper can often be rejected because of that. Or rejected with possible revision, maybe they'll tell you, okay, don't over-hyped conclusions. Okay. And plagiarism and self-plagiarism, as I said, if you're going to copy anything, you don't just give the reference, you have to give the quote. You have to actually put it in quotes. And self-plagiarism. It might seem weird, but let's say you've published a paper before, and I don't know, the Journal of tables and chairs. And then you published another paper in the Journal of chairs. And you just want to copy whatever you wrote in another publication that was yours that you co-authored, but you can't copy. He can't do that. You can't self plagiarize. It sounds weird. But once he published in that journal, that you have basically transferred the copyright to that journal in most cases. So if you copy and paste something into your own paper, even though serum writing, that's now self-plagiarism and it's also not good. And last but not least, submitting to multiple journals at once. I think we've gone through this, but you can't do that. You have to do it one at a time, even though it's super slow and you might not like it. Actually, I think nobody likes it. But you have to do one journal at one time. Otherwise it can cause some troubles. And generals might ban you. Ok, avoid predatory journals. Okay? You might not have heard about this as a new scientists, but there are a lot of predatory journals. And why I say predatory is that they just want to publish your paper and make money off of it. So they're going to give you emails. They're gonna say, hey, go, come publish with us. They'll publish your paper. And it doesn't matter if your paper is a good paper, if it's. Garbage. They're just going to publish your paper because you're going to pay them some article processing fee or a open access publishing for you. Or they're just gonna make up some random fees for you to publish in their journal and they just want to make money. So don't publish in these journals. There are lists of predatory journals online that you can reference so that you don't fall into this trap. If you're not sure if it's the predatory, predatory journals are not. All also you can look and see if a journal is index on PubMed. Pubmed tries to make sure that journals are journals that PubMed indexes, not predatory, that they're actually good journals that are ethically sound, that don't, are, aren't just trying to make money. Of course, PubMed is never a 100% correct and good at doing this. So you can just make sure by going on the website, looking, asking your peers if they've published in that journal, looking at the impact factor and making sure the impact factor is real. Because journals will sometimes say, oh, this is our impact factor and they've calculated it themselves. But the real impact factor is calculated by clarify that analytics, their statistics, the official impact factor. So make sure you look at the official impact factor of a journal, not just the one that they tell you they are. Ok. And then peer review for these predatory journals because they don't care about actually publishing real science. They're going, they're peer review process is just going to be a show. They're gonna say whatever and just publish your paper. Okay, so email spam is going to be a reality for the corresponding author. What's going to happen is after you publish your paper, the corresponding author, his or her email is going to be listed on the paper so that other scientists or other people that read the paper and need to contact you somehow about something. Other scientists, they can contact you by the email and the corresponding email, corresponding author's email is always listed. So what people will do is they'll just go and copy your email because they know you're a scientist and they'll try to get you to publish in the journal. So this is like an example. I'm gonna give you a couple of examples of these spam spam emails that you'll get. So they'll start out with the steam and professor. And you know, you're not even a professor, but they'll say esteem Professor. Archives of health science invites your research article submission. Blah, blah, blah. Kindly submit your article within this mail. They'll say whatever just to get your article because at the end of the day they're trying to get money for me to publish your paper in their journal. Okay? For example, this is another one. Del, you'll have spam to join a medical society based on the interests of your authors and blah, blah, blah. We invite you to this society. If you want to look at good societies that are actually sound, they're not going to probably send you spam emails. They're just going to, Yeah, if you're a reputable society, doctors will find you. You won't ever be getting emails from them or are usually not. Also spam on becoming an editor for a journal. And so for example, become a section editor for inquiry and impact factor. So they even listed impact factor here probably to show their validity, but I doubt that this is the actual calculated impact factor by Claire that analytics. So this is probably their own impact factor which you know, it might not be totally the right one. So if you're getting these e-mails, you don't basically ignore them. And if you're not sure if this is actually a reputable email, if this is a legitimate email, you can ask your fellow scientists, your fellow colleagues, just look online to see if o is this journal legitimate or not. Also, the most spam you're going to be getting is to attend a conference. So there are a lot of reputable conferences around the world. And this is where you'll get to mingle and meet scientists in your own field and they're wonderful. But basically, you have to understand that anybody can make a conference. So you have to look for conferences that are made by reputable societies. So if there's a conference on anesthesiology, There are certain there like one or two societies of anesthesiology that can, that have the, you know, prestige and recognition to actually hold those conferences, other conferences, whatever, you want to completely ignore them. Why are they asking you to come? Because conferences make a lot of money for people who are hosting the conference, because every person who speaks at a conference needs to pay a lot of money. And that money can be a lot like 1, $2 thousand or pounds. So just look out for these spam emails after you get published, especially if you're the corresponding author, but also the other coauthors. Somehow they find your emails. 6. How to install and use a reference manager (mendeley): Alright, in this tutorial, I'm going to teach you how to download Mendeley and mentally is a desktop reference manager and web reference manager. So first go on Google and click hit Download Mendeley, and just go on the first link. And you'll come here. So download whatever you want to. So if your Windows download for Windows or Mac or Linux or whatever, so download this and also download the web importer. So you click here and finite more. You'll go here. So I'm on Chrome, so get web importer for Chrome. And then you'll go here and just download. I already have downloaded, so I don't need to download again. So after you have everything downloaded, I want you to go to whatever PubMed page where you want to reference whatever thing that you want to reference. So let's say I want to reference this paper in my, in my paper. So the genes play a role in the decoy effect. What I'll do is, I'll go here and click the Mendeley app button once I have installed. And it'll open up after a bit of loading. Ok, so head comes up to genes play a role in the decoy effect. And over here, do genes play a role in the decoy effect? So after that is checked, all I do is if I have a folder that I want to put it in, I can put it on that. But anyway, that's all it is. Press add. Then you go on your Mendeley desktop application and you hit sync up top. And while that's sinking, can see it's sinking down here. Go on tools and install. Install MS Word plugin. I already have it installed, so it says uninstall MS Word Plugin for me. But anyways, that's how you do it. And now we're gonna go in Microsoft Word. So here we are in Microsoft Word and I want to insert some kind of reference. So if you go to references and hit Insert Citation, you'll be able to insert whatever reference he wants. So in this case, the genes play a role in the decoy effect and boom, the paper will show up. I'll press, okay. And then I'll get this thing, come up this number. So that is our reference. And then at the end of the paper, this is why Mendeley so grade will have a reference section. And all I have to do after I get in, I write my entire paper and put an older references like this. Well, I have to do to make the bibliography is go up to the Reference tab and hit Insert Bibliography. And mendeley will automatically right the reference exactly how it's supposed to be written for the exact journal. Now, every journal has a different style of reference, so all you need to do is go to style. So for example, right now it's Patient Education and Counseling and there are bunch of others. For example, maybe we want to make it look like the thing for the American Medical Association style for the medical, American Medical Association either set that and it changes the style. You'll see the number is different and the reference itself is also different. Now let's say that the actual reference right now isn't, isn't on the short list. So I can go to More Styles and get more styles. I'll just choose any random word or no jump Latin American Journal of criminal justice. I can install that. And then go to Install tab and then just find whatever it is that I'm looking for. So forgot or criminal justice. Okay, there we go. Use this style hit done. And now we go back. And then it gives me the style for this criminal justice journal. So it's pretty easy. And just one more tip. This will be useful when you do systematic reviews. If you go over to tools, you can check for duplicates. So it'll search for papers that have been added twice. So you don't well, you can delete the ones are merged, the ones that you think are the same. And you can select confirm merge. And it'll merge papers that it thinks are the same. And this is great for systematic reviews and we'll get to that later. But for now, this is how to use Mendeley and add references to whatever paper you're reading. 7. Software to use for research: Okay, so in this lesson I want to go over some of the software that you may use for your research. Alright, so if you have the microsoft suite, the Microsoft Word, and Microsoft Excel, great, then I recommend you use that if you already have it installed, right, because it is paid and it's quite expensive. But if you don't have that, you can download OpenOffice totally free. Or you can work on Google Docs and Google sheets and everything. Google has its own online suite. And I will say that mendeley, the Reference Manager, works on Microsoft word and it also opens on works on OpenOffice. If you're looking to work on Google Docs, I would recommend using Zotero, but we'll get to that in a bit. So the reference manager, if you have the Microsoft Word, use Mendeley. If you don't and you're just working online, I would recommend Zotero. And then there's also Endnote, but EndNote is paid. So yeah, it does the same thing but it's paid. So I don't recommend it. Alright, then for the statistical software, the F31 is passed and it's really great software. It works for both PCs and Mac. Then there's mad calc. It's, it's a great software as well, but it's paid and it's only for PC. Then there's statistics. It's a much more advanced software. It's paid and it's only for PC. And then there's Graph pad, graph pad prism, which is also a very advanced software like statistics. And it makes great, especially for figures. If you're making beautiful figures, you can use this. But it's paid. But it works for both PCs and Mac. So if you don't have it already, our recommend downloading past because it's completely free. But the thing is for statistical graph pad, prism and mad calc, you can get the 30 day free trial. So, you know, in our in our course, we're writing all these papers and about one month. So if you, if you don't want to pay for them, you can just use a free trial and follow along and you don't have to pay for anything. Okay. So some of these programs are like statistic, our Medcalf, they only work on PC. So if you really want them to work on a Mac, you can use several solutions. So there's apples bootcamp. There's the virtual machine that you can have for Mac OS running Windows programs like Parallels Desktop, VMware fusion and virtual box. Then there's also crossover, Mac and wine and wine bottle. So there are a bunch of programs that you can use to run Windows applications on Mac. Just look at what works best for you. I would recommend using Apple's bootcamp because then it doesn't matter. It has basically it has the best compatibility with Windows programs. With these other software, you might run into some problems here and there. So I do recommend this first one, but I don't own a Mac myself, so I can't I can't actually tell you from personal experience, just from what I've read online. Alright, so here are the download links for all these, all the software. And I'll leave this presentation so you can download it and you can just quickly go to whichever software that you want to download. All right, I'll see you in the next section. 8. Active vs. passive voice: Alright, let's get started. So what's the difference between active and passive voice? And which one do we use in science? So the answer is, we use the active voice. And if anyone tells you otherwise, maybe your doctor, your professor, your superior, they say no, no, no. You can't use the active voice in science, you can only use the passive voice. Well, tell them that I told you or actually, no, it's better that you tell them that nature told you, write nature the one of the biggest journals, biomedical journals in the world where the impact factor of 42 recommends that authors write in the active voice. As experience has shown that readers find concepts and results to be conveyed more clearly if written directly. Who knew that information was better if written directly. Ok, so the active voice is the way to go and they want you to unpackage concepts and active voice, as you'll see, is very simple and readable and, and just natural. So ok, the active versus passive voice. Let's get into it. What is it, right? So the active voice tells us what a person or thing does, and the passive voice tells us what is done to a person or thing. So that's the difference. If you look at the structure of a sentence, typical sentence and active voice, you have the subject, then the verb, then the object. But in passive voice you have the object verb then the subject. And okay, I think an easier way to go through this will just be just to go through an example sentence. So here we have in the active voice sentence, the banks made mistakes leading to the recession of 2008. Okay? So the banks, which is a subject, they made mistakes, that's the verb, leading to the recession of 2008. So the recession is the object. Now let's read the passive voice sentence. Mistakes were made leading to the recession of 2008 by the banks, wu wei. Not, let's just cross out by the banks and we can still have the sentence. So mistakes are made leading to recession of 2008. Mistakes were just made. Mistakes were made. We don't know how those mistakes were made. We don't know who made those mistakes, not by the banks, of course. But now you get the idea that passive voice avoids responsibility, right? And passive voice sounds awkward and it's harder to read. While active voice sounds natural is easy to read. This is the way we actually normally speak, right? And it claims responsibility. So here, the banks made mistakes over hair. Mistakes were made. Who, I don't know who made them, but they were just made. So it avoids responsibility. So in science, which you have to do is recognize the passive voice. But I understand you have your full manuscript, maybe older, you wrote it, and you have thousands of sentences, or maybe not 1000. You have thousands of words. They have got 4 thousand words in a typical manuscript. So how are you going to find those passive voice sentences quickly so you can fix them? Well, the trick is a passive voice always needs a To be verb and what's thought to be very well to be can be hidden as many things and that's what I have on this slide. So to be can we written as is, are, was, were, be, been, Em has been, and also could shall, should, will, would, may, might, must be. So could be, should be, you know, all these things. So when you're looking at your manuscript and you see, you know, was or where B or you can say that this might be a passive voice sentence if he can't pick it up directly, and then you can try to change it to active voice. So now you're probably thinking, Let's get some practice. Changing passive voice sentences to activists. I think that's a great, great idea. Alright? So in these, in these examples, we're gonna do three examples. And I want you to think to yourself, who does what to whom, right? Because we know that in passive voice we have object, verb subject, but an active voice, we have the subject, then the verb, and then objects, a subject verb object, right? Okay, so who does what tomb, alright, passive voice with alpha amino level in IC acid, the tumor could be better visualized. And I bolded could be y, because we know that. Could be, could be, right. This is in our list here. Could be. It shows us that it's active. In passive voice. Could be, be better visualized. So now try to think of how you could change this into the active voice to just, I'm going to take a moment with a couple of seconds. Alright, now I'm gonna give you the answer. So the active voice would be, we visualize the tumour better with alpha amino level and ic acid. So the passive voice would be, the tumor could be better visualize. And now we visualized, right, sounds better and it's shorter. Okay, let's do another example. Fluorescence of the tumor was observed under blue light. Okay, try and take a moment and change this into the active voice. Ok, it turns into we observed fluorescence of the tumor under blue light. All right, good job. All right, one more example. Okay. This is the passive voice. Muscle hypertrophy is induced by high-intensity exercise. Now this is a tricky one. I purposely gave you kind of a tricky one. This is a bit harder. See if you can do it. Muscle hypertrophy is induced by high-intensity exercise. Okay, here's the answer. High-intensity exercise induced muscle hypertrophy. So in this sentence, the subject is high-intensity exercise induces the verb and the object is muscle hypertrophy. All right, it's a good job with these examples. Is there a moment? Is there a part in your manuscript when you can actually use the passive voice that I encourage you to use passive voice? Yes. It is the methods and materials section, right? Methods and materials section is a part of the manuscript where the emphasis is on the what, right? Like what did you use? You're literally listing what you used, your microscope, you are your tools, your software, and not on who was using it, right? It's very boring, bland part of the paper, methods and materials section. So in this section, you can, I give, so it gave you permission to use the passive voice. Now, if you want to use the active voice in the methods and materials section, you know, great, you can do that. But if you want to use a mix of passive and active, that's also fine. But you can use the passive voice and you won't be in trouble. But also, the one last thing I wanted to mention, active voice is just more enjoyable to read than passive voice. Why? Because passive voices harder for you. So, you know, because active voice is more natural, it's just easier to read. Alright, with that, I will leave this lecture and I'll see you on the next section. 9. 10 Common writing mistakes to avoid: The ten common mistakes to avoid. That's right. I'm gonna give you all the common writer mistakes that I've made, that my students have made. So you don't have to make the array. Let's start. First of all, there's some dirty words that you should never, ever, ever use. These are more many a lot. So instead of using these dirty words, instead, just use several. I actually, once you go through your manuscript after you have completed it and take some of these tips and literally just, you know, control, find more or many or a lot and just replace them with several. This is super easy to do and it makes your writing sounds a lot more professional. More dirty words get can and different. Don't use these instead of getting to obtain or other words can use may or different. Contrasting are distinct or other synonyms but don't use these. These are dirty words. They're overly used and it is not very professional to use them. Alright? And now these are words or phrases to absolutely just delete. You don't. 99% of the time you don't need them. So just go through your manuscript after you've written it and just delete them. So very doesn't, doesn't give you anything. Also, also just doesn't give you anything really. Quite. And also I put LY, So these are unnecessary adverbs. And in conclusion, a lot of people, a lot of people, that's a dirty word in itself, but it's okay, I'm talking to you. Alright? But in conclusion or enclosing or n summary, conclusion, always Self-evident that it is the conclusion. I can see it. It's at the end of the paper. It's the conclusion and you're telling me. So so don't tell me that is the conclusion. Just don't just say whatever you wanted to say. Whatever the conclusion is, you don't have to explain it. And also the fact that you don't have to say the fact that it's a fact. I know that it's effect. So just just say whatever you want to say. And if it's a fact, I'll note. And you can give a reference. So even, even say it's more of a factor, whatever. Okay. If and whether Okay, now this is not the type of weather it would the Clouds. This is more like I want to, there are two alternatives. You know, whether or not we want to go to the movie theatre or the park. So what's the difference between f and weather? So weather is if you have two alternatives, like I just said. And if is, if something is dependent on something else. So let's go through just two examples because I'm guilty of making this mistake. So over here, please let us know if or whether you have any further comments or concerns so you guys can kind of think of it yourself. Which one would you use here? Please let us know if you have or whether you have any further comments or concerns. The right answer is. If right, it would be f because it's dependent on something else. If you have any comments or concerns, you can let us know, right? There are no two options. Over here. Let's see what the answers. Okay, we marked if, whether videos contain the following quantitative elements. Definition of meningitis symptoms causes. Ok. So in this case, what would you use F or whether in this case, it would be whether because there are different alternatives, there is, you know, we marked if videos contain this, this or this. So there are three alternatives in this case. And because of that, we would use whether not if, because nothing is dependent on something else, it ok. Avoid aspects. This is, this is very common in any, in any research paper physicians, for example, physicians are concerned about various aspects of the treatment. Instead of saying aspects, just delete the word aspects and actually say what aspects those are, right? So for, for example, physicians are concerned about side effects, efficacy, and the cost of treatment. This way we got rid of aspects altogether and now we have a much more detailed sentence that's much more pleasurable to read and it's very specific and not broad like the first sentence. So control. Next time you're reading it, control, find aspects and just get rid of it, make it more specific. Okay, a void there. Alright, so let's go through an example. There is recent literature supporting Smith at all its findings. Okay, that's an OK sentence. It's not too bad. Okay, but let's read this one. Recent literature supports Smith at all its findings. Ok. Well, not only is the second one shorter, but it just sounds better and it's gotten rid of there. Usually there is completely unnecessary. If you're starting the sentence would there you can rephrase it. So, so you put the actual subject of the sentence in the beginning. So for example, there's recent literature supporting Smith at all findings. Okay. We can just say recent literatures, Portsmouth Smith at all findings have that as the subject of the sentence, not there as a beginning of the sentence. Alright? And also avoid similar, similarly to there. Don't begin sentences. It's just silly. For example, it is clear that multiple sclerosis is a debilitating disease. Instead, you could just have multiple sclerosis as the subject of the sentence. So multiple sclerosis is a debilitating disease. Great. It sounds better. It's much more simple. And there we go. It's shorter. Alright, eight, avoid, and these are some general tips. Avoid jargon and to technical terminology, remember, when you're writing a paper, you're not only writing it for people that are like those specific scientists that are in your niche specialty. Note, you're actually writing it for the world. You're writing it for physicians that are, I don't know, nephrologists that are neurosurgeons that or I don't know, public health experts. You're writing it for people. Really anybody, it should be easy to understand and easy to comprehend for anybody. At one exception to this rule is the methods section. The methods section, as you probably know by now, is the most boring section. And that's where you can get away with writing jargon and technical terminology. Because you're basically going to have to give, you know, I use this, you know, X5 97 microscope with this thing on it. Okay. Unreadable descriptions. For some reason, I don't know, but this is very popular in science, just giving a bunch of blah, blah, blah, descriptions that are just so technical. Nobody can actually read. And convoluted figure legends. Tried to keep it simple and too many acronyms, okay? This, this is something that almost every scientist is guilty of. If your oncologist, you think that everybody knows those abbreviations and acronyms that you do. That's not true, right? If I'm I don't know, maybe I'm a medical student, maybe I'm another person in another specialty. Maybe I'm I don't know. Maybe I'm a surgeon and I'm trying to read this Oncology paper. So try to use try to not use acronyms and try to dispel the word OUT. Okay? Okay, last but not least, skim the journal you're applying to y. This will give you the level of science that a journal publishes. And this will save you a lot of time, you know, often, you know, I was guilty of this in the beginning when I was very new to writing papers. I didn't know, you know, if I was reading paper, can I submit it to this journal or not? I don't know. I think, I think this is a great piece of science, but it's better to actually read the journal. And then you might say, OK, wow, the level of science in this journal is much higher than I thought. So maybe I'm in the level when I say level of science, level of findings, you know. So so read the journal, read even just skim the titles of their latest issue and try to get an idea of of what what type of findings, the level at which they publish. And then, you know, have reasonable expectations based on that. Alright? So skim the gentle, not only for the level of science but also the length, right? Sometimes journals don't have, usually they have a specific word, word count or word limit, but sometimes they don't. So you can read the journal and see, alright, not only you know, the length of the manuscript and the approximate word count, but also the length of, you know, do they have short introductions, are long introductions or whatever. Even each section you can see you get a kind of idea. Usually by the way, the introduction should be about a page long, no more than that. Alright, also the readership, right? If your topic is on, I don't a movement disorders, make sure that you're publishing in a neurology journal where they publish about movement disorders. Maybe the journal is more concerned with other topics. Maybe, I don't know the other diseases. And last but not least, if you know you want to publish in this journal, just go on the general and download the PDFs that, that way you'll get to see how they actually format their tables and figures. And you'll have, you'll have a jump headstart because now the reviewers and the section editor will be like, wow, these figures and tables are all formatted really nicely the way I like to have them in my journal. All right. And last but not least, if English is your second language, which it is for a lot of scientists, because of course, the language of science right now is English. But the whole world can conduct science and they do. And English becomes kind of a problem. So if English is your second language, I highly encourage you to get your paper edited by native English speaker, or just a speaker who really knows English very, very well. Or if that's not possible, if you don't know anybody and Eva, colleagues or friends, you can get a professional to edit it. But I will say that, you know, publishing is a business and getting a professional person to edit your paper online, it's possible, totally possible they'll do it. But it's kind of like it's quite expensive. Right now as of 2020, it's about $200 plus. So for the cheaper at its editing of the manuscript, it's $200, which is which is quite expensive, especially if you're a student. But yeah, and they go up to like thousands of dollars. So I hope these ten tips and tricks for writing will be helpful. And I encourage you to not only see this video now, but after you've written your manuscript, go through this video again, look at the slides. You can download the slides, will have them there and make sure you just go through these ten suggestions and that you fulfilled all of them. All right, I'll see you on the next lesson. 10. My Mistakes When Writing Papers: Okay, so in this lesson, I want to go through some of my actual mistakes when writing papers and then go through the response the editor gave me. So maybe you can learn something from my mistakes and not make them. Alright, so here's the sentence at the top. We suggest that hospitals clearly addressed the pathophysiology with patients. Now, try to figure out, I'll give you a moment just to figure out what is wrong with this sentence. So I'll read it again. We suggested hospitals clearly addressed the path of the pathophysiology with patients. Okay, here's the answer. It's wrong. Word usage because hospitals don't treat patients. Because hospitals are just buildings, right? So hospital staff treat patients. Obviously, it's kind of a really small error, but it's a big error in the fact that I'm saying that hospitals should, you know, clearly addressed the pathophysiology with their patients? I haven't talking Hospital yet. But yeah, so it should be hospital staff. Alright, this example, our study illustrates the valuable insight that Google Trends can offer. So just maybe think of what might be wrong here. Okay, here's the answer. It's wrong word usage again, right? Because he cannot illustrate an insight, right? Our service, our study illustrates the valuable insight. It's difficult to actually illustrate the insight. It would be rather better to say gain an insight or have an insight, right? Okay. Smith at all describe how bla bla, bla, bla bla. Right? Maybe figure out what's wrong. Okay, and here's the answer. It should be Smith at all with periods. There should be a period hair. Why? Because at all is a, is a Latin phrase or a Latin abbreviation. So at means and in Latin and all is short for alia and Latin. So you put a period after it because it's an abbreviation, right? So Smith at all. So period here. Now I was confused about this little bit because according to the journals journal guidelines that I was submitting the paper too, they said don't put a period here. So I don't know why. Maybe they didn't understand it or maybe they just don't know. They have their own formatting guidelines. But if you're gentle doesn't say anything about it. There should be a period there. Alright. One more example. There are critical and misunderstandings between patients and surgeons in regard to surgery. Okay, a hint for this one. This isn't actually a technical error, but try to figure out how the sentence could be better. Okay, I'm gonna give you the answer now. Alright, so this is a interesting point. This is what the editor, editor told me and it deserves at least a hint of an explanation, right? Because I said there are critical misunderstandings. The reader can notice the reference. So here's the reference, you know, 14, whatever it was, no paper. However, it would greatly increase clarity of this article if at least one example of the misunderstanding was cited. Alright, so it would be much better for you to say there are instead of critical misunderstandings. If he just list the critical misunderstanding. So, you know, I don't know patient-doctor communication. I don't know. Misunderstood, whatever, whatever whatever are the misunderstandings between patients and surgeons in regard to surgery. So in this way, I hope that you learned a little bit from my mistakes. So you don't have to make them and say don't have to have the editor. And you can make the editor's job easier for whatever journal you are submitting your paper to. Alright. 11. General formatting recommendations: Alright, I just want to give you a few tips on formatting your manuscript. So you might have heard that Times New Roman font that you should use. I don't really prefer Times New Roman. I prefer usually Calibri REL, because it's much easier to read. And Times New Roman is very narrow and it's difficult treat especially when you're going to be reading all the time and reading all the time. So I prefer Calibri. And also almost for every manuscript, you need to double-space your entire text. So here, now it is double-spaced. Yes. Okay. And also now you see that it's double-spaced, but there's, you know, the paragraphs are still together. So I also double-space it and add a space after the paragraph. That way. Now you can see hairs this paragraph and here's the next paragraph. Okay. So those are just some tips. And last but not least, I almost forgot. Makes sure it's 12 points the font size. And these are pretty much the standard recommendations, double-spaced 12 font and Calibri, or sometimes they want you to do another font, but these are the basic recommendations I'd seen in most journals. 12. The parts of an article: Okay, in this lesson we're going to learn the parts of an article. So there are a couple of parts of an article which pretty much for any paper you are reading, they're going to be the same. So this is what you'll have to have for almost any paper. So the cover letter, the abstract or the title page, the actual manuscript. And then some statements like conflict of interest and financial disclosures, the acknowledgments, and the references. So now in this lesson we're gonna go through one by one and I'm gonna tell you exactly what it is and give you examples so you know how to write your own when the time comes. The cover letter is one of the most underutilized parts of a submission. This is where you can say anything to the actual editor that will be getting your paper and that will be making the decision for your article should be published or not, or who, which peer reviewers friendly or unfriendly maybe should get your article. So you can say anything that's not in your actual article. So you can say why your article is amazing that you wouldn't be able to say in your paper. You have to say why he chose a journal, why the Journal should publish your article. So you should say the findings, how they're knew, how they're novel, how everyone needs to know about this. You also need to stay. State that the paper is not currently being considered at any other journal. That's right. You can only submit your paper to one journal at a time. I know this might sound annoying. It would be great if you could send your paper five journals, and then whoever wants to publish it first, you can do that, but no, you have to publish it one by one and you have to wait. It's annoying, but that's how publishing is. That's just the way it is. And then you have to, the cover letter should be written by the corresponding author. So let's give you an example. So there are two parts. I divide up a cover letter into two parts. The beginning, which is pretty easy. She'd started out with the date. Have the editor in chief has his or her name and all his or her titles. So over here I have an example. Just say editor in chief and then the name of the journal. So in this case it's Euro surveillance. Alright, so you start off your letter and a very polite and formal way, dear doctor, or whoever that is. And you basically start out with the same sentence. You can copy this. So please consider our original paper entitled this, this for publication in the journal. Now of course you're, the title of your paper will be different and your paper might not be an original paper, it might be a review paper, it might be a poem. I don't know. Whatever it is, you change the template. So the, I guess the second part of the cover letter is the actual meet the most important part. So you say why, you know, why they should publish this paper and why this journal is the best. So for example, in our paper, we challenged recent literature which found that Google Trends was able to surveil the epidemiology of the novel coronavirus. Okay, so that's cool. You just said that the EU challenged recent literature. Wow, okay, so that's novel, that's saying, Hey, this paper should be read, okay, and then you give a summary of your paper. So here, through a comprehensive methodology, our study shows that these findings and previous publications or most likely incidental. Okay, so you're saying that, wow, this paper needs to be published because it sheds light on previous publications. And you show that, oh, you have a compromise comprehensive methodology. Alright. So i the last sentence I your name. So whatever your name is, John Smith certify that this manuscript has not been previously published in whole or in part are submitted elsewhere. Elsewhere for you. You can basically copy this sentence word for word, because this is just saying that, hey, you know, I haven't sent this paper to anybody else. It hasn't been published. They want to know that you, you're sending your paper to their journal and that's all they care about. Their joan, That's it. Ok. And the last part, just a very polite way of saying bye, bye. So you can say we humbly thank you for your time and considering our manuscript for publication, please let us know if you have any further comments or concerns sincerely, the corresponding author's name. And if you're if you're more than one author, you have to say on behalf of all the authors because you're representing all your other authors. And then your city in which, in which your institution is and the country. Okay, so that's the cover letter. The next part is the abstract. In other words, the abstract is the short summary of your paper. And the abstract basically consists of four parts. And this varies from general to journal, slightly, sometimes these different names, but it's basically the same. So you first have the aim or the background. This is where you say what you intend to do than the methods and materials. So all the things that you used, some microscopes, maybe some imaging. I don't know. All those things and how how you did what she did, and then the results and conclusion, pretty self-explanatory. So this is an, an example of an abstract. So you can see basically the background, the methods and results and the conclusions. So over here you can see that this journal chose to have the methods and results combined. And this example. And there is an unstructured abstract. So you can see that there's just a bunch of text without any introduction. I mean, without an aim or materials and methods. And some journals prefer to have an unstructured abstract. You just have to find out what's your general prefers. But even though it's unstructured, all the information is still there about the aim, about the methods and materials, about the results and the conclusion. So whether or not you need to label it is up to the general, but all the information still has to be there. Alright. Next up is the title page and the title page. Of course, you need the title and the running title, which was just a shortened version of the title. And then all the authors with all their affiliations and degrees, and then the corresponding author and the keywords. And you might be confused because sometimes I've mentioned corresponding author. And the corresponding author is basically the author who is going to finally submit the paper. That's what it means. The corresponding author is a person, is only one author that submits the paper to the journal, and they're responsible for keeping contact, keeping contact with the journal. So all communication goes through the corresponding author. So you have to basically find someone who is responsible with checking their e-mail all the time. So I mean, once a day should be enough, but yeah. Okay. So this is an example. I wrote just a sample template for you that you can copy or are used when you're writing your own title page. So over here we have the title. So tables are better than chairs for setting on double-blind randomized trial. Obviously, this is not a real study. But okay, so the running title is just a shortened version. So tables are better than chairs for sitting on. So I basically deleted this double-blind randomized trial. Each journal will have recommendations and guidelines on how long a title is supposed to be. So you can check your journal, make sure that you're complying. Okay, then the authors. So here are some authors and you can see that I have MD or PhD. Make sure you add that if you have a MD or PhD. And okay, there are a couple of things you can see. First of all, you can see this asterisk right here circling, they're circling it there. So you can add this asterisked for asterix. For example, if you want to signify the two authors contributed equally to the manuscripts. So in this case, both authors, since they contributed equally to the manuscript, they are both first authors, right? So first authors are the ones that contributed most. But if two people have contributed, contributed like an equal amount, they're both considered first authors and this is how you write it down and intelligence. Yeah, your birth first Authors, affiliation. So over here I have these numbers, so one to two, okay? So this basically shows your affiliation. So your university, your department, your university in the country, and then the actual address of your institution. This is not your home address. This is the address of your institutions. So the hospital or the university or clinic that you are in, that's the address, not your home address. Some students get that confused. Or if you're in a student's scientific circle, you can write that down and then also write down same thing, your university, your country, and also the address of the university and in this case. And then you have to make sure to write down very clearly the corresponding author. So I always put another space here and put corresponding author, John Smith. And basically write down the same thing, write down where they're from. But also you'll have to write down the email that's very important. And this is the email that you should be checking every day after it's on your paper and also your phone number. They basically will never call you. I've never had someone call me, but they always ask for it. So anyways, you can put that down. Also. They sometimes ask for the facts, but They never have. Nobody basically is as a fax machine nowadays. And all the journals I submitted to have never asked have never communicated with me over facts, although they sometimes ask for a fax number. And anyways, Last but not least, you can see at the bottom the keywords. In this case I put tables, chairs, setting. The keywords are just so that the journal can index your paper so it makes it easier to find. So if this paper's about tables being better than chairs, double-blind randomized trial. Well, your keywords should probably be tables, chairs, you know, things like that. Okay, now is the manuscript. This is the meat of your submission. This is what people are gonna read. And so this consists of almost the same sections as the abstract, except it also has this part called the discussion. So introduction methods, materials, results, discussion, and conclusion. So the introduction, the discussion is basically where you are going to compare your article to other articles. I'm going to have a separate lecture just for the parts of the manuscript. So you can look forward to that. I'm just going to skip this for now, but just know that there are some there are five major parts of manuscript. Okay? And then for basically any journal, You'll have to state if you have any conflicts of interests or financial disclosures, you as a student or as a young doctor, are probably not going to have any conflicts of interests or financial disclosures. But for usually older doctors that are being paid by a certain pharmaceutical companies are about, are being paid to write for a certain company, or if they're paid at all in any way or have any kind of financial relationship, even having stock in a particular company which maybe a pharma company or another company where the findings are important or, you know, it could be important, so that's where you have to write it down. But for your case has just put none reported because you probably don't have any. The acknowledgements is where you say any names or any people that helped you but didn't make it on your author list. So basically, if you have somebody supervising you, but they didn't actually help write anything. They didn't help editing anything. They didn't help with giving, giving you tips on what to write, how to write, finding a journal didn't help in any part of the process. They shouldn't be on the author's list but they should be on your acknowledgements. Also, anybody helped you with that or no. If you are taking some imaging, some x-rays, if there was a lab technician, you can say, oh, this lab technician, thank you for facilitating these things for the study. And if anybody just helped with the language editing, only with the language editing and not editing the actual contents of the paper. Like making stronger arguments. That would be considered maybe more of a author contribution. But just language editing would be considered. You would consider them for just the acknowledgements and the references. For the references, you will use Mendeley. Mendeleev's a reference manager which makes it really super easy to have all your references and a really nice, And in the correct format. I will tell you about Mendeley and a separate lecture on how to install it and everything. So don't worry about it now, but I just wanted to mention it. And for the references, Charlie's original studies and not blogposts or newspaper articles. Obviously, sometimes you'll have to use newspaper articles or, or other, other, other websites or resources that are not original studies. But try to use original studies, right? And also, just because he give a reference, does not mean if you, if you directly copy and paste a sentence, you still have to put it in quotation marks. It doesn't matter if you give the reference. You have to give the reference and put it in quotation marks. If you copy the sentence word for word. Now, if you're paraphrasing the findings of a particular paper, fine, that's okay. You don't have to put them in quotation marks, you just have to give the reference. But if you give a direct word for word quotation, you have to put it in quotes. It might sound obvious, but some students get confused by that. If you're giving the reference and you don't need to. But yes, he always knew to give quotation marks if you're copying word for word. Ok, one more mistake. Commonly encounter is that students will reference a review article. Or review article as you know, is when an article looks at, you know, hundreds of other papers and gives a summary of them. But you shouldn't reference or review article when you're talking about a specific finding of a particular article, tried to reference the actual original article. And if you're giving the overall findings that are review article has made, then you can give the reference for review article, but usually try to actually reference the original article when it's possible. And for almost any journal, it varies a little bit, but the limit is usually about 50 references for original papers, for review articles, it's usually a little bit more like maybe 75, but for original papers or the maximum limit is 50 or sometimes 45. Obviously that depends on the journal though. So you have to see alright, so that's it. Those are the parts of an article and I'll see you in the next lecture. 13. The order of writing a scientific paper: overview: All right, so welcome to section three of the course. If you've come here, this means that you've already written a letter. So first of all, I want to congratulate you. And second of all, all right, let's move on to something bigger. I'm going to teach you how to actually write a scientific paper and original paper, erotics. Let's get started. So you probably know at this point the order of the final paper. So that's gonna be your abstract, your introduction, your methods and materials, your results, your discussion and conclusion. Okay? But higher actually going to write the paper is going to be in a much, much different order. You actually, when you're writing, you're going to start with the results. Why are you going to do that? Well, if you start with the results, well these days, there's a bias for publishing studies which have significant findings that have really cool, innovative, novel results. So if you come up with results that are not that novel or you have only negative findings that are not that cool. Well, sorry to say, and it shouldn't be this way, but your paper's going to be very, very difficult, if not impossible, to get published in a good PubMed indexed journal. So you're going to start with the results because if he got good results, then you can continue on and write the rest of the paper. But if your results are not great than okay, you'll say, maybe I won't go down the path and actually write the whole paper. So anyways, when writing you start with the results, then you go on to the methods and materials. Now that you have the results, then you're going to explain how you actually obtained the results. So it's a backwards approach, but this is how you should do it. And then only after that you should write the introduction. And remember the introduction gives you a nice introduction of what the topic is and we'll discuss more about this later. And then the discussion and then the conclusion. And only then the abstract. The abstract is the first part of an article, but it's the absolute last part that you, right? Alright. So when you're starting out, you should probably go and start out with ethical committee approval, right? Because to do many studies involving human subjects, you need the approval of your local Ethical Committee. So if you have any study involving people or the information, even if you have just questionnaires asking people about their experiences or their preferences, you still have to get ethical committee approval. If you're not sure if you're like, I don't know if this really requires ethical committee approval. You can just call your local Ethical Committee and ask them and then you'll know absolutely for sure. Alright. I'm telling you to get started with this early because obtaining approval may take several months. It depends on how many well, how busy they are. In my case, in my personal case, it usually takes about two months. But you can call them and you can ask them, hey, how long will it take? How busy are you right now? And they'll tell you. But keep in mind that it'll take it might take several months, two months in my case. Okay. What does what kinda studies do not need? Ethical committee approval. Well, those are studies with only publicly available data. So you're basically analyzing data that's already out there in the world that does not require official approval. So for example, if you're analyzing data from the Center for Disease Control and the CDC, the WHO, the World Health Organization, or Google Trends. You know, these, these places gave a lot of cool epidemiological data or, or online internet traffic data or things like that. If it's already available, then you don't need to obtain any approval. Alright? So the results, you're going to start with the results. So what are you gonna do with this? Well, you're going to give the relationships and overall trends. You're going to try to summarize most of your data visually. So in graphs and the stuff that you can't put into graphs or other illustrations you're gonna put in tables. And then why? Why do you want to put most of your information and graphs and then tables because graphs are easy to look at. I mean, you look at a graph and you immediately understand what's going on. So when they say a picture says a thousand words, it's true because I would rather look at a graph then read a whole paragraph of information and I think you would too. And tables are giving a lot of boring data, a lot of numbers. Of course you don't want to read a lump, a bunch of numbers in a paragraph, so you just put them in a table and have them all neatly organized. Alright? For most studies you're going to have many different parts. So I recommend dividing your paper into many subsections with headings that way it's organized and it's easy to refer too easy for you and easy for the people who are going to be your paper. And I think what's the most important is to make it friendly. So for example, if you are saying, I don't know, over, I don't know some value some value increased from 142 to 381. Obviously, these numbers don't really mean that much to me. So to make it friendly, you can say, oh, this increased from 42 to 381 is a 168% increase. By giving the percentage, you can make the increase a little bit more tangible and easy to understand. Alright, so continuing with the results and during the Results section, and actually during the paper, whenever you say significant, significant in normal English means, oh, this is important. But in your results section, especially significant means statistically significant. So if your p-value is 0, less than 0.05, basically if you're saying something is significant, you're saying that the p-value for this is less than 0.05. So in other words, what is the, what is a p-value? If it's less than 0.05, that means that there is, in this case, a 95% chance that this was not a random finding. Ok, enough of that. So let's continue. No explanations. What I mean when you're in your results section, you're only going to give the dry data. Maybe some figures and tables. You are not going to give any explanations for why you have that data for. So for example, if you have an increase of I don't know, some value, you're not going to give the explanation for why you have the increase in your discussion section. You're going to explain why you have those results that you have, but not right now. Okay? And the result section, you should have all the data include, including the non-significant findings and the negative results. So the positive results and the significant findings or you know, the cool ones that you're going to highlight, which also have to give all the negative results and the non-significant findings, right? Even though they're boring. And let's say your paper, your data is just really, really huge and you can't seem to fit all your data on figures or tables. Well then what you can do is you can add a supplementary raw data file. So basically an Excel file with all your, all your data. And you can make it available as like a supplementary files. So when people view your paper online, they can download the Excel file if they really want to look at all your nitty gritty data. And that's great to include your supplementary data because then other scientists will gain more confidence in your findings. Because if you're including all your raw data, you're showing hey, I have nothing to hide. You can see exactly everything I did right from the beginning. So that increases the confidence and that's good for you because that means that more people will trust you and believe your findings. Okay. The methods and materials section. So that's the second thing that you are going to do. And this is you need to give the information, information to replicate the study. And a lot of people including myself, sometimes don't do this part very well. Because when I say replicate the study, that means anybody should be able to replicate the study. So things should be very objective. So if you have a method, it should be that you can explain it and then your friend can do it. And a person around the world can do the same study and analyze it the same way. So if you have a very subjective method of analyzing something the way only you analyze it, okay? It's not a great study because people are going to analyze it differently. So you need to say exactly, for example, if there's a radiological image, you need to say exactly how you analyze it, what you are looking for. And you need to give any scores that you maybe use or any criteria that you use to analyze the data. Okay. Use subheadings. So and the methods and materials section, it's going to be very long and there's going to be very boring. And so it, it's good, just like in the Results section to break it up into, for example, inclusion and the exclusion criteria, the experimental protocols, the statistical methods. So that way it's much easier to read. Alright, the introduction. Now, you're going to give a concise review of your topic and you should follow what I call the three paragraph KKK format. And I don't mean to offend anybody, this is just a way that you can remember how to write it, hopefully. So the KKK format, so you're gonna have three paragraphs. And in your first paragraph you're going to talk all about the information that's already known. So. I don't know if you're talking about stroke. You'll talk about the information of stroke that's already known. This many people have died of stroke. I don't know. These are the imaging things that are used. Okay, then you're going to talk about unknown. Maybe there is a great imaging method, but we still don't know if it can be used for I don't know. Hemorrhagic strokes. I'm just pretending here. Okay. And then the third paragraph, you'd say how clinically irrelevant. So in our example you can say, okay, if we figure out this new imaging method, you know, people with hemorrhagic strokes would have a better prognosis or we'd be able to get to them faster faster imaging method. I don't know. So you need to say why it's clinically relevant and the purpose. So just to summarize, you start with a known, then the unknown than how it's clinically relevant. Obviously, I know this is misspelled, but this is just for the mnemonic. Ok. And most importantly, don't in introduction, you don't answer the research question. See you leave it a mystery, right? You don't want to tell the person right from beginning. Give them all the beans and tell them exactly the conclusion of the study. No. You want to hold the suspense and make them wait for it a little bit, a little bit longer. So make them wait for the results actually get the answers to the study. All right? The discussion, the discussion is usually for students the hardest part, right? And it was also for me in the beginning, one of the hardest parts, right. Because there's just so much that goes into it. But if you break it down into the six parts, I promise it has helped me and helped the students that I teach. So this is how you do it. You start with the key findings. The key findings are, well, what you learned in this paper, what was significant and how it's clinically relevant. Then you go to the context and this is going to probably be your biggest section. This is when you're going to compare your study with other similar studies in the past, right? And then the limitations. This is usually going to be a paragraph, and by the way, it's obligatory to have them limitations. Every study has limitations. And if you don't include the limitations, it's it's a very for me, I would see it as snobby because every single study in the world there is no perfect study. Every study has limitations. And if you don't have them, you know, the reviewers are going to be skeptical to say the least, ok. Then the future outlook. In this future Outlook section, you are going to talk about the future directions that other researchers can take and that maybe you will take to explore this topic more. And then the clinical implications. Why? Why are your findings important? Will they change clinical medicine at all? Or will they change the world or, or change how we approach things? And anyway, you're gonna give a really high level, big picture sort of conclusion here. And then of course the conclusion and sometimes the conclusion as part of the discussion. And sometimes the conclusion is a section of its own, but basically just depends on the general. But yeah, the conclusion you'd give the take-home message and you're basically going to be repeating the main finding. Ok? So that's that the conclusion is quite short. It's 2-3 sentences, and sometimes it's a section of its own. Sometimes it's not, just depends on the journal. Alright? And lastly, you're going to write the abstract. So after you write your entire paper, you're gonna go to the Abstract and you're gonna give a shortened version about your paper. So the abstract is actually out considered the most important part of the paper because scientists are going to be reading your abstract. They're not really going to be reading your paper. They're not going to have time for it there first. I mean, they might have time for it after they read the abstract, but if they read the abstract and they don't understand it or they read the abstract and the, you know, the findings don't aren't clear or they aren't novel and you don't show your best foot. The paper, all your work is gone out the window. So make sure you abstract is polished. And it really highlights the main takeaways from your paper. And the abstract is short, usually journals, every journal has their own limit, but it's usually about 200 to 300 words. So really make every word count in your abstract. And the abstract is separate from the manuscript. And of course it's going to show the most important parts of your paper. One common thing that I have been guilty of, which I have to work on sometimes is the abstract and a manuscript should not have repeating sentences. So for example, you might be tempted to repeat your conclusion from your manuscript word for word in the abstract, right? You did all that. We're a work writing great conclusion. And he just want to copy and paste it into the abstract. You shouldn't do that. You should write the abstract. Would not, at least not the same exact wording. It should be a little bit different. Alright, so I hope that gave you a good overview of not only how scientific paper is structured, but how you should go about writing your paper. You start from the results and then you go all the way to the abstract. Alright, see you in the next lesson. 14. Results: All right, so let's talk about the results section. So I want you to think of the results section as the figures and tables section because they tell the essence of the paper. So before you even start writing down your results, I want you to look at the data that you have, and I want you to try to make figures and tables out of them, right? Why are, why am I putting such an emphasis on the figures and tables? Because when people read an article, they first read the title than there were the abstract, they skim over it, and then they just kind of go over the manuscript and try to see the tables and figures. And then they may be read the manuscript. But the figures and tables are telling the story of your manuscript. They're, they're saying what everything is about. So make sure you focus on those because that's really the gem of your paper and everything else. Everything else in your papers, actually just showcasing your figures and tables, including the rest of your written results. So there, yeah, as I said, they're showcasing your figures and tables. Now. Some tips now we're actually going to go through tables and figures and how to do them. But some tips might, my biggest takeaway, I would say is less, is more. Only have figures that are crucial. Don't have figures that are kind of important. Note only have figures that are important and that are critical to your aim to answering your research question. And each journal has maximum limits on the number of tables and figures. So make sure you look at that before you actually start making yours. And last but not least, each figure or table, it should stand on its own. So it shouldn't have to be the o I look at a figure and then I have to read a whole paragraph to understand what it means. Or I read, I look at a table and a half to read part of the paper just to understand that no, I should be able to look at the table. Everything should be clear as to what it is that I'm trying to say what it is you're trying to say right from the table and from the caption that you have. So some more tips. Pretty self-explanatory. The figures and tables should be numbered consecutively. So if it appears first in the text, it's numbered figure one and figure two. So each figure and table requires its own title and an each title, there should be no abbreviations. And if there are abbreviations, you explain the abbreviations, right? In formatting of the figure or the table, it's always a good idea regardless, to go to the, go to your target journal and just look at the tables and figures and see how they're formatted, how they look. And then you can get ideas of your own of how to make them for the particular journal that you are submitting to. All right, so one last technical detail on a table footnotes sometimes. And this depends on the gentle, but this is a standard sort of flow. If you need to point out things in the table, you use the asterisk and then the dagger and then the double dagger and so on. To show whatever you want to show, for example, a p-value. I don't know. So here's an exercise. What's wrong with this table? So just look at this right now. Take a moment, take a pause, and maybe pause the video right now, and just try to see what is wrong with this table and what you would change. I think. I think the first thing you probably think, oh, these are, you know, these values here are not aligned. Or maybe you're confused about what this S is over hair. But try to find out on your own. So I'm gonna take a little pause. Okay, I'm back now and I'm going to give you the answer of what's wrong with this table. So they're actually a lot of things wrong. First of all, there are way too many gridlines. Proper table should not have all these grid lines. There should only be three gridlines. So in this table, this is the right way of the table. You only have three grid lines. This one on the top, on the bottom, and then at the very end. Alright, so let's go back here. So too many gridlines and then there's no table label. You always need to have a label that describes what your table is all about. So this is the correct version. Over here we have table one, it's labeled and we have descriptive characteristics of study participants. Right now everything is labelled so you know what it is. See you don't have to reference the text. Remember I said that the table should stand on its own and show it so should the figure. Alright? And then inconsistent capitalisation. You see that everything is capitalised like woman. But then men isn't capitalised, right? Or a doesn't capitalize. So these things, if you're reading a paper, this is just unprofessional and it, it gives a bad taste to your paper. If these see these sorts of mistakes. And then we have, of course, no units. This is a big mistake and a common mistake. For example, age might be obvious, right? Oh, the age should be in years, but it might not be in years. You know, if you're doing a paper on pregnancy, it might be in weeks, it might be in months. It might be, I don't know, in seconds, probably not, but of course it could be in years, so you have to say what it is. So in this case, we corrected it and we said years. Alright, then it's misalignment. I think this is, this was pretty obvious. Of course this is centred and then this is to the left. So of course everything should be aligned to many decimal places, okay, right here, look, look at the age. This is the mean Age. But there are way too many decimal places here, here and here. Also, also right here in this row, there are way too many decimal places you don't need to have that many stick with, I would say three significant figures or whatever it is, depending on how accurate your measurement tool is. And stick with those. So in this figure, we see that, okay, it's consistent. It's to one decimal place and it looks much neater. Alright? The abbreviation is not defined, right? So here, as you might have other abbreviations, This is a small table, but you always need to say whatever your abbreviations are and enlist them. So over here we have abbreviation S, smoker. This is a correct version, right here. We have. Everything there. And then there is no standard deviation nor percentages used. So obviously, if you're going to have an age like we have here, and we have a number, that's the mean. But of course, we should have also the standard deviation or the percentage if it applies. So in this case we have smokers and we should have some kind of percentage. Just see oh, really quickly, what percentage of those men are smokers? So in the corrected version we have 0, 7%. Of course. These are just random numbers, so if they don't make sense, that's, that's totally possible. So we have the percentage here and we have the standard deviation here, and also in the title of the paper. So table one at the end we say means plus, minus standard deviation or percentage. So the reader knows exactly what this is. They don't have to guess that this is the standard deviation. They know it and they know it right there. Okay? And last but not least, there are too many columns. You have the main column, the woman column, and then we have the p value column. But actually we can take the p-value column away. How do we do that? So in the corrected version, we have men and women, but, oh, where did the p-value column go? Okay, so what we did is we used this asterisk, asterisk. So we have it over here. And then on the title of the table, we have a space and then it says O P values less than 0.05. So in this way, we can really, really neatly put everything down, including the p-value and make it look just a lot more professional. And this'll, this'll be really great for you because while your peer reviewer or whichever editors reading your paypal, they'll say, okay, well, this is a great table. I'm understanding everything and this is professionally done. These guys know what they're talking about. These guys are real scientists and that, that's what you want. You know, you want to pay attention to these small little details because it does make a difference. Okay? So we talked about tables. Now let's talk about figures. So figures, this is quite a complicated topic because there are so many different types of figures and there's so many different ways of representing your data. So this is more of an art form, but there are three basic types of figures. They are the real images like for example, X-rays, pathology slides, or actual. If a patient has some kind of disease that you can see you on the skin, you know, this is popular for dermatology journals. You'll just take a picture and you'll have it there so you can see. So these are the real images then you have your graphs and this is what we typically think of when we think of figures. These are your bar graph scatter graphs. I don't know so many different types of graphs. And then you have your diagrams. And diagrams are used a lot for anatomy, drawings of anatomy, aneurisms, things like that. Cause and effect and flowcharts, especially for systematic reviews. Diagrams are for systematic reviews their golden because they take a lot of boring information that you would have to have in paragraph form. And they put it really nicely on the table. Alright, so let's look at some examples. So for graphs, and graphs are great, but there are some distinctions that should be made between them. So a bar graph, line graphs and scatter graphs, these are super popular bar graphs are for one time point. And so if you're looking at one specific time point and you're not moving, looking at different dates. Bar graphs are great. Then line graphs are for trends. So over time what happened, right? And scatter graphs, sometimes you use best-fit lines. They show relationships and kind of have to see which figure fits best with your data. So in this example, we actually have a bar graph and they're showing something happening over time. In this case, the number of publications over time. For a particular thing. I think this is a Google Trends papers over time. And now you see that, okay, it's rising, but because It's showing time passing and it's showing a trend over time. I would actually prefer a line graph rather than a bar graph, but they used a bar graph. Okay, that's fine, but I think a line graph would be a lot better. All right, let's look at another example. So here we have a diagram, and this is from a systematic review. And I think this is an amazing diagram. And generally for systematic reviews, it's a great diagram because you have all the papers, you know, you have a hundreds of papers that they had and have the system of how they screen the papers, have full text articles were there and then, you know, that took some away and then they included some. So this is such a great way of representing your data. If you're doing a systematic review, you better. Or I really recommend that you make a diagram. Alright? But diagrams can also be more like drawings. So here we have a map and looking at different statistical approaches or methods all over the world. Alright, so I hope that was a good review of the results section. Remember, your results are actually your figures and tables. So do those first and do everything else later. Because every, your tables and figures are the essence of your paper. Alright, that's the end of this lesson. 15. Methods and materials: Okay, moving on to the methods and materials section, or should I say the who, what, when, where, and how section? Because that's really what you're saying. How did it happen? What happened? I want to be honest with you, this is the most boring section of any paper. But in a way it's good because it's quite easy to write. You're literally saying what you did. And it's just the info to replicate the study. So for this section, I recommend that you use subheadings because that makes it not only easy for you to organize everything, but also easy for the reader because they're really not going to be closely reading the method section. There more just going to be skimming through it. How did this, this, this happens, so it makes it easy for them. And so you're going to use references. I recommend you use references for commonly used methods and just write down like, oh, the images were analyzed as previously described and then you just give the reference and use diagrams. This is the most boring section, so I recommend you use diagrams. You make it short, you know, by using references to other common methods that are the same. This is great if you're especially during follow-up studies and you are basically using the same methods. Alright? So N, the methods and materials section, you need to state, you need to have a formal statement that basically says ethical approval was granted. And usually you'll have a number that they gave you once the ethical approval is granted and you just copy and paste that there. And then of course, all the equipment with all the information about the model. So if you use, I don't know, some microscope, you have to say, you know the XYZ model. Or if you have a microscope of the extra lens, you have to say, oh, the microscope with this particular lens. So be very specific about all the things that you use. And that applies also to the statistical programs. For example, if you're using Microsoft Word or statistics or IBM software, you have to say not only you know, Microsoft Excel, but you have to say the version. So version, I don't know, 3.8, I'm just making it up. And then also the statistical tests, so Chai squared Student t-test, all those things. So here is an example of a randomized trial, and I just copied, copied and pasted. The citation is at the bottom. I copied and pasted the how they set up their methods and materials. So they started with trial design than the participants then randomization, allocation, concealment and blinding than the interventions, the outcomes, the sample size and the statistical methods. Pretty much every papery ever read is going to end with statistical methods. Leave the most boring stuff for the end. I think, I think that's a good way. Alright, and as we said before, for the methods and materials section, you want to keep it concise and as not boring as possible. Super boring treats. So if you can use a flowchart to show how exactly the study was done. As I said before, this is a great for systematic reviews and also for trials. But yeah, so use flow charts and diagrams and tables wherever you can. Alright? And then for the language, this is important and point of confusion for some of my students and it was for me also when I started. So I told you that you're supposed to use active voice first of all. But in the methods and materials section, you can use passive voice. Why am I saying this? Because active voice is, well, first of all, it's more entertaining to read. It's fun. It's more fun to read, right? So, but the methods and materials section is all about what you did. And passive voice is going to emphasize what you did, not, who did it. Active voice has gone to emphasise who did that thing. And it's more entertaining. But in the methods and materials section, you can use passive voice. Now, if you want to use active voice, Sure, you can use active voice, that's fine. Or you can use a mix of passive voice and active voice. But I recommend just using mostly passive voice. Also because people aren't going to be closely reading your methods materials. That's mostly, they're just going to skim through it really fast. Alright? And then for the language, you're going to be using past tense for most of this section because we conducted or you did something. But what's not going to be past tense is the data. So if you're saying what you did, you use past tense and if you're showing where the data is, the data, the data are summarized, it's happening right now, it's still there. It didn't happen before. You're looking at the data right now. So it's there right in the present. Alright, so that's, that's how you write the methods and materials section. And I'll see you in the next section. 16. The Discussion and conclusion: Alright, on to the discussion section. This is probably one of the most exciting sections for you because you really get to be creative and you have a little bit more freedom to write. It's not so constrained as the rest of the paper. Now, that might mean that it might seem a little bit more difficult. But if you take the outline that I have for you, I think the discussion section will also be your favorite section to write. Alright, so basically, when we're writing the discussion section, we're gonna go from specific to broad. So we're going to start specific at your paper, your specific findings. And then we're gonna go more broad talk about other papers, and then more broad Talking about the future, about the future of this topic and you know, whatever you're examining or researching. Alright, so in this lecture, what I'm gonna do is I'm going to tell you how a section is setup. And then I'm going to give you an example. And the example I'm going to give you is what this paper basically copying. This is an open access paper and I'm copying and pasting some of the discussion to show you how it might be written. So in this case, the example is YouTube as a source of patient information for coronavirus disease. Now I'm sure you guys, oh, what this coronaviruses at this point. But anyways, let's get started. So the discussion, as you might already know, has six parts. So those are the key findings, the context limitations that feature outlook, the clinical implications and conclusion. Obviously, this is my outline for how I would have it and the order for how I would have it. But you should include all these and a good discussion, a good discussion sharing could all these aspects. But, you know, after, after you start writing, you might, I don't know, you might change up, change these things up just a little bit. But I encourage you to stick to this order and the structure. Alright? So the key findings, what do you right here? This is going to be one paragraph where you start out with, we found that whatever your main findings, we found, you know, horses really like plants. I don't know whatever it is. And then he said, what does that mean? So a force is really like plants. Are they going to eat up all the plants in the world? Maybe you can write that down. Why does it matter? Because then our world wouldn't have any plants because the horses would eat them all. His findings are novel. You have to say at the end here. These findings are novel as our studies, the first two, blah, blah, blah, blah. Research horses eating plants, you know. So you have to say each study has to be novel. You cannot write a study where it's not novel. So, you know how I said that? You should start with the results. Well, he started with the results section because then you know, if your findings are significant, if they're new or novel, and then you can write papers. So in your discussion you basically have to say that your findings are novel because otherwise the channel will want to publish it or any, any, any respectable, bigger journal. Anyways. Okay, let's continue. So this is the example. So here, let's see what they write. They should start with whatever their main finding was. So did they do that? We found that the overall quality and reliability of each videos on sars coal v2 and covert 19 is poor, which indicates that the information about this disease on YouTube does not provide a comprehensive review. Okay, yeah, they do that. They write their main finding. We have included a table in the highest quality of the highest quality videos on YouTube as a reference so that people who may want to learn about coated May 19 use them as a relatively reliable source of knowledge. We suggest physicians and other medical professionals recommend these videos to the general population and feature them on their websites for a better understanding of covert 19. Okay. So they give their main finding and then they say how it pertains to real-life. Now physicians can actually recommend them to real-life populations. So now if a physician is reading this, they're like, oh wow, this is not just some random finding. This is applicable to my life because now I can recommend these videos, informational videos to my patients, right? So this is good. We also encourage Egypt content creators to use the discern scoring system as a guide to making better quality, unbiased videos. So not only is this, you know, does this, do these findings pertain to physicians, now they're even saying to Egypt content creators. So if you guys are, you know, YouTube content creators out there, this is also a good, alright. And here's this, the reference. Whenever, whenever a number is here, that's just a reference. Okay? Our findings are novels since our study. Okay, so great. They say If their findings are novel, alright, our findings are novels since our studies the first analyze the quality of health information concerning covert 19 on YouTube. Great data, state it. It's a fact, boom, easy done. Moreover, our results are relevant as our analysis was conducted just a few days after covert 19 was declared a pandemic. Are right, so that they fulfill everything they needed to that. Okay. Did they say what they found? Yes. That they explain what the data meant? Yes. That they say why it matters. Yeah, they said white matters to physicians and to Egypt content creators and that they say that the findings are novel. Yes, so this is a good beginning introduction. Alright, so now the next section of your discussion should be the context. And this is where you're going to compare and contrast your findings to other papers and other literature that's been recently published. Now what do I mean by recent literature? Well, it depends on whatever topic you're looking at. But usually Recent is in the last ten years. Now, if you're looking at a topic where there's not much published and maybe there hasn't been much hasn't been much going on in the last couple of years. Maybe then 20 years, 10-20 years. I wouldn't go back more than 20 years though. So yeah. All right. So you're going to also explain, have some explanations for your data. If possible. Maybe you had some findings that were strange or you didn't understand or something. And this is where you can actually say, oh, now, I have the explanation for why these findings were like that. I don't know. Maybe in our horse example, we were in some island on, I don't know, in the Pacific where horses eat plants, but those horses are just endemic to that island, you know. So that would be an explanation in that case. And okay, let's read the example. Contexts and our analysis. The news channels had a poor discern score, the cern score, this is just the scoring system they used for evaluating videos. So a low port a certain score would mean that the videos were not did not have great medical information about Coven. Anyways. Okay, let's continue these videos. Not only fail to mention the treatment and management strategies, but often fail to provide almost any medical information that we took into our analysis. Although their video claimed Title claim to. Okay. So they're just giving right now just a general overview of their findings. This is not really pertaining to other other papers. All right, so let's see what happens next. Okay. We assert that the covert crisis is not only a viral crisis, but also a Health Information crisis. Okay? So now they're taking their finding wish they hadn't, they're saying that, okay, you know, this was not great. They're saying the information is poor and now they're saying that this is viral, not just a crisis, it's the Health Information crisis. Alright, so recent studies have shown that Y dissemination of misinformation concerning the outbreak has created panic among the public. Ok, so they're giving these two references. So now I'm starting to see why they, why they said this. They gave this background just so they could come in and say how, you know, other, other studies have also reported misinformation across the web. Okay. Larsson at all has dubbed the biggest risk of covered 19 viral misinformation or right. So now, now I understand they were saying this so that they could add so they could reference other studies. Ok, thus, not only is there an urgent need to scale up public health measures, but also to address the pandemic of social media panic, endemism, misinformation array. So now they're saying, Look this information. We saw misinformation on, on, on these health channels, on these news channels. And this is a problem not only on YouTube but across the board. Other scientists have found this. All these references, people referencing misinformation or in this case pour information. This is, this is a problem not only in their paper that they found, but also in other literature. Okay. So did they have explanations for metadata? Not really, not in this case, but they did compare to the recent literature. Alright, limitations, okay. Limitations are obligatory. This is where you're going to make specific you're going to point out specific limitations of your paper, not broad limitations. So an example of a broad limitation would be that, oh, this was a retrospective study. So all the limitations of retrospective studies apply. And then you just list them. You know, you go on Wikipedia or on Google and just find out the limitations of retrospective studies and just let them know. That's a very, very broad way of looking at the limitations. You have to say specific limitations pertaining to your paper, right? You just give broad limitations. It's lazy and it's it really doesn't say anything. Okay? And then while you are saying limitations, you still have to prove to the reader that even though there are some limitations in your paper, your findings are still robust, that you can to some extent trust the findings of the paper. Ok, and so this is the place we anticipate the criticisms of the reader, of the peer reviewers, of whoever's reading, right? Okay, so let's see how they did in this example. Medical student readers as an unsteady, maybe considered unreliable raiders compared to physicians. Okay, so in this study basically the raters were the ones that watch the videos and rated the videos. Okay, so they're saying that their students, so they might be unreliable compared to doctors, right? Ok. However, the creators of the cern stated their instrument was not dependent on specialist knowledge of a health condition or treatment, and then they give the reference. All right, that's pretty good. They gave the limitation and then they give why their findings are still robust, right? Okay. Moreover, the intraclass correlation coefficient between the two raters was excellent and they give them, give a reference. Okay? So the intraclass, intraclass correlation coefficient is basically a way to measure how two raters, in this case, how their ratings matched each other. So if it's excellent, that means that the two raters evaluated the videos in pretty much the same way. Alright, so that means our data is robust, that's ok. Thus we assert that the medical student traders who each had five years of experience using the discern instrument while in medical school provided adequate results of the study. So I think this is a great example. They give the limitation and then they give why their paper is still robust and still worthy of looking into that their conclusions are real. Alright, so yes, they say this what their findings are so robust, there are limitations, are specific, not broad because this is a cross-sectional study. And they didn't just say, oh, you know, this is a cross sectional study. Whatever limitations apply, whatever they did have a limitation section. So that's good. It's obligatory. So they had one that's good. All right, so I think this was a good example. Alright, future outlook. In this section, you're going to say what is the next best step? Next. A step that other scientists can take in this area, or that you would take in this area and the future or or any confirmatory studies required or are there any remaining unknowns that need to be answered? So these are, you know, what are the future plans and this area. Alright, so let's look at the example, future outlook. In this case they titled The subheading future directions but whatever. Okay. Since sars call V2 and covert 19 or such relevant topics in the emerging pandemic, we encourage researchers to conduct a follow-up analysis in the future. Alright, boom, great. They give a very specific recommendation. We also encourage video content creators to user audience engagement suggestions and the discern instrument to assess their videos for educational content so that they may provide more robust information about the disease going forward. Alright, so let's see. They say what's the next best step in this area? Yes. Our confirmatory studies required. Well, they didn't say that confirmatory studies are acquired, but they did say that future follow-up studies should be done because it's ever changing, right? This COBIT situation, okay? What are the remaining unknowns that need to be answered? They didn't really say that there were any remaining unknowns. I think they could have added a little bit more to the future outlook. And I mean that they might have said, hey, what are the, what's the quality of information, not just on YouTube but on, on Google, on these new sites. Maybe that could be a future direction, right? Okay. Clinical implications or this is what you're going to basically end the discussion with. Why should anyone care that you have these findings, that you have this misinformation? And what do the findings mean to medicine, right? What does it mean to people clinically, to physicians, to people that are not doctors, you know, and you need to give high level implications of your findings. I misspelled this findings. Alright, so let's look. There are several simple yet effective steps that people may practice personally to prevent the spread of infection, such as washing hands regularly, practicing cough etiquette, and avoiding public gatherings. However, these reminders need to be promoted and presented in health content on YouTube so that people adhere to these recommendations. Absence of this information may result in higher health care costs for a country, increased risk for viral spread and higher hospitalization and mortality rates. Okay, well, so this says very directly that the information that the public has will lead to some, some pretty, pretty bad outcomes. I mean, look higher health care costs for a country, increased risk of viral spread and higher hospitalization mortality rates. So they're very explicitly saying why their findings are important. Yeah, so, OK, let's continue reading. We hope that this quality analysis serves as a prompt call to action to physicians and health organizations create more robust health content for viewers online. Alright, so I think they very well, very eloquently say why, why people should care and what the findings mean. Not just medicine, but they say overall and a public health way. You know what the findings mean and why they're important. The high level implications yet so in a very, in a very broad public health aspect, they say, you know, this will lead to increase viral spread, you know, when you have poor information. Okay? And last but not least, the conclusion. Now the conclusion may be a part of your discussion or it may be a separate section on its own. But whatever the case, it's just a technicality. And you can just look on the journal's author guidelines to see how they wanted setup. But anyways, the conclusion is where you summarize your main findings and you summarize the clinical implications. Basically, this is a take-home message. This is what you want your reader to remember, right? Okay. Lets read the example. The overall quality of each videos and sars Coby too and covert 19 is poor. Yeah. Okay. So they're basically repeating whatever they said in the first sentence of the discussion, which is good. This is the conclusion. You can repeat things, right? It's loud. Alright? Thus, healthcare consumers obtaining health information, uncover 19 on YouTube, or obtaining an incomplete comprehension. Okay? They gave kind of a high level summary of what their data actually means. Or this may lead to misunderstandings concerning treatment prevention and the general characteristics of the virus. Okay, so they continue with the high level. What their data means. We recommend that people verify the facts they learn on YouTube with more reliable sources of information like peer-reviewed research papers, healthcare professionals are online updates by the World Health Organization or the Centers for Disease Prevention and Control. We recommend physicians to refer patients to the list of the highest quality videos that we provided. If a patient wishes to use YouTube as a source of their medical information. Okay, so I think they did a great job because they went on to say that not only for physicians, why this is important, but but for people that they make specific recommendations, that they learn, more reliable information, check the WHO and CDC. And yeah, so I think this is a strong conclusion because they summarize your main findings. And they summarize the main, main clinical implications to people and physicians. Alright, so that is how you set up your discussion. That's how you can split it up. The discussion is a big beast. There's so many things that go into it, but if you use subheadings and break it down into smaller parts, I think it can be something really managed, manageable, and actually something really, really enjoyable because he gets read a lot of other papers. And you get to compare and contrast your paper and really see why it matters. Why did all this work you put in, all this writing, all that data analysis. Why does it actually matter to the world? And you get to write it down and make your argument. Alright, so I'll see you in the next section. 17. Introduction: All right, now we're at the introduction section. The introduction is a concise one page review of your topic and it follows this KKK format that I told you about the non NFO, the unknown gap, and the clinically relevant knowledge and purpose. And importantly, don't answer the research question in your introduction. Alright, so let's look at an example. So in this example, YouTube as a source of information on food poisoning. This is possibly a study that you could do yourself, so I use it as an example. So this is published in open access journal and you can access it so people, let's read it from the beginning. What I did is I copied the introduction, the paragraph, and I split it up just so it's easy to see on the screen here. So people are increasingly using the internet to access health information, okay? And it's quite convenient for people to obtain a wide array of health information. Okay, so the first paragraph or the beginning of the introduction should say what is known. So they are saying what's known. People are increasingly using the internet to access helping me health information. And it is quite convenient for people to obtain a wide array of health information, okay, the second line, and it is quite convenient for people to obtain a wider of health information. Okay, that's quite stupid. I think. Why are you saying that? That's such a broad statement? Alright, I would delete that if this was my paper. Anyways, let's continue. Iti represents one of the most popular social network sites for sharing your contact behind Google. Alright, great and great reference. Youtube was increasingly being used for health and health information and has a large community user-based that allows users to view, upload and download a free cost. Okay, this is great, but I don't think YouTube actually allows you to download at free cost. I USE too, I don't think it does, but anyways, let's continue and also communicate in common easily between the source of Upload and other viewers. But everything else, everything else is great. It describes YouTube even if you don't know it. And it gives the most important piece of information, I think right here, is that people are increasingly using the internet to access health information. Alright, so let's see how they continue. This first paragraph did what it was supposed to, it gave what was known. So the next paragraph here we are. It's just supposed to say what is unknown. So let's see if it accomplishes that task, right? So however, using the internet for health and medical information has a variety of disadvantages, including disorganization, complex medical language, and lack of peer review. Ok, so now they're starting to introduce a problem. Now there is some kind of problem here. Therefore, it is essential to assess the quality of the information delivered. Okay? To our knowledge, no prior studies have examined the availability of food poisoning education videos on YouTube. Boom, this sentence right here, it says why their study is necessary. It gives the gap in the knowledge. It says what is unknown. They say that first of all introduce a problem. That YouTube videos have a lack of peer review. You know, you can pretty much upload anything. And then they say, alright, no study has actually examined the videos on food poisoning on YouTube. So we have no idea if they are, good videos are not, I mean, medically good videos if they have good medical information on them. So now we have the gap in knowledge. This is the unknown, uh, right? Now. Let's see the last, last part of the introduction. Alright, therefore, the study aims to systematically assess the usefulness of YouTube videos regarding food poisoning for improving the professionalism of video websites. Okay, this is pretty good. But what I think would make this last part even more clinically relevant, right? Because the last part of the introduction is supposed to make clinically relevant. It, I mean, they say, it's also supposed to say like give you a broad overview of what you're going to do, right? So in this case they say, okay, they're going to systematically assess the usefulness of YouTube videos regarding food poisoning. Great. But I think what could make this introduction shine is if they said and gave a reference to a study that proved it. If they said something like 74% of people in America, US, and trust YouTube as a source of medical information that would make the introduction shine even more because then as a reader out be like, wow, it's, I would understand how important it is to do this study and to be aware of the study so that, so that we know the information on YouTube. Because if, let's say the study finds that the YouTube videos, the medical knowledge of YouTube videos concerning food poisoning is horrible and there's a lot of misleading information, then I would as a doctor, I would have to know about that so that I can make sure my patients, especially my younger patients, who watch YouTube videos and access health information online that I tell them and inform them about food poisoning, right? So, but overall pretty good introduction. And here's overview. I highlighted the most important sentences that I think are the most important. So over here You Ci was increasingly being used for health and health information. Okay, right, that's a good sentence and a reference. And this is what's known, and this is the gap in the knowledge. So no prior studies have examined the availability of food poisoning education videos on YouTube, right? And last, how they did the study. But I think they could even make it more clinically relevant. But anyways, the study aims to systematically assess the usefulness of YouTube videos regarding food poisoning. So there you have it. That's how the introduction is structured and that's how you want to write your introduction. Alright, see you in the next section. 18. Abstract: For the abstract, you wanna pull out the highlights. So you've written your paper and at the very end I want to write the Abstract and pull out all the important parts so that people can read the abstract, which is, you know, first part people see and they're like, wow, this is an amazing study. Look at these crazy findings. Alright. So the abstract, as I just said, is the initial impression. It's short at about two to 300 words, depends on your journal. It's separate from the manuscript. It's the most important part of your paper and it has the most important parts. And most importantly, the most read write. So this better be shining. You better read over this 2-3 times over 23 days just to make sure everything is Pitch Perfect and it's just goes smoothly, right? And importantly, we abstract in the manuscript should not have any word for word repeating sentences. So when I say, you pick, you pick the most important parts, you do pick them, but you try not to copy sentences word for word. Alright? That's been, that's been one of my problems. But anyways, alright, now the parts of the abstract is the background. Start with that, and then the aim and purpose. Now eat journal that have slightly different versions of these slightly different names. It might be the purpose, or they might label it the aim, or sometimes the background and aim or purpose or sometimes combined. So you just look at whatever your journal wants you to do. And then you have materials and methods, results, and conclusion. So then we have our aim and purposes. The first part, right? Our aim was to him and he just write your name or we speculated that or hypothesized that. It's pretty easy. It's just one sentence giving your aim or purpose. And before that, as I said, you might you might give one sentence background depending on the journal. Okay. And then you have your materials and methods. You want to answer two questions here. How did you gather data? And what were the main statistical tests used? Now, of course, it depends entirely on your manuscript. If you have a different type of manuscript, this might not apply, but you wanna give the basics of your paper, whatever the basics of your paper or that's what she give you are not going to list all the materials that you used here, just, just the big broad things and the results, the most significant findings. So you probably have positive findings and negative findings. You're gonna give the findings that are the most, wow, that fit your paper, not any secondary findings. You want to give the best parts right up front. You can give a few numbers, percentages or P-values, but try not to overdo it. Alright, the conclusion that the big sentence is going to say, was the aim achieved? Did you achieve it? What did you find out? So one sentence with that, and one more sentence with why people should care. So basically why they should care is, and Madison, How is it steady, clinically relevant to physicians, to patients, to medicine at large or the public health or whatever it is you're trying to achieve. So pretty, pretty short, pretty easy. Once you've written your paper, don't try to write your abstract first because then it'll be super hard. Okay, so here's an example. This is a structured abstract. You can also have a non-structured abstract, but okay, so we can see pretty short. Basically they give one sentence background and you know, here and then the background and Amer or together. So here they say the effect of dapper, dapper go flaws and patients with chronic kidney disease or that type two diabetes is not known. So the effect of this medication is not known. Ok. And then they tried to find out the effect. And over here you can see in the results section they do give some numbers like Ci over hairs confidence interval. They give some p-values less than 0.001. They give some percentages. Over here. This is a clinical trial. So in this case they would give a lot more numbers than, than usually. And the conclusions they gave OK. among patients with chronic kidney disease, regardless of their presence or absence of diabetes, the risk of composite of a sustained decline in the estimated GFR of at least 50%. End-stage kidney disease or death from renal or cardiovascular disease causes was significantly lower with depth of flaws than with placebo. Ooh, there we go. You answer the main question. Honestly, that's a really, really long sentence. I would try to shorten that up if I was writing that down, because that's a very difficult tree sentence. But yet there you get the point they answered domain name. And because this is a clinical trial, I mean, the sentence itself tells you how relevant it is like, okay, now you can use this dab, dab Gullah flaws and you can use the drugs. It's kind of self-evident in this case, so they don't need to write down why it's clinically relevant. Alright, here's another example of an abstract and I just wanted to show you this because over here you have unstructured abstract or a free form abstract. Basically, if the journal that you submit to wants you to have a free form abstract, I want you to write the structured abstract and then just take away the labels because you need to contain all the same information. It's just some journals prefer you not to have those labels. Honestly, as a reader, I like having the labels because I can more easily read the abstract. Like if I want to just skip to the conclusion which a lot of people do, right? You can just do that. But with the unstructured abstract, you kind of have to read everything or it's difficult to skip. Anyways, that's how you write an abstract. See you in the next section. 19. Tackling peer review and writing the rebuttal letter: Tackling peer review, the rebuttal letter, the dreaded rebuttal letter. So and this module I'm going to teach you that it's not just what you say, it's also how you say it. So basically the take home messages be very polite. Whether you're agreeing or disagreeing. The reviewers are not paid for their job. They're reading your manuscript, they're doing it all for free. Putting in quiet quite a bit of time, usually more than an hour, and writing a very constructive response. Sometimes they're rude, right? But, you know, you gotta forgive, forgive them for that. And sometimes they actually don't make sense and their views are unfair. But you also have to just kinda try to put that aside even though your papers like your baby. So here I'm gonna give you some tips on on actually what to say and how to say it. So whenever rebuttal letter, you submitted your paper, now you get the peer reviews, peer reviewers comments, and now you have to change your paper according to their comments. And this is how you do it. So we're going to begin your letter with saying something like this. You're gonna say the author is would like to thank the reviewers for their careful review and constructive feedback. The manuscript has been improved according to the helpful suggestions. Right here you're saying two things. You're saying, hey, I know you guys you're acknowledging that they put in time right there, careful review which they did. Even if they didn't you say that he said, and the manuscript has been improved according to their helpful suggestions. So now you're saying it has been improved. So now, now the journal and the peer reviewers should accept the, should accept the paper because it has been improved. And then you go with, we have carefully considered the comments of the reviewers and would like to respond, respond point-by-point as follows. Okay, so you can start with that and you can end with by editing our manuscript according to their viewers, constructive criticism, we feel that our paper has been improved significantly. Alright, so you end and began with a positive note. And you kind of say it has been improved, you know, so now you should maybe accepted now. Alright, so in the middle is where you're actually going to comment and say, what do you changed according to the reviewer? Comments. So you can either agree or disagree and you may agree with certain points. And if you do you say that. So reviewer has suggested that are for example, reviewer two has suggested that our methods section being more detailed. Okay, accordingly, we have added a paragraph elucidating the inclusion criteria. So just for example, now the reviewer feels good. Ok, I have changed the manuscript and now it is better. Grape. Or if you disagree, you don't always have to change, you know, or do exactly what the peer reviewer says. If you politely disagree, they'll probably be okay with it. So for example, reviewer two has suggested that other populations be tested. We feel that this is beyond the scope of this article. However, we have added this idea to the future directions section of our discussion. Okay, so you see what you did in this, in this example, you disagreed. We clearly disagreed, but it made, you still made changes to the manuscript. So now, not only is your manuscript better because you have another idea and your future directions section. Now the peer reviewer doesn't feel that your, that their comment was just being ignored. So now they know that, okay, alright, it might have been too big for your paper, but at least your manuscript was changed and this has been added. So maybe other scientists can conduct whatever, whatever his comment was about other populations being tested. So in this way, you have more of a constructive response. And this, I can say in my case, if you're polite and you give very good responses, constructive responses, it, it will be good for you. So here my tips and I'll see you in the next lecture. 20. Authorship: Okay, so let's talk about authorship. So there are some different terms for the different types of authors. So you might have heard about first author or lead author, and this is basically the first name that appears on a list of authors. Then there's the corresponding author, which I've mentioned before. This is the author that's going to actually communicate with the journal when you're submitting your paper and doing any revisions. This is the author that's going to have all communication. So as I said, this is somebody that needs to be checking their email daily. And then there are the co-authors. And you can have many co-authors. These are the names in the middle and then there's the senior author. And the senior author is usually the last author. And more often than not, this is the head of a department or the professor of the Department, whoever's in charge in whatever department you're working at. And alright, so there are four conditions for authorship. This is according to the uniform requirements for manuscripts submitted to biomedical journals. So I literally just copied and pasted it from there. So here we go. So control, so you know the four conditions and you have to meet all of these four conditions to technically have the ethically, ethically BE author of a paper. So contributed substantially to the conception, consumption, and design of the study, the acquisition of data or the analysis and interpretation. So basically, you are there to design how the paper was going to look like. And then you either drafted or providing critical revision of the article. So drafted means who wrote the first draft? And this is usually the first author who writes the first draft. Or you provided critical revision. Sometimes the first draft is so bad that the critical revision is actually the thing that makes an article worthy of publishing. And then the final approval. So all authors need to finally approve the a paper before it is sent for publication. And then last but not least, all authors need to be accountable for all aspects of the work and ensuring the questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. So one thing here is you can't publish a paper where you have fabricated data. So if you've published a paper where he fabricated data, all authors are going to be responsible even if one author who made the mistake. So make sure all your authors are, have this integrity for publishing. So when to decide authorship, this should be done before starting a paper. A common mistake students make is deciding the authorship after the paper is written and you know, right before you're going to send the paper for publication and they say, Oh, oh yeah, okay, we need to write down the list of authors. So this should be done before starting a paper. This way, nobody feels cheated because obviously it's more prestigious to be the first author. And because the first author does more of the work, so it's better to say hey, before the paper, ok, decide, hey, I'll be the first author. You can be the second author and third author, et cetera, and last author. If everyone knows. Which author they are. There'll be happy because okay, now it's fair. And also everyone will know the work required for them. So you can say that OK, the first author will write the first draft and then the second author, you will do the critical revision. Sometimes, as I mentioned before, the critical or the, you know, the first author is very inexperienced and maybe the second author that you've decided makes a very, very, very big critical revision. Maybe after that, you might want to talk again and say, hey, your first draft really sucked and I basically had to rewrite the entire paper, OK, in that case, you can, the second author that you decided can become the first author. But basically, it's better to at least get a kind of outline of who will be the author before writing your paper. And also, one more mistake that I've noticed is more authors does not, in my experience, does not have any correlation with having a better or writing a better or faster paper. Usually if you're a new author, you think, oh, I'll get all my friends involved. And usually your friends also know nothing about writing a paper. And maybe they're your friends, but they might not be that proactive or they might be just lazy. So make sure you choose authors, not just to have more authors, but choose authors that are hardworking, that are serious about writing the paper. That way, you can actually write a good paper. And one thing I wanted to mention only go back the four conditions of authorship. Now I mentioned that these are all the conditions technically for authorship. But often the senior author, which is the head of the department, quite often gets their name, usually their last author. They usually have their name without actually contributing anything just because they're the head of the department. It's not right technically, but that's it. It does happen. And some departments, and that really depends on your hospital or university, university or clinic that you're at. So just be aware of that. Alright, lets move on. Okay, so when you're going to actually publish their papers, many journals will ask for the authorship contribution statement. And this is where you're going to write down exactly what each author did. So, for example, I have this example, Domenico pronounces polar, shut CIO. Anyways, so this person did the conceptual, conceptualization, the methodology, the investigation and writing the original draft. So yeah, this is the first author and I can tell because they did, right? They're usually the first author writes the first draft and then, you know, this person just supervision. Quite often if somebody just did supervision, journals will say that this is not enough for being considered a author. But yes, so they were an author anyways, methodologies, so you can kind of see what kind of contribution you can have. Alright, so a common situation that I've seen is an author who won't do his or her part. So this is my very biased and never humble opinion. First of all, I would politely remind them because they might be a friend or co-worker or a doctor that, you know, in the hierarchy they are above you. Politely remind them and give them some time to do it. Ask them what's the reasonable amount of time that you'll be able to do your part if that's I don't know, revising it or supervising it or doing whatever. Politely remind them, then if they still don't spawned or anything and you've given them time, make adjustments to the author list. So either just put them as one of the later authors, one of the last authors, or put them in the acknowledgment section. Why do I say this? I'm not saying this to be mean. I'm just saying this because I don't want you to let a lazy co-author delay the publication of your paper because you've put in a lot of hard work and you don't want to let one co-author delay your entire publication and lateral your hard work go to waste because sometimes, especially in a hot topic, you want to publish your findings right away because there might be other scientists that might publish your paper before you publish basically the same paper that they've conducted by themselves for you. So you want to publish your paper usually as fast as possible. And because we're talking about authorship, I just want to end with this code. Talent wins games, but teamwork wins championships. So writing a paper is usually all about teamwork because usually, especially when writing more advanced papers, it's very difficult to do every single part of the paper yourself. So this is a really great chance for you to develop your team working skills and your communication skills to have a good teamwork. Alright, I'll see you in the next lesson. 21. CRediT authorship contribution statement: So usually after your article is accepted, you'll have to submit a credit authorship contribution statement. So this is a pretty simple and straightforward statement. It basically says, who did what? So you list all the authors of the paper and then you say what they did. So for example, they did the conceptualization, data curation, formal analysis, investigation methodology, validation visualization, writing the original draft and writing the well, reviewing and editing the paper afterwards, or just supervision. So here's an example. So you can see you have just the name of the author and just listing whatever they did and then the next name and whatever they did. So some journals have some guidelines on what constitutes authorship. So for example, you can't just, for example, you can't just be an author. If you only did data curation, you have to have done, I don't know, some formal analysis or you have to have some part in writing. So if your journal has those guidelines, make sure you read them before you submit it. So you don't end up in an awkward situation. But anyways, it's a pretty straightforward statement. And here's another example. So you can see here is the first author. He did the original draft and then the second author, he did the data creation and editing it. Alright, that's the end of this lesson. 22. Timeline to publication: Okay, in this lesson we're going to talk about the timeline to publication. I just want to begin with the fact that publication and writing a manuscript and to the day that it will be published can take awhile, several months, and in some cases, even a year or even two years. So the typical timeline goes like this. One day you wake up, you get a brand new idea. You're like, wow, this is a great idea and I want to write a paper about it. And of course in this, in this guide that I have for you, I'll give you tips on how to get good ideas and papers to write without a lab, ok, so you find an idea and then you'll have to decide, okay, was is this something that I can do and has already been published? If it hasn't been published. Okay, you can look at finding the right journals, journals that can publish a paper like this that you're thinking of. Alright, you found the journals you have, your idea hasn't been written before, and now you're going to actually start writing it or conducting your study. And after that, revising your paper and making it look wonderful and OK. Now you have your first paper. Then you're going to submit the paper to your journal, your first choice journal. Well, what's going to happen usually is the paper is going to be rejected. This is completely normal, statistically speaking, most journals, most authors will have to submit to more than one journal because they're usually rejected the first time. Basically, authors aim for a journal that's a little bit too high or a little bit too prestigious than they think that they can reach. But anyways, Whatever the case, if you are rejected, you'll have to resubmit the paper and kind of repeat this process over and over again. Usually after one or two journals. Yo get successful. In my experience, usually I get rejected the first journal, but usually the second or third journal, I'll have an acceptance. So anyways, after that, you'll have your decision, whatever that decision is. And after your decision, usually the decision is that your paper is accepted, but you have to revise it. So you'll have to revise the paper. And after advising paper, you're going to resubmit the paper. And then after that you'll get your final decision and acceptance. And after acceptance paper will be published. Whew, alright, so I'm gonna go through a little bit more in detail about this timeline. So the idea, as I said before, make sure nobody has done it before. So as soon as you get an idea, go on PubMed and see if people have written a paper like this before. If people have written a paper like that before, you're, it's going to be very difficult to publish because journals like to publish and novel ideas, ideas and studies that have not been done before. I know that in science we say, oh, it's good to have confirmatory studies. And yeah, it's good to have confirmatory studies, but they don't really get published. It's unfortunate, but that's just the way that publishing works because as a reader. You want to have big headlines. You want to read the best, the new thing you don't want to read about a boring paper that has already been done and you're reading about it again and again. It's good for science, but it's not good for headlines and it's not good for journals that wanna make money at the end of the day. Alright, so you gotta make sure that nobody's done it. You gotta make sure the ideas novel, it's new. And Ella said confirmatory studies are not easy. Publish. All right, finding the right journals. I suggest that if you're going to write a paper, you've come to the step, you find three potential journals. So your first choice journal, your second choice journal, and third choice journal. Your first choice journals should be a journal which is maybe a little bit, a tiny bit above your kinda overreaching. Maybe your paper isn't that amazing that you're aiming for a journal that's just a little bit more prestigious. Your second choice journals should definitely be a journal where you're pretty sure you can get published and your third choice journal go for slightly lower tier journal than you think. A place where you can guarantee publication. So this is usually journal with a much lower impact factor, maybe impact factor of one or even 0.5, depending on what you're publishing. Okay, make sure that the journal is in the scope of your topic. Sometimes it's, it's, I mean, it sounds stupid, but make sure if you're reading a paper about movement disorders, don't submit it to nurse Surgery Journal because you have to submit that paper too. Neurology journal. Right? Ok. And let's say finds some journals. You're like, Oh, I loved these journals. You'll look at the impact factor. It's I don't know, whatever. It's good and makes sure it's indexed on PubMed. So you can do that just by going and PubMed searching for the journal or using the PubMed and search. And last, not least, you can ask your colleagues because if you're interested in, let's say, neurology, you can ask your fellow doctors or classmates that are also interested in that. Hey, where did you publish articles about this topic? And they'll usually give you some good tips or advice. Okay, writing the first draft and revising. Well, this can take anywhere from a couple of days a week, two months. Usually, I would say that if you're planning on reading your paper in one week, usually it takes two weeks or even three weeks. So whatever you plan in my experience, it's always double double that. And usually they're revising part takes double as long as the part that it takes to actually write the paper. Because you'll realize, oh gosh, she made a bunch of language mistakes, doesn't flow very nicely. Maybe the paper isn't that easy to read. You definitely need to revise your paper multiple times to make sure that even a person who's not an expert in your field, just regular doctor that doesn't know anything about your field, can read the paper and completely understand whatever you're saying and whatever your findings are and apply them to his or her clinical practice. Okay, for submitting the paper. This is quite a boring process because you literally sit down and you will read the author guidelines and make sure your paper follows all those guidelines. This will take about two hours. I mean, why is it two hours? Lies it so long because you need to read all the guidelines and make sure that you owe the papers in the right formatting. Maybe it's double-spaced or the references are in the right format. Just very, very simple things, but it takes time just to format the paper. And this is important to format the paper because if you don't have it formatted correctly, the paper will just reject your paper right from the beginning. It won't even go to Peer Review the Journal. We'll just say, oh, rejected and give you the paper back again. I mean, the legislative they'll let you resubmit the paper again, but you'll have to go through that work again and make sure it's formatted correctly. This has happened to me. So I'm just telling you now, just make sure it's in the right format. Okay? And you'll probably go through this process of resubmitting the paper to a different journal because it'll probably get rejected. And most papers, most authors, when they submit their first tos journal, they are rejected, so don't be discouraged. This is kind of a marathon that you're running for publishing a paper. And don't also, this is a big mistake. Don't just don't just take the same paper and submitted it to a different journals. Usually, a journal will give you feedback on why they actually rejected your paper. They'll give you comments from the peer reviewers. And they'll say, oh, maybe the statistics are wrong or maybe it's difficult to read. Or maybe I don't know, there might be other issues, so don't ignore those issues. Read them, and try to change your manuscript so you can satisfy their viewers. Because what will happen if you don't is that you'll submit it to the next journal and they'll pretty much say the same exact thing, right? Sometimes peer reviewers don't get it right on the ball. They don't say exactly what's wrong, but they kind of give you some good pointers to go at that. That will actually help you a lot. Okay, and then you can finally we submit to your second choice journal after those revisions. Now the decision is acceptance, but that'll never happen, almost never during the first time when you submit. It will usually be acceptance pending minor revisions or acceptance pending major revisions. She'll get your paper back and you'll have to revise it a little bit and then submit it again, or you'll get rejected but resubmission possible. This is, this is a good still a good decision. Or you'll get rejected and no resubmission possible. They say no and they don't want to see your paper again. So after acceptance, what will happen? After acceptance? You might think that the paper is published, Ooh, it's gonna be published the next day. But no, unfortunately, for most journals, it takes one to three months of waiting before getting published. So you might ask what's happening in these months? Well, there's some technical things that the corresponding author will have to do. Usually basically writing some boring paperwork. So the transfer of copyright to the journal or proofing and checking, this is what the journal will do. They'll just read over your article and makes sure it's written nicely or doesn't have any mistakes. And then after all this process, your paper will be published online. So and one or three months it'll be published online, some journals or faster, like one week, but it'll be published online first and then after online publication and or one or two days, it'll be indexed on PubMed. So yay. And then finally, some, but not all journals have a print publication. So this is when the journal actually hard copy and kind of send the journal out via mail or whatever to people that subscribe to the journal. And the print publication is a couple of months after. It has been published online on PubMed. And so that's a couple of months after, but that doesn't matter for you as long as it's indexed on PubMed, that's what matters and that's what you write on your CV. Okay. So that's the general timeline. I hope that was helpful and I'll see you on the next lesson. 23. How peer-review works: Okay, in this lesson I want to talk about how peer review works. So just to begin, when you submit your paper, the editor at a journal will get the paper and they'll say, hey, I want to assign some peer reviewers to this paper. And these peer reviewers is just how it sounds their regular doctors or other scientists around the world can be literally anywhere. And they will read your paper and they will judge it on effort for nicely. If the findings are novel, if the paper is worthy of being published. So unfair views are the norm. It's often frustrating because you'll get reviewed, your paper will get reviewed by a non-expert. So let's say you're writing a paper about, I don't know, pulmonology. And it kinda has to do something with imaging. So the Journal chooses a radiologist to review your work. But the radiologists, maybe we'll talk about a bunch of random things like the contrast used or Oh, the settings of the imaging machine. And your papers about pulmonology. And you're, let's say you're an expert in the field. And basically every article that you've ever read on pulmonology on your topic has never talked about these really kind of stupid and technical matters of how imaging works. You're just very interested in another part of the paper. So he might find it very unfair or stupid that your paper has been reviewed by probably a radiologist in this case, or even by a person that's a non-expert in your field. So keep in mind that that is the norm that might happen, and it probably will happen if your gonna publish a couple papers. But that's just what you have to deal with and you have to respond to their comments and concerns the best you can, even though it might be frustrating. Usually the reviewing process, while at least I'd say one month, but it can take up to six months. So give yourself some, some time to wait and be very patient with this process. And last but not least, this is one of the most important things you have to change your manuscript according to the comments of the peer review. Even if they're there comments or frustrating or unfair, it was reviewed by a non-expert. You have to change the manuscript according to their comments because if you don't, your paypal, your paper will not be published. I mean, if you're okay with that, fine, just don't publish it there, don't respond or whatever. And you can move onto your next gentle. But if you want to get published, you have to change your manuscript according to their comments. And last but not least, stay polite in your response. If they, if the peer reviewer makes a mistake while or misinterprets your findings for some reason. Tried to stay polite and your response and yeah, because that'll be in your favor. And also recommending reviewers. So recommending when you publish, when you submit a paper to a journal, sometimes you'll have an opportunity, sometimes you don't. But often you'll have the opportunity to recommend certain reviewers that you want to review or paper. And often the journal will take your request seriously and actually send your paper to those people if they are so qualified. Because a journal, you know, they have to find qualified people, right. They don't they don't want you to have that first hearing frustrating experience that I just described before. So they'll give you this opportunity. And it's controversial, but it's common for doctors and physicians or other researchers to basically recommend their friends as peer reviewers. Now this, this is kind of controversial because you don't want a friend revealing your paper because obviously they're going to be giving you probably a favorable review. They're going to be recommending publication because they're your friend. But at the same time, your colleagues, your friends, they, you, they are your colleagues and friends because they're in the same field as you. They're doing the same research is you. And often in very small niche specialties where there are only maybe ten researchers in the world that are doing research on a particular area. You're basically all going to be friends because you're going to meet at conferences and you're going to know each other. So yeah, it's controversial, but it's common. And to become successful as a scientist and become a successful person with a lot of publications, with high impact publications, you're going to have to make friends with other scientists in your field of work and how you can do this as gone to national conferences, big conferences and present there and you'll get the opportunity to mingle with them and talk with them, and maybe even organize papers together, organize researchers together. And also last but not least, after you got a couple of publications. This is later on in your career. After maybe 20 publications or maybe some other high impact publications. You'll be invited by another doctor, physician to become an editor for a journal or a section editor, or even the Editor and Chief of the journal. And then from there you can make a lot of connections with other doctors and scientists. So that's the end of lesson and I'll see you on the next one. 24. What is a letter to the editor?: Okay, so in this section we're going to write a letter to the editor. But what is a letter to the editor? Okay, let's pause before we start. I just want to congratulate you on making it this far with this picture of this cat roaring at these dandelions or whatever else flowered is. So cute. So I'm showing this to you to show you my appreciation that you've made it this far and soon. You will have a real publication under your belt. Okay. Well, by Kerry. Okay, so cute. Alright. What is a letter to the editor? It's a response to something published in a journal published recently, I should say. It provides additional information. It might ask some critical questions or it gives some constructive comments. And some way it adds value to the published paper. This is the end goal of a letter. It somehow adds value to the published paper. And usually that's by asking or pointing out critical limitations or questions or adding some constructive comments are just praising the paper. Ok, so why write it so it's faster, right? And I've structured this course so that you write this editorial or editorial letter or a letter to the editor first because it's faster, right? It takes about three hours or even shorter if you're experienced in writing. And the decision of acceptance or rejection is quite fast. Usually within a week or two. And its PubMed index, right, so it looks great on your CV and it's great practice for academic writing. So this is why I'm having you read a letter to the editor first because you'll get some really good practice with academic writing, which will be invaluable when you're actually actually writing a full original paper or any kind of other scientific paper. Alright, so again, what do you offer in a letter to the editor? You offer your interpretations. You're going to review possible mistakes or limitations, and you're going to offer your new perspective. Basically, if I had to sum up a letter to the editor and what it is, you're either going to praise or critique the article. And I think this is something you should stick to when you're writing a letter to the editor, you should aim for this. You should ask yourself, do I really liked this letter? In which case? Which case you're going to praise it and say why it's amazing. Or you're going to criticize it and say, hey, these are the limitations. This is how it could be better. So praise or criticized, that's the main takeaway. I want you guys to remember and you guys to know and ask yourself when you're choosing to write a letter to the editor, which you are. Ok. So these are the usual author guidelines for letters to the editors are usually quite short, so only 500 words, some are a little bit more. I think the max is like 1000 words. Some are a little bit less at about 400 words, but around 500 words is the usual max word count. And also the references. It's five. References maximum for most journals. Three authors maximum for most general, some journals have a to author max limit. Some don't, some have, you know, you can have as many as you want, but usually there's usually a limit of about three authors. And then the main limitation about writing a letter to the editor is that it has to be published recently in the last four weeks. Most journals require to be published in the last four weeks. Some are a little bit more lenient. They say in the last maybe two months, some maybe even in the last six months. But to be safe, I would stick to the last four weeks when trying to find paper to read a letter about. And usually most letters to the editors. Most letters to the editor are on original papers, but you can write a letter to the editor for literally any sort of paper. It doesn't have to be original article. It could be a review article. It can be a viewpoint that you're writing a letter about. It could be really any any type of paper published by a journal. So for example, if we go on GMOs website jam has one of the biggest journals in the world. So they have a letter to the editor section right here, and so on. They're author guidelines. They say letters discussing a recent article in the Journal should be submitted within four weeks of the articles publication and print. So that's important for weeks. And OK, here are the requirements. 400 words, less, less or equal to five references, and one of which should be the actual article, right? And less than or equal to three authors. So I gave you this just to kinda give you a reference for how the author guidelines might look. And also I just want to point out, point out that it's letters discussing a recent article in the journal. They don't necessarily say only a specific type of articles. So you can really write a letter about any type of article. Okay? So what topic you're, you've decided, okay, I'm going to write this. You're excited, all right? It should be a topic that you know a lot about or that you're passionate about. Or if you've written about this topic before, maybe you've written some scientific papers before. And you're interested in certain topics. So you can write about that. Also. You can write about less scientific topics like I mentioned before, you don't always have tried about original papers or scientific findings. It can be less scientific two, because journals published, opinions, historical papers, others, other, many other different types of articles. So you can really be creative. Okay? So how do you actually find an article to write a letter about? So I would go to PubMed and I would look at what you're interested in. Maybe you're interested in YouTube information of YouTube, medical information that's on YouTube and maybe you could do a analysis of it. So okay, you just put it on YouTube and make sure you go to the display options and put in most recent work, right? Because this is going to give you the most recent articles so that you can find articles that have just been published. Because of course, remember this is a four week limit. If it's usually more than four weeks, the journal is not going to accept your letter to the editor. Alright, or So, as I show here, you can search by topic, right? So I'll go on PubMed and search out on YouTube, whatever whatever your topic is, stroke I don't know you can MS. I like neurology, so that's I'm giving an early topics, but anyways, you can also search by journal, right? So over here is still the jama network journal, one of the biggest journals in the world. So if you really want to get published and write a letter in this journal, which I can completely understand why you would go to their website and go on the new online section. That way you're going to find all the recent articles and then you can just go through like, okay, you can see the date here, November sixth, 20-20, and recommendations for follow-up colonoscopy after polychromy. Alright, maybe if you're interested in that, OK, go for it. If not, just keep scrolling and try to find an article. Alright? So they're going to be two decisions that you make when you read an article. Read an interesting article that you're like, wow, maybe know something about, or maybe if you don't even know something about it, maybe it's something that you want to learn more about. So if you liked it, what you could think about, what you could say to make it even more amazing and more clinically irrelevant. What did the authors of this original paper forget to say? Or maybe what did they not say? There's only a certain amount of room that original paper has. Usually the limit is like 4 thousand words. So you can't say everything about a topic. So if you thought it was amazing, even more things, more research that backs up whatever their paper said. Okay, so give additional information, more research, right? Or given other perspective that appreciates the paper from another angle, this is really what your letter is about. You're going to be giving a different perspective, right? So if you like it, this is what you do. If you didn't like it, right? You thought it was, it wasn't a great paper. Well, this is what you're going to say in your letter. You're going to say if there are any limitations in this paper that were not discussed, maybe the methods were wrong, maybe, I don't know. Maybe the author was overstating a solution or giving a slightly false depiction of reality. All right, these are things that you can definitely point out. Were there any assumptions made that could be dangerous or wrong or biased, right? And then there are things that are clearly wrong that you can point out like, was there anything that was done incorrectly onetime or an article? And they actually gave the wrong formulas and they used the wrong formulas and their methods and materials. Or maybe they used the wrong statistics. Maybe you're really good in statistics and you say, oh, there might be a better way to statistically analyze the information they have here. So I'm just going to summarize. You either liked it and you praise it or you didn't like it and you criticize it, that's the basic options that you have when you're writing letter. So what you should do, every article that's published should has these things. You should use polite language, whether you like the paper or you didn't like the paper, you're going to use polite language. Okay? You're gonna give an alternative viewpoint no matter what you're writing, you have to make it concise and short, right? And make it very clear and specific, right? You don't want a long article and you definitely want to be played. So what you shouldn't do is use scornful or rude language. So this is sometimes the case of my students when they use, or may also when I started writing letters. When you write a letter, even if you don't like, even if you pointing out the limitations, you still have to be polite and you cannot use scornful language, rude language. You can't say that the authors of the paper at incompetent or stupid or anything like that, right? It has to be very polite. Ok? So what you shouldn't do is have ambiguous or general message. You want something specific and concise as we said before. And also, you shouldn't have biased comments. Your, your findings in your paper, your opinion. I mean, it can be opinion based, but it has to have scientific evidence behind it. So if you say, you know, this should be like this, there should be some science backing that up, right? So no bias comments. Okay, so how it looks. So letters to the editor usually have this on PubMed. I have the screenshot here. They usually have this letter to the editor prefix before the paper. So in this case, the letter to the editor colon regarding a recent publication on the association between abuse and adverse events of analgesic medications. And then here, response to the letter to the editor. And when you actually submit a letter to the editor, the authors that wrote the original paper can have a response to your letter to the editor. So they can say, oh, you're right, thank you for pointing this out. Or they might say, Oh, you're mistaken, blah, blah, blah. You know, that can actually response. So keep that in mind. Some journals don't have this prefix sum. Just it looks like any other publication, but usually they have this letter together, prefix. Yeah, so so how to find when a paper was published quickly. So you're probably going to be looking through PubMed, right? So I just wanted to show you this is an article that was published and on the top, usually you'll find when it was published. So over here, they usually write the date like opposites. So year first, then month, and then they write today. So in this case, 20-20 November seventh, right? Okay, so here's another example. Over heresy. It's a different position that they're writing it over here. It says the year 2015, but it actually says the month and day over here. So ePub that just means electronically published 2015, January sixth. So usually on the first line you can see exactly when a paper was published. So then you can see o is this, you know, within four weeks. Okay, so the goal I'm setting for you is to write the first draft of your letter within five days. Now I know that might seem like, whoa, five days, that's not much read a whole publication. But I promise that this course will help you and that if you put your mind to it, you can definitely write it within five days. Alright, and because this is going to be your first publication, I just want to leave you off with some motivation by Arnold Schwarzenegger. This quote, strength does not come from winning your struggles, develop your strengths when you go through hardships and decide not to surrender. That is strength. So I thought this is fitting now because you're going through kind of a hardship now this is something totally new for you. New way of writing, academic writing, and a new way of expressing yourself and your, maybe your first publication ever. So, I wish you the best of luck and I'll see you in the next lecture. 25. Examples of editorial letters: Welcome back. Now I wanna take you through two examples of letters to the editor, so you kinda get an idea of how it is. Okay, so for our first example, here is a title Hybrid anesthesia for fractured neck of femur using interest fecal pill O'Kane. All right. So first of all, I want you to notice something. This letter is incredibly, incredibly short. This is literally one paragraph long. I'm in the rest of this stuff right here, over here. These are just references. This is just, you know, other information when the letter was received and accepted and other blah, blah, stuff like, oh, no competing interests. So the actual text of the letter is very, very short. So this is, I just want you to realize that a letter to the editor really doesn't have to be that long. Usually they're very short. And to the point, as I said before, alright, so let's read to the editor, due to the recent shortage of Hyperbaric BBVA cane in the UK. But so this is the first reference. This is the reference to the first to the actual original articles. So this first sentence is summarizing the article that they're writing about. And you can see the reference here. So if you want to read the original paper, it says, and by the way, this is from open access journals. So legally I can show this to you. Alright, we thought this would be the ideal opportunity to share our successful experience regarding hybrid anesthesia for for uncomplicated fractured neck of femur surgery using interest fecal pillow cane combined with a single injection fascia, iliac block. Under propofol sedation, we found that the shorter surgical block duration of ethical pillow K-NN versus Bitbucket BBVA Qin was not clinically significant as long as the additional analgesia from the aphasia iliac block was present. Thus, one can almost consider the peripheral nerve block as an adjunct to the spinal to prolong the surgical anesthetic conditions. As drug shortages become increasingly common across the globe, anesthesiologists will, patients will benefit from frontline ingenuity and creativity. Ok, so this paper, this letter, I think it was great because it's very short. It's to the point there's no superfluous blah, blah, blah going on. They directly say they, first of all, they directly mentioned the article is summarize it. They give their opinion of how their own perspective of how it could be. They give one other reference, which is a good reference, which supports their claim. And then they vary politely. And the and the paper. As drug shortages become increasingly common across the globe, anesthesiologists will benefit from frontline ingenuity and creativity. So the ended in a very polite way. And they also say how their letter is novel, how their letter is useful, right? So they're saying, this way of thinking is, you know, shows ingenuity and creativity. So I think this is a great letter and a great example for you to kind of get an idea of what it is. Alright, let's go through the second example. And again, you'll notice that this is an extremely short letter. It's literally one paragraph and sentence basically right here. Okay. This is also an open access letter, and at the bottom, if you want to read it on your own, it's the same thing but the references at the bottom, okay, so to the editor, and you'll notice that every letter to the editor starts to the editor. So to the editor here and also to the editor here. Okay, so to the editor and OK, they have the reference to the original article. It was with great interest that I read the article by Kapoor at all titled cariogenic shock in the setting of acute myocardial infarction. Okay, so you're all, you'll already notice one similarity. So it was a great interests that I read the article by blah, blah, blah. Okay. Yeah. So the first sentence always references the first, the original article that they're talking about. So in this case, due to the shortage of Hyperbaric boo, boo cane in the UK, boom. They always summarize the findings. So I want you to kind of see the patterns here. Okay, so let's continue. The material was quite helpful and thorough in detail. I'm concerned regarding the information presented in table one, page 16, when it knows that a new left bundle branch block is considered a semi equivalent. So immediately it gives the limitation of the article. And a very clear and polite way. The American Heart Association semi guidelines removed the finding of a new left bundle branch block from the guidelines in 2013 after studies demonstrated difficulties and determining age of the left bundle branch block, low rates of culprit artery occlusion and higher complication rates association with utilizing this criteria for cardiac catheterization. So wonderfully they give these two references. They back up their findings and give good references that backup what they say. So an observational cohort study by Chang at all also showed no difference in the rate of acute myocardial infarction between new, old or no bundle, left bundle branch block. So another, they gave really good references. Their letter is short and to the point where we didn't we didn't finish one more sentence of note. The table also references got scar both those criteria which should in fact restaurant reference Scarborough criteria. Okay. So this is a spelling mistake that they made with this C here should be a G. So they're pointing out this mistake over here. So wonderful day. They immediately set, summarize the letter. They gave what was worrying for them, and then they gave the reason and references for what was wrong and why it was wrong. And so they gave their guidelines, 2013 guidelines that have changed. So wonderful. So this is the second example. And hopefully from these two examples, you can kind of see what a letter to the editor is. You're either critiquing an article, in which case this one did, or your praising and article and pointing out something new. And this is kind of what this letter did. Alright, so I'll see you in the next lesson. 26. How to write an editorial letter (with template): Okay, so welcome back. For this lesson, I'm actually going to be giving you a template for how to actually write your letter. So the first page of the letter should just be the title page. So of course, the Reidel title you're going to write that last. The authors, remember I said max three, try to aim for three, but it depends on your journal and then of course your affiliation, you write down your address, the corresponding author, makes sure you know what the word count is before writing your letter. The maximum word count. And of course, conflict of interests, none reported. Ok, so for the rest of the letter, I'm going to have a template for you. And the color and purple is going to be the template text and the color and green is going to be the example text. Okay, so here we see the introduction. The introduction should be about three sentences. This is what I recommend. So you always begin with to the editor and your first sentence will be something like this. We read with great interest the study by but the first author's last name at all on, and then you rephrase the paper's title. Okay, So this could read something like we read with great interest, a study by Smith at all on what challenges remote consultation psychiatrists face. And then you just put the PubMed link just so you have it for yourself because at the end of the letter you're going to be adding the references with Mendeley. All right, so that's your first sentence. Basically, we're going to introduce the article, the original article that you are going to be critiquing. Alright, so the next sentence we said this is a three sentence introduction. Okay? So what do you write? The paper illuminates the importance of, and then you're going to give the main conclusion of the study. What is a paper actually saying? It as a paper saying that I don't know. This, there's a correlation between something or whatever that main finding is. You can find it in the conclusion of the paper. So just summarize that in one sentence. So the example sentence, it might look like this. The paper illuminates the importance of nonverbal cues to physically assess one's patient to place a diagnosis. Alright, so that's our second sentence. So your first sentence, you're introducing the paper. The next sentence you are summarizing what the paper actually concluded. And the third sentence is going to be like this. So while the paper offers crucial insight into whatever the topic of the paper is, we believe that discussing this topic and this topic, it may augment and then whatever the topic, whatever the topic of the papers. So it might read something like this while the paper offers crucial insight into remote consultations, we believe that by discussing the utility of phone apps and the safety of remote consultations, it may augment tele medicines roll today. Okay, so this is the three sentence introduction. I wrote it out. Word kinda gave you a really great template and you can follow that. Of course, this is just a template. And if you're an experienced writer, you can go off the template and do what you want. Okay, so the body paragraph, This should be about five sentences, in my opinion. Okay. So the First sentence which is optional, that you should start out with, is, if it's not already obvious, say what the original paper found or suggested. In the introduction you wrote euro down, of course, small summary of the conclusion. But maybe if the conclusion is a little bit more complicated or if it's not obvious, kind of say what the paper found. So for example, Smith at all found that psychiatrists and New Zealand were unhappy with phone tele psychiatry consultations because nonverbal cues are not possible to be observed. This cost psychiatrists to have a lack of confidence in their diagnosis. So this gives a short summary. So the second sentence is say what you can add to better the understanding or how might they be wrong? So if this is, if you are praising the article, you can add, you know, wow, this is amazing and adding more information to make it even more amazing. Or if you're critiquing it, say you know, how they might be wrong or how they haven't considered some other things. So, and this example sentence, we're going to be critiquing it. So we remind psychiatrists that other forms of telepsychiatry are still valid and maybe more useful. Alright? Alright. So the third sentence now is when you give a fact and it's backed up by a study that supports your point that you just made. So for example, both doctors and patients are satisfied with screen to screen consultation as with face to face meetings. So this original article and in our example sentence said that, Oh, telepsychiatry isn't good because you can't actually see somebody, right? You can't see their face when you're talking over the phone. But in our example we say, oh, screen to screen consultation. So basically a video call is much better and patients are satisfied with it. And you have to give a reference. Pubmed, PubMed original paper, which says that, okay, this is actually true. And then the next sentence, okay, so we're at the fourth sentence of your body paragraph. This will explain the last sentence a little bit more. So basically it's going to explain that study even more and give more insight. So for example, video conferencing allows the patient to interact with his or her physician from the familiarity of his or her own home. In this way, patients may be more receptive and expressive in a psychiatric session. Alright, so, great, good example of how to explain it. Alright. And the last sentence, you say, we advocate, we recommend, we identify, We're mind. So something along these lines. So we let's say we're in mind and then write a summary sentence while giving the big picture. Give the big picture the conclusion about what you're actually saying. So we're minds psychiatrists to not discount the benefits of telos psychiatry, but instead encourage them to switch over to video conferences. So in this example sentence, you are summarizing the finding of the last paragraph that you have added, right? Okay. So you can have one paragraph if that's all you want, or you can have two paragraphs. I recommend having two paragraphs, but of course you can have one. It's just if you're able to fit it within the word count, you can add a second paragraph and it follows the same outline as this first body paragraph. Okay? And then the conclusion is likely introduction a three sentence conclusion. So the template sentence, we command and use the author's last name at all for providing crucial insight on whatever topic they're paper was about. So even if you disagreed, you say that they, you know, they did something great. They provided some crucial insight. You have to be polite, okay, so for example, we commend Smith at all for providing crucial insight on the psychiatrist experience of remote consultations by phone. So that was the first sentence. The next sentence you're going to compare their article with your article. And say, for example, while tele-medicine poses new obstacles, it introduces an array of benefits for both patients and psychiatrist delay. So their paper was given the limitations of telepsychiatry and your letter rate now is giving this example, giving the advantages. And the last sentence of the conclusion. In this letter, we expand on and give a summary about what your letters about. So in this letter we expand on several proven features and Teller psychiatry is current use and provide a nuanced view of how clinical practice is affected amidst the covered 19 outbreak, for example. Okay. So that's just a summary sentence. And that set, that's your letter. Of course, you're going to end with the references and you can do that with the Mendeley. And what I usually do is I do my references last, so I will write out my entire letter. I will just put in the PubMed link. And then at the very end, I will use Mendeley and add the references and make everything formatted and fancy. Alright, so I hope this was helpful. This is a template that you can use when writing your own letter. And I'll see you in the next lesson. 27. Example of editing a letter: Alright, so now let's go through an example of a letter to the editor. And I'm going to show you what's good and what's bad and how I would personally edited to make it better. So in this example letter, we're going to have a letter, an original study by Bob at all. It's made up on empathy and medical students and the letter will go like this. So before this, before any editing, empathy has a multifaceted appearance and that has its roots in the individual's ethical, behavioral, and intellectual thought pattern. This pattern is also shown to differ between men and women. Okay, right from the beginning, this first sentence is not telling me anything about the original study, nor is it telling me about any limitations or any praise that they are giving towards the study. Okay, but let's keep reading. The definition of empathy is difficult and not uniform, but rather individual, which makes the assessment of characterization about empathetic changes throughout medical school challenging. Okay, well, This sentence is a little bit more specific. It's saying that measuring empathy is challenging, but it's still not explicitly telling me anything specific about the original study or how it could be improved. It's very, it's very broad and it's very general. So not a great second sentence. Alright, let's read the third sentence. We also remind the authors about the small number of participants and that a large, more diverse sample size may increase the validity of the study. Ok, so this sentence finally is giving me a very concrete limitation of the original study. It says, okay, the sample size was small and that it should be increased. So I hope the next sentence will tell me more about that. Alright, so the study was performed awesome medical school during the academic year 201920, only 20 students participated in the study, 25 females and ten mils of unspecified of ethnicity. Ok, so these two sentences are pretty good because they tell me exactly what was wrong with the original study that you felt was wrong. And so now I get some actual details. Alright? I like, I like these two sentences for the most part. Alright, Smith et al. found these are other authors. So this is another reference, another study, Smith et al, found that gender differences in empathy self-evaluation studies may have arisen due to females being more inclined to over-report empathetic behaviors, whereas males under a port them. Therefore, the study by Bob at all, this is the original study, may not properly reflect empathetic decline among medical students. Okay, so this is a great reference because first of all, and the original study, they were 25 females and ten mils. So basically more females, a lot more females and males. And then they're referencing other study which says that, oh, the changes and empathy might be recorded differently based on the gender. So having an unequal number of females and males just increases that bias. Alright, so not, not too bad of a paragraph here. What I will say that English was good, right? Not too many grammar mistakes and. Yeah. It was a good paragraph well-written, but it could be a lot more specific. So this is how I would personally edit it. Alright, so instead of, so I would start the paragraph off with Bob et al, study was performed awesome Medical School and Australia during the 201920 academic year and only 20 students participated in the study, 25 females and males of unspecified ethnicity. So you'll see that the first piece of information I added was I actually went back to the study by Bob at all and I found which country they were in. Because often medical school, obviously this is just an example, but awesome medical school. Nobody has any idea where the medical school is. So let's get to give a country, in this case at least. Alright. So the next sentence, we suggested a wider sample size with an equal gender distribution and better control. First, students cultural differences be used to improve the legit, legit legitimacy of the study. Sorry like that. Alright, so you might also notice that I introduced another piece of content into the sentence of cultural differences because in the sentence before we mentioned unspecified ethnicity. So we need to comment on that and say, oh, well the unspecified ethnicity, it might result in cultural differences if you don't control for it. Alright, so next sentence. This was kept mostly the same. Smith et al found that gender, gender differences in empathy self evaluation studies may have arisen due to females being more inclined over port empathetic behaviors, whereas males under-report them. Alright, I basically kept up the same. Therefore, the study by Bob at all may not adequately reflect the empathetic decline among medical students. Alright, so I added this conclusion sentence that summarizes everything. We encourage future scientists to recruit a larger number of participants and suggest a larger and more diverse sample size we used to increase the validity of the study. And this last sentence, to make it a little bit more clinically relevant, make your findings more clinically relevant to future scientists. Okay? So I hope you got something out of this para, example paragraph. What I want you to remember when you're writing your letter is that you need to make your findings, your message extremely explicit. You need to tell exactly what's wrong or exactly what's right. And remember, you have basically two ways of writing letter. You're either going to say the paper that you read is amazing. It's great. It's the best paper you've ever read. Or you're going to say it's really limited and you're going to critique it. So you're either going to say it's great or it's sucks, right? So just make sure your letter is structured like that. And you, and your thought process is structured like that. Alright, we're gonna go through one more paragraph just to give you a little bit more practice. So this is before I've edited anything. So several physicians experienced at creating and maintaining an empathetic approach should patients is a complex task and can be associated with emotional distress. And you'd give reference here. Okay, so again, this is a very, very broad sentence. It's not telling me anything about the original study and it's not telling me if you thought that the original paper was great or that it sucked. But okay, so it's not a great first sentence, but let's keep reading. Therefore, it is of crucial importance to encourage new teaching methods and evaluations to counteract the erosion of empathy among medical students in order to find a balance for their future medical career. Okay, so this second sentence, it's kind of saying the erosion of empathy among medical students. It's saying, okay, something about empathy not being in medical students, but it's still not making any definitive claim. It's just giving very broad information. So this is also another great second sentence. Alright, let's keep reading. This enables students to receive better tools and guidance as to how to approach patient interaction. Okay, we're already in the third sentence, and this is still a very, very broad sentence. I'm I have no idea if the letter is telling me that the that the original paper either sucked or that it was great. And remember, this is basically the question that literally every sentence of your letter should point to which it's either say, oh, this paper was amazing and this is why, or This paper was, it thought it was really limited and this is why, why, why you list the reasons. Okay. So I still have no idea. But hair, I bolded the sentence because I think it's good. Additionally, barriers to real empathy interactions may be overcome by taking a more natural approach where students whole interaction with the patients might be assessed rather than looking solely at the verbal communication. Okay, So this sentence Finally tells us something. It's saying that, and by the way, I didn't know this the first time I was reading it. But I think the student that that wrote this, I asked them and they said, oh, the original study only analyzed the student's response when the student actually wrote a response of how they felt like their empathy levels were, or how they felt towards their patients. And it was analyzed like that. So the students said, hey, well, we can actually use body language and analyze the body language to measure empathy as well. So it wasn't clear and I had to go and ask and and make sure that was the case. So this is what I tried to make in my in my editing of the letter. Much more clear and explicit and you'll, you'll see that soon. Okay? So therefore, we remind students and physicians not to neglect the importance of establishing good patient contact based on genuine empathy, whereas encouraged, encouraging students to use body language and gestures may be of more or at least equal importance as the Hearst bound centers sentences of empathy. Ok, so all right, that's a good conclusion sentence. But anyways, this is how I would edit it out, make it much more explicit. First of all, let's, let's see. The study was based entirely on letters written by students and neglected to record or analyze any real life interactions students had with their patients. Oops, made a spelling mistake. Students. Alright, so this first sentence is a lot better because it tells me immediately the limitation of the original paper. There's no guesswork that it's not broad. It tells you exactly what was the limitation. So the study was based entirely on letters written by students and there was no, you know, analyzing real-life interactions. Okay, so that's limitation. Now you know exactly, alright. This form of analysis was limited to students self-reflection about their feelings and to their technical, verbal, and writing ability to express their emotions on paper. Ok, now we've explained why that limitation really was a limitation. Alright, let's look at the third sentence. The paper made no mention of any demographics. So as readers, we are unsure if the students were native speakers of English. Okay, another barrier, another limitation of the study. Thus barriers language may have influenced the results. Okay, so you can see that every time we have a sentence where we explain a limitation, we have a sentence explaining it. So even if it's quite obvious, for example, here, we say that we're unsure of the speakers were native speakers of English. I have a sentence explaining it that, oh, the barriers to this language might have influenced the results, right? So always explain whatever limitation that you point out. And then we have a short conclusion. We suggest that these barriers may be overcome by students use. Well, I would say students recording, recording of body language and gestures, or maybe not recording evaluation. Evaluation of body language and gestures. Alright, so now you can see from these two examples, hopefully that your findings, your message needs to be very explicit to the point. No broad sentences, no general statements. It needs to be to the point. And you need to say if the original letter sucked or was great. So always ask yourself, what am I saying? Am I explicitly saying what were the limitations? Where am I explicitly saying what was great about it? And am I giving concrete examples? And am I explaining those examples in a succinct way? Alright, so I hope you got more out of this lecture and can edit your own paper. And I'll see you on the next lecture. 28. Submitting your editorial letter: Okay, so if you have come this far, congratulations, because now you've written your letter and now you're ready to submit it. So when you're ready, all you have to do is go to the actual website of the journal. And you will find a four authors section somewhere. Maybe it'll say author guidelines. It has different names, but find the section and click it. So in this case here we are on the jama cardiology site, contains some nice information. Here's the Editor and Chief. Alright, so we're going to submit our manuscript and we're going to click here. So here we are. And it wants us to make an account and pretty much every journal will want us to make an account. So we have to do that. So let's make an account. Now. First-time user, please register for an account. Ok, so here we are, and we're going to register for an account. We put in our name, email all this good stuff. Your institution is going to be your university and your street is going to be your university street address also the city and postal code. So this is all about not where you live, but where your university lives, right? Okay. So we keep on going down. Temporary work address. I don't work at the university, so there we go. Okay, that's fine. Alright, so now we're here and now we can finally get started with submitting our manuscript. So all you do is go here and hit Submit Manuscript. Okay, so on the first page we're going to upload our files. So just hit browse and upload your files. Already, have them uploaded here. And if you need to move them and reorder them. Alright, so after that, just come down and hit Next. Now we're gonna put in our title. In this case, I just put in a sample title for this example. And next. The authors. And my case, it's just one author, just me. But if you have more, you can put them there. And yeah, so the number of authors allowed in this case, as we already knew from our author guidelines was three. So you can have no more than three authors. The system would actually allow you to have more. Also, if you want to speed up this process, you can do the author email lookup. But that's only if they've published in this journal before. So, alright, after you have putting all your authors, make sure you have them in the correct order, right? Because you already know who is going to be the first author of the second author and the third author and the order is important so you can change it here. Alright, so contributing author and notification, you have to make sure that all authors know unconquered that you're submitting your article here. So I'll just put in your initials as your signature and hit Next. Alright, so every journal will have this section where you're going to select the manuscripts, subject areas. So if your letter is about, I don't know, heart failure than just press heart failure and lets, you know, I'll do this again. So I pressed heart failure and it comes up here and I'm going to drag it to the primary subject area. And then you can have some secondary subject areas, like maybe it's about sudden death. So I'll take that and I'll drag it to my secondary subject area. Alright? But we only need one for the primary. And you see this one selected, one required. Okay. Let's sit next meeting presentation. This asks did you present this some kind of meeting or at some conference? In our case? No. But if yes, you'll have to provide the date, the meeting Tikal, title, and the work that you presented? Our case, no. And he Duplicate Materials was any data, text, tables, or figures and this letter that you have, was it in any other publication? In our case, No. But if it says, Of course he choose, yes. Previous interactions, have you had interactions with any of these editors? These are the editors for jama a cardiology. Maybe if you've published previous papers before with this journal, you can choose this, but in my case, I haven't. And potential conflicts of interests in my case, no. But yes, of course. She's that then find related articles in this case because we're submitting a letter, they have this section so they know exactly what article you're referencing. And my case, it's an imaginary article just for the sake of this tutorial. So I'm just gonna choose some random dates, right? Search, but it's not going to find anything because it's imaginary. Ok. Next, Alright, reviewers to include this is important. If you do know somebody in your field that is an expert in whatever you're talking about here. So if you have some colleagues, you can put them here. As you mentioned before, conferences, going to conferences, that's a great way to network and get to know new people that are working in the field that you are. So you can put them here if you know them. Okay. Please not list people from your own institution or colleagues were close associates, collaborators, or family members. As I said, listing friends is controversial. It's ethically questionable, but it's a common practice anyways. But I would advise you to not less people from your own institution because it's clearly glaringly obvious that like you meet them on a daily basis. So nobody from your own university, and I would also say nobody from your own country. So if you live in America, I would say to someone who lives in Germany, a doctor in Germany, or I don't know, the UK. That way, even though you might be friends, you have a safe amount of, I don't know, distance where they can truthfully give their opinion about your work. Ok, so these are the reviewers to include and then the reviewers to exclude. Maybe you have submitted to this journal before. And there were some reviewers which were unfair in their assessment of your paper. So you can put them here. Some journals have this. Okay, let's set next and review the material so you'll have to click on both the PDFs and you'll have to go through it and just make sure everything is correct. Everything is just the way it should be according to the author guidelines. If it's not. Well, this is the last chance you have to check. So take this opportunity to just make sure everything is the way it should be. Just read over your text and make sure it's right. Okay, so after you actually click on these PDF's, you'll be able to hit the approved tools. And then you'll be able to hit Next. Alright, so now we have our data here that we can review just before actual submission. So everything looks fine. Of course, this is incomplete because this is a tutorial. But otherwise you'd be able to hit Next and actually submit your paper. So there it is, it's not too bad. And now I just want to say congratulations because you have just admitted your first publication. Hopefully, I mean, hopefully it'll be a publication soon. So congratulations and I'll see you on the next lecture. 29. The Likert scale for surveys: Introducing the Likert scale. So what is the Likert scale? I gotta say I really like it. Anyways, it's 5 or a 7 scale for measuring attitude, beliefs, opinion, or behaviors. So basically, you're going to use the skill, a survey that you make for measuring these things. And it's a good way of doing it. Why? Because it gives me more than just a yes or no answer, right? You can say, oh, I really like this or I don't like this. But if you use a Likert scale, you can get degrees of opinion. Oh, maybe I like this just a little bit, or you can say that I have no opinion at all or if I like this or not, and that wouldn't be possible with just yes or no answer. And furthermore, if you use a Likert scale, the data is easy to analyze because at the end of the day, we are going to be taking the data and you have to process it into something tangible, into some findings, right? So that's why I use it. It gives you basically a more holistic view and degrees of opinion about a certain topic. Now, what can it measure? Mostly, it measures these things. So Agreement, frequency, importance, quality, and likelihood and more. So these are quite broad, broad things. And so the Likert scale can be really, it can be utilized for almost any, any specialty. Psychiatrists and psychologists and psychiatrists uses lot because, well, it's great for their types of studies, but literally any type of study, the Likert scale can be used. Alright, so I'm gonna give you some examples. So for example, if you want to measure the agreement with some kind of statement, like for example, I say, chairs are better for setting on than tables. Then let's see if they agree or not. So I would say strongly agree, but some other people might say agree or undecided or disagree or strongly disagree or frequency. How frequently do you sit on chairs? Always, often, sometimes, rarely, never. You know, some people might all only sit on tables. So there we go. Importance. How important is it for you to sit on chairs rather than, I would say, only slightly important. Alright? So the quality, the, you can have different types of scales. It doesn't always have to be like an importance, very important, important. If you're measuring quality, for example, you can use a scale like this. Excellent, good, fair, poor, very poor, or very, very good, good, acceptable, poor, very poor. So the statement could be something like, I think the I think that setting my experience sitting on the chair was excellent, good, fair, poor, whatever it does, the likelihood. How often? I mean, what's your likelihood for sitting on chairs rather than tables? I would say, you know, I don't know. Almost never true. Maybe I really like sitting on tables or definitely not. So there are different ways you can formulate your, your questions. But I would recommend that you use these very standardized skills that I have here. So whenever you are writing your survey, you can just go through this presentation again and see like OK, maybe I'll use this formulation or that formulation. Alright? And so I just gave you a bunch of examples of 5 scales, while they five-point scales, because 123455 points, but they're also seven-point scale examples. So if you really, really want an even more in-depth answer, you can go into a 7 scale. So for example, very dissatisfied, moderately dissatisfied, slightly dissatisfied, and a neutral, and then slightly dissatisfied, moderately, slightly satisfied, moderately satisfied and very satisfied. So in this way you can get even more information. Alright, so those are just some examples. Might tip is to keep it focused and keep it around a topic and keep it specific. So keep it focused. So group your questions together so they're all about the same thing and then keep it very specific. Don't have any ambiguous questions. So let me give you an example. If you just had a sentence that said, what is your satisfaction with the hospital staff, you know, and you just had this only this only this first one. That would be a very bad question because if you only had that, you know, you have at the hospital, you have nurses, you have doctors, you have the secretary you have I don't know the janitor. You have all these people that work at a hospital. So this would be a very bad example because hospital staff is very broad and ambiguous. Okay? What you should do is, well, you could start out with this question, that's very broad, open-ended question, but then you could follow up and keep it focused and group your questions together and say something like, Oh, what is your satisfaction with the nurses and with the doctors and with the secretary? And then, for example, I cross this out on purpose. For example, you would not want to say satisfaction with the hospital food because hospital food, that's completely different topic, right? You could, if you wanted to analyze hospital food, that's good. You could do that. But that would be like another group in your survey. So you would maybe start out with, what is your satisfaction with the hospital eggs and then with the hospital butter. With the hospital plates with the hospital, you know, the the cutoff cutlery that the knives and stuff like that. So group your questions together by topic and that will be good for you because that's going to help you get more accurate results and that's what you want. In the end, you want good results, robust, robust results that you can actually draw some strong conclusions with. Alright, so here are just some potential applications. So you might see what percentage of participants felt a certain way. Now this is a very basic analysis you just see, okay? How many people felt a certain way about this thing, alright? Then you can also sum up the numbers. So for example, if you have a bunch of questions about the satisfaction with hospital staff, you can sum up the numbers and you can get a score, and then you can rank, rank the scores and see, okay, how many people had a score this marsh. And then also you can relate the questions in a survey to each other. For example, if you do a question about hospital staff and then a question about hospital food, you can see that, oh, maybe people that were satisfied with the hospital staff were also satisfied with the hospital food. Or maybe you can draw the conclusion that people that were satisfied with the hospital staff were not satisfied with the hospital food? I don't know. Something like that. Right. So you can relate the questions in a survey to each other or you can relate them to demographics. You can say, maybe I don't know, males were more likely to rate the hospital staff is better compared to female. So you can make these kinds of comparisons. And last but not least, you can use other validated questionnaires in conjunction with the Likert survey. So you're gonna make a Likert survey, which you can also use validated questionnaires. And you might be wondering what are validated questionnaires and that answer, I will answer in the next lecture. So I'll see you there soon. 30. Validated questionnaires and when to use them: Okay, in this lecture I want to give you some examples of validated questionnaires. Alright, so why use validated questionnaires? So you should do this when you're measuring something particular. And you want to compare and contrast your findings to other publications. And want to have a standard method of interpretation and have some robust data. So basically, how should understand them is a questionnaire, is basically just a survey That's somebody has made and has validated. When they're validated it div, uses the same survey on many different populations and seen that. Okay. If they're trying to answer a question, maybe are you an alcoholic? They have given that same survey to so many people, asked the same question and they've seen that, oh, most alcoholics and yes or no to these questions. So I think the best way is to actually give you an example. So if you're going to screen somebody for alcohol problems, you can just ask them, Are you an alcoholic? Right? And then you can just have a Likert survey question. Right? But the thing is people aren't actually going to tell you probably, oh, I'm an alcoholic or not. Or, you know, they don't know what an alcoholic is, right? Even if they're trying to be honest, they might not know. I don't know. They have seven beers a day and a couple of shots of vodka or even alcoholic? I don't know. They don't know. So or you can just ask them how much do you drink? And well, that's still might not be the best way because well, people drink different amounts of alcohol. And when he asked people how much they drink, research shows that people give a lower estimate. So it's really not reliable to directly ask somebody how much they drank or if they're an alcoholic. For this and other problems like this, we use a validated questionnaire. So in this case for alcoholism, we used a cage questionnaire. So I'm just gonna go through this with you so you got to get an idea. So you would ask four questions and they're here. So have you ever felt in year to cut down on your drinking? Have you ever annoyed have people annoyed you by criticizing your drinking? Have you ever felt guilty about drinking? And have you ever felt you needed a first for drink first thing in the morning? So an eye-opener to study your nerves or to get rid of a hangover. So if you responded yes to two of these questions or more, there is a possibility, a real possibility of alcoholism. So you can see that this questionnaire has ask very specific questions. And because it has been used in a number of populations with a lot of people and a lot of studies. You know that this questionnaire is reliable and it can do a good screening for alcoholism. Now, it, of course, it has its problems, right? Every every surveys has its own limitations. For example, with the cage questionnaire. You have it self-reported, right? So people are actually reporting whatever yes. They do need the alcohol or not. So it's self-reported with obvious questions. There's also a social desirability bias because being an alcoholic is stigmatized, drinking so much as stigmatized. So they might want to say, no, no, no, I don't drink that much, you know, just, you know, just a 100 years a week, something like that, but not that much. Okay. So another limitation would be that the person conducting the interview asking these questions, they would have to have an honest relationship with them. So if it's your doctor, they would have to have a good, strong, honest relationship that they'll be able to trust you as a doctrine, make sure that you actually have the best intentions for them. Okay? So for this reason, because of this interviewer bias that may happen, it's better if the, I believe if the survey is anonymous, so if it's done online than they can be more honest. And while they're not stigmatize, they'll know for themselves, you know, okay. I may be an alcoholic. They'll realize it for themselves. Alright. So this was just one example, the cage questionnaire for alcoholism. It was just one example of a validated questionnaire. There are many, many, many other questionnaires for literally every thing you could think of. So I gave one more example for the quality of life and heart failure patients. You can see there are a bunch of questionnaires, the most popular of which is the Minnesota living heart failure questionnaire, followed by the chronic heart failure questionnaire, followed by the Euro heart failure quality of life questionnaire. You get the point. So if you're measuring heart failure, you might want to use a questionnaire to do that. Instead, a survey that you just made. That way, it'll be more robust. You'll know, you'll know that, hey, this questionnaire has not only been validated, it's been used by other papers. So you can very reliably and easily compare and contrast your findings with other researchers all around the world. Now, when you're picking a validated questionnaire, right, they're great, but remember to understand the pros and cons of each questionnaire. So for example, in this example I gave of quality of life in heart failure patients. You might want to go through each of these questionnaires if you're going to measure this and see what are the pros and cons of each and decide for yourself for your particular situation, what would be the best questionnaire to use? Alright, so pick the questionnaire if, let's say the questionnaire is both have very, all have very similar pros and cons. And you don't know which one to pick our, say, pick the questionnaire that is most popular. Why? Because if most scientists use that questionnaire, it's going to be very easy to relate and contrast your findings to other researchers. Also, remember to give credit to the original authors of the questionnaire, right? Making questionnaire is hard work. It takes a lot of time and a lot, a lot of studies with a lot of people to actually make this validated questionnaire. And for this reason, questionnaires are copyrighted, so you have to ask for permission, usually to use it. Some aren't, some are just everyone can use. And last but not least, be mindful of thes right? Because these questionnaires are copyrighted, the people that own them might want you to pay a fee. Now, the fee can be small, like a $100 or can be a lot like $3 thousand, right? So you have to make sure whatever it is that you're doing. Make sure if you if it's free, you probably see if you need to ask for any permission or if there are fees, make sure you have the wallet to actually pay for it. So here are some helpful resources. If you want a particular survey, if you're searching for something very particular, all it can do is just go on Google and search validated survey instruments for, I don't know, heart failure patients or for depression or for alcoholism or for burnout or for I don't know, whatever you're trying to find. And then I have some helpful links here as well. And I'll quickly go through them with you now. So for example, here in this website we have a bunch. We basically have a database of all the surveys for mental health overhead, for military health policy, for quality of care, quality of life. Yeah, so, you know, many different things. So Quality of Life, mental health inventory, sexual problem measures, sleep scale, social support surveyed. Over here we have in this website, we have just basically they've index a bunch of websites and what kind of databases they are. So for example, this ETS test collection is a database of descriptive information of over 20 thousand tests of varying fields with an emphasis on education. Alright, so you can find that specific questionnaire there. And then this website also, you have a bunch of surveys, just a nice database. So you can see if you're measuring attitudes, you can see a bunch of questionnaires, hair, I don't know teacher beliefs, the visual analogue scale. I don't know whatever personality for, for children, questionnaires for emotional intelligence, for health, alcohol use, or whatever. So self-esteem, there's so many different types of questionnaires. And so let's pick just, just a random one. In this case, I picked the job stress survey questionnaire. So it gives you a description of what it's used for, gives you the author's name. So in this case there are two authors, the reliability and validity. So you can see, oh, is it reliable or not? And then over here looks like you have to pay for this one where to purchase. And so then you can go on and see array. If I have to purchase it, and how much does it actually cost? Alright, so I hope you found that a little bit more about validated questionnaires and how you can use them. And I'll see you in the next section. 31. Examples of survey based papers: Okay, in this lesson, I want to give you three examples of survey-based papers so you can start to get an idea of what you could do in the future. What kind of survey study or validated questionnaire you could administer and find out something about wherever you have. Ok, so the first one we're going to look at is a survey study of challenging experiences after ingesting psilocybin mushrooms. And if you don't know, so let's dive in. Mushrooms are psychedelic type of mushrooms. Retake it and you kinda get some hallucinations. Are right. So this was the title of the study and you can see you published by John Hopkins University School of Medicine in Baltimore, maryland, USA. Okay. So this is one of the figures from the study and you can kind of see what they were measuring. So for example, this one on the top right, how personally meaningful was the experience? And so after, you know, taking these mushrooms, and you can see that most people over here, so more than 25% said among the top five and also among the top ten. So this was, you can see quite clearly that this was a very meaningful experience for most of the people that took these mushrooms. Alright, so, or for example, enduring change in personal well-being or life satisfaction. So you can see in most of the cases, it increased very much or it increased moderately, right? And some people, there is no chain, but for most of the people, there was a positive increase in personal well-being or life satisfaction. So this is a great finding because it supports that, hey, psilocybin mushrooms are actually illegal right now as a 20-20, you can't take them. But maybe this study will change that. Maybe actually it shows that there is a increase in personal well-being or life satisfaction and it's a very personally meaningful experience. Right? So for example, these, these studies might actually change hopefully or actual loss. Alright. So here's another study understanding vaccine hesitancy in Canada. So you might know at this point, it's been in the news a lot about, you know, a group of anti-vaccine carriers around the world, people who are completely against vaccination, who believe some, you know, it's bad for them for whatever reason. So this was a study looking at that. Why are people so hesitant about taking these vaccinations? Alright, so a bunch of, a bunch of authors here for this study. Alright? And I want to show you this table because as you can see, the question was based on a five-point Likert scale ranging from not at all prepared to very prepared. So you can see that yes, the Likert scale is used in real applications. Alright, so let's see what this shows. So this is a vaccine providers perceived preparedness and dealing with vaccine hesitant patients. So n 79, that means 79 people were surveyed. Okay, so let's see how prepared are you to effectively provide information about risks and benefits of vaccinate, vaccination. So in this case, 87% were prepared. That's good. But alright, okay, over here, I see that only 68 were. Alright, let's see what question this was. Ok, how prepared are you to effectively discussed patient family values, priorities, and goals. Alright, so you can see that a lot less. We're very prepared to discuss family values, priorities and goals compared to the actual risks and benefits of vaccination. Alright, so this can actually change education in medical school, for example, that schools might start teaching students to discuss, you know, how to talk to these patients who are hesitant about taking vaccines and not only telling them about the risks and benefits, but also telling them about how to discuss patient and family values, priorities and goals, for example, right? Okay. Let's do one more example. So in this one we're going to look at excessive media consumption about covert 19 is associated with increased state anxiety. So you might have heard about covered 19. It's bend just a little bit on the news lately and 20-20. So let's see. So this is the title of the paper by a bunch of PhDs. Okay, cool. Alright. So I took this example of this figure because I think it is pretty, pretty cool. Alright, so we have the density on the y-axis and we have the STA II on the x-axis, axis. And what? The SDS ands for the state trait anxiety, anxiety inventory. So we have the state in pink and orange, red, and then we have the trait STI in blue. And as you can see, there's a significant overlap, but it also differs a little bit according to the density. So I think this is a great graph. It shows how there's little bit of variation among people. Alright? And this, this is just another figure from the same study. This study was conducted in Russia. So you can see this is the Russian Federation map over here. And over here you can see the S anxiety score. So the state anxiety score. And you can see where there was more anxiety on geographically and when, where there was less. So whenever there is more of a red region, there was more and more of a green region. There was less, but it looks like it's pretty red all throughout the board. So people are quite anxious, especially over here and over here in these smaller sticks here. Okay. So now with these three examples, I hope you have some inspiration about maybe, maybe get some ideas during in your head about what you could do. So think about your own service study and think about what you could do, what you want to measure, and how you can measure it. Also, I want you to take into account where you are right now. So whatever country you are, and maybe you're in the United States, maybe you're in Europe. You know, that will be the easiest publication, POP, population for you to access. If you have some money, you could access other populations as well. You could advertise their survey and encourage people to take it on social media as well. Or you can post it online. So I want you to think about your own service study. Think about what you're interested in and what you want to do. 32. Writing your Methods and Materials section for surverys: Alright, now on to talk about how to set up your method section. So in most cases, I would say get your data first. But for survey studies, you kind of need to set up your survey beforehand before you get any of your data. So in this case, I would think of your method section a little bit before even administrating your survey. Right? So first of all, possible subheadings for your methods section could be participant recruitment, right? How did you get these participants? Survey administration. How did you administer your survey? Maybe it was was it online? You know, I don't know the inclusion and exclusion criteria. Right. Because you're only going to be serving a certain population of people that you want, that you're actually setting. Also the measures, what you're actually measuring. This is going to be the main part, right? Because this requires most detail and information for how you're actually measuring it, right? You could do this through a Likert survey. You could do this through a validated questionnaire. However you do it, ok. And then the statistical analysis, of course, which is obligatory, you have to say what statistics he did. Alright, so participant recruitment, This is a big one for service studies because you can make great survey. But if you don't get anyone to answer it or take part in it, it's kind of useless and you don't have any information, you don't have a steady. So I recommend the easiest is just to make an online survey and use an internet. Given internet link online. This can be through email, this can read through advertisements on Facebook or Instagram or wherever on social media, or just a post on reddit. You can do it on a subreddit that you want wherever. And then you have to explain why we're specific people targeted and it has to be specific people that you are studying. Of course, for these survey studies or questionnaires, you have to get ethical approval most of the time. So my tip would be to write your survey and write the proposal and send it early to your ethics committee because it usually takes a few weeks, a month or even two months sometimes depending on how busy they are to get approval from your ethical committee, right? Alright, also, I, I strongly suggest that the whole survey is anonymous because people are going to have a hard time answering truthfully if they're not if they can't be anonymous. So I would recommend to have it be an anonymous survey or an anonymous questionnaire. Right? Okay. And then you have to decide what you're going to do with full versus partial responses. Because not all people, people might start the survey and then the answer a few questions. And then they're like, oh, they get distracted or bored. What are you going to do with those partial responses? Are you going to just delete those partial responses? Or are you going to also analyze those partial response? You have to decide that beforehand what you're gonna do so you can set up your survey properly. Okay, alright, and how the responses would be used. You have to know yourself how the responses are going to be used. Basically you have to say, okay, for your paper, for the science, for, you know, maybe you're going to report the answer somewhere. Maybe they're, maybe you're interviewing a bunch of students and maybe the responses would be used to make a new policy for students at a medical school? I don't know whatever the cases you need to know how those funds that are going to be used in your research and even beyond your research. So not only do you know, but also the people answering the survey or questionnaire. Note that, okay, this is what it's used for. You need to be very upfront, unclear with why you're doing it. Alright, so survey administration, as I said before, administer how? So? I would say google forms, it's completely free and it's a really easy way to set up your survey. Also Survey Monkey is quite popular and it has a free version and it has a paid version. But I like the free version of Google form so you can do that. But if you have a bunch of money to throw around, you can also use Survey Monkey because it does have some extra features if you pay than if you, if you use just Google Forms. Alright? So approximate duration for the survey. You have to tell people when they started. Okay? This will take about, I don't know, ten minutes or five minutes. The longer it's going to take people, the more difficult it's going to be for you to get full responses. So if the survey iteration, if the service so long like one hour, it takes you to answer it. You're going to get very, very, very few people actually answering that survey because, I mean, who has one hour in their day to do a survey? Not many people. So there you go. And when so is this going to be a survey that people are going to complete just once in one setting is it's going to be a cross-sectional survey, or is this going to be a survey? Will people do it multiple times, over a month or over a year? For example, you might do a survey of medical students and you might look at their burnout and the beginning of the year and then measure it towards the end of the year and then see over time what actually happens, what changes. So you have to decide when are you going to do it? And this has to be decided beforehand for obvious reasons. Okay? Inclusion and exclusion criteria. This is important because this is what your data is going to be based on. So for example, it could be based on age, it could be based on English fluency. Of course, if you're have a English survey, it's you have to get people who are fluent in English, right? You can't use English survey on a Spanish population, right? If you do, you have to make sure you're targeting only those English-speaking people. And also, for example, was a survey done previously. So maybe you can have a tick box like, oh, did you do this survey previously, right? And then whatever variable you are measuring. So I don't know if it's heavy. Had a kidney transplant or have you been diagnosed with major depression or have you taken illicit drugs within the last month? Right. So whatever the inclusion or exclusion criteria is, make sure you have that pre-defined so you know exactly what you're measuring. And so you don't have any extra variables in your survey that are messing up your data. Alright? Measures for basically every survey or questionnaire, I would recommend that you do some demographics, ask people about their age, where they're from, things like that. And then whatever you are measuring. So your questions, your scales are validated, surveys, whatever. And then I also recommend which people skip a lot of the times. Just try to have one open-ended written comment. So basically a text box where you have, where you ask a question and people can actually write down if they want to, they don't have to write. But one question we can actually write down in their own words whatever thing that you're measuring, right? So if you're measuring burnout, have people write down, students write down what is contributing to their burnout in their own words. That way, you get a much more qualitative analysis. You can do a qualitative analysis on what's actually going on in the students minds, right? And of course you don't. One note, you shouldn't have too many open-ended questions because it's quite difficult to, It's quite difficult to actually write down yourself exactly like that. And it's difficult to analyze to many open-ended questions. So I will have just one open-ended question in your survey. Alright, and statistical analysis, of course. So you need to have your descriptive statistics, mean, median mode range, things like that. And then your associations because you want to make associations between the different questions. So, I mean, there's so many different types and you're going to use different ones for many different whatever situation that you're in, whatever you want to analyze. But it might prepare some correlation Spearman multiple regression analysis, binary, whatever, blah, blah, blah, odds ratio. So you need to figure out what you want to answer. Also, from your survey. You don't need to have a completely fixed idea about it before you start. But try to get some kind of thinking, you know, try to think about it a little bit beforehand so you can ask the right types of questions. So you can make those associations, right? So that's how to set up your methods and I'll see you in the next section. 34. How to write a study proposal to your local ethics committee: Okay, so if we're going to do a survey study or a questionnaire study, you'll probably have to submit a study proposal to your ethics committee, right? So this will give you a template and an idea of how to write it. It's not too long and it's not too bad. And you can download this and kind of customize it for your own studies. Alright, so here we go. First, you're gonna give some general information. So the protocol title, in this case, burnout among medical students that awesome Medical University. Is there a difference in student burnout among home and international medical students? Alright, so that gives you a basic idea of what the study is going to be all about. And then I'll put today's date. I'll put any sponsor funder in this case, none. But if you do, of course put that, then the investigators, we have John Smith and John Doe, both MDs and PhDs. And then you're going to give the name, you know, basically the affiliation, so university or the place where they work or address and email. And then the research site. So the name of the university, probably for the same steady countries up code. Okay. And then the project summary, This is where you're going to tell why you're actually doing what you're doing. So in this case, medical students often feel, feel overwhelmed and exhausted with the sheer amount of coursework requirements and responsibilities. International medical students studying have to overcome an extra set of obstacles, such as being far away from home and adjusting cultural differences in the country. So objective in our study, we aim to analyze student burnout and its consequences at awesome medical university. Okay, so now we have the rationale and then we have the objective or right, great, let's see how we're actually going to do this. So the methods, the methods to administer a questionnaire at home when international students in all four years of study. So one through four, all the questionnaire consists of four parts. General questions, the modified Oldenburg Burnout Inventory, and this is just a validated questionnaire for assessing burnout, the PHQ-9 scale for depression. And this is just another validated scale for depression screening. And the cage questionnaire. And as you know, the cage customer is for alcohol screening problems. For alcohol screening problem, great. The survey will be administered online on Google Forms and the link to the survey will only be available on the University online communication system. A student and teacher communication platform only available to university students. Okay, so this is just an example of how it's going to be done, right? How it's going to be administered. So in your case, be like email, maybe our university has an email system or it could be on social media or wherever else you're doing it. Make sure you read down here. Alright, and then your populations. This is why you need to know kind of exactly who you are going to be administering it to. So in this case, home and international students at the university and the timeframe. So in this case, the survey will be administered during the 20, 20-20-20, one academic year. So then I give the specific dates, so just random dates here. Alright? And then the expected outcomes. This is important because you need to give more than what you think you're going to get. So expected outcomes, in this case, we expect one hundred, five hundred responses from medical students. Now, obviously, let's just say for the sake of example, I, sorry, I expect only 500 responses, right? But I'm going to write down one hundred, five hundred. Why? Because I want to write down even more than what I expect. Because if I, let's say I write down 500 here and then I get 600 responses for some reason. Then, hey, that's not good because I wrote down, I only expect 500, but I got a lot more. So it's better to way, way, way, overestimate and write down like a 1500 when you only expecting 500 then to underestimate. So there's some tips and that's basically it. And then afterwards you will basically copy and paste your actual survey and that will be your basic proposal to the Ethics Committee. So not too bad and totally doable. And you can use this right here. I'll, I'll leave that download so you can download it as a template. All right, so I'll see you in the next section. 36. The results section for surveys: Okay, in this lesson, I just want to give you some general tips on the results section for surveys. So first of all, you're going to say if the survey was completed, right? So if people had a partial response, are you still going to count those those responses? Or are you just going to count the full responses where they answered all of the question? Or for example, what if you were just looking at burn out and people that have depression have been diagnosed with depression. And you want to exclude all those people that don't that answered the survey. But they actually didn't have depression, right? So if you have any situation like that, you need to say why some responses were excluded. Justify it, right? And where do they come from? So they could have come from a link on our Facebook page or Reddit or email distribution list or just a word of mouth or I don't know. You just went up to some random people on the street and they're like, Hey, do you want to answer this survey? Okay. So wherever they came from, you say where they came from. If he did it on the street, you say, oh, I did it on, you know, ask people on the street in New York, you know, whatever. Okay. So participant demographics and characteristics. Basically, in every survey study, you will have to write down the demographics and characteristics because you're defining your population and then your measures, of course, and this is particular for each study, whatever you're measuring. So all right, let's go through an example so you get an idea of what I mean by demographics and categorical and numerical data. So you might be familiar with this study. This is the same psilocybin study that I talked about before. So we have some categorical variable. So the gender, the education, the race, you know, Hispanic or Latino. 37. What is a YouTube quality evaluation study?: You've made it. Welcome to this section. In this section I'm going to be teaching you how to write a YouTube quality evaluation study. But first things first, what is a YouTube quality evaluation study? Well, I think let's start with something you might know. Youtube. Youtube. You go on there probably all time to check out. Whatever. I mean from cat videos to YouTube is playing video games to financial advice to, and most importantly to medical advice. There's a lot of medical information on YouTube. And the problem with it is, I mean, it's great. There's medical information. But anybody can upload medical information on YouTube. And the thing is patients, oh, look at this stuff. Because YouTube is a most popular video site in the world, and it's the second most popular site before Google in the world. So it's, it's really popular. People go on at, people view it. And patients who don't know any better might actually trust it. So it's important to go on YouTube and look at the quality of the medical information on there. And that's what your quality evaluation studies actually going to be. We're going to go on YouTube. You're gonna watch a bunch of videos and you're going to evaluate them. But to get a really good idea of what your paper is going to be about, Let's read an, an abstract of another paper of a YouTube quality evaluation study. Alright, so let's begin. The one I chose is the reliability of YouTube videos in patient education for glioblastoma treatment, right? So glioblastoma is this brain tumor and it has a horrible prognosis. And they're looking at the reliability of these YouTube videos and look a bunch of authors and they're from Jacksonville. Well, the first author is from Jacksonville, from Mayo Clinic and some of the other authors too. So Mayo Clinic, as you might know, is one of the biggest and most prestigious institutions, hospitals in the world. So if h1, a doctor from there's reading about it, I think it already tells you that studies like this are clinically relevant and that they can be published and that they are published in this journal. Okay, so let's go through this study, the background. Alright, so they say glioblastomas are one of the most devastating primary tumors in humans and often results in minimal survival rates. Yeah, that's unfortunately very true. Over the past two decades, patients have access the internet to obtain information related to their diagnosis? Yes. In the study, we aim to evaluate the accuracy and reliability of glioblastoma related YouTube videos. Alright, so you might be wondering, and we're just going to watch some random videos. How do I actually, you know, do anything with it? Alright, so let's go on to the methods. And June of 2017, a search was conducted on YouTube using six key words. Videos were sorted using relevant space cranking option. And by the way, this option is the default option on YouTube. If you don't do anything, this is what you get. And the first three pages for each search were selected for further analysis. So they basically watched 30 videos, three independent videos. Viewers evaluated the videos using the validated discern tool. Alright, so three people watched a bunch of videos and they use this discerned tool, which is just questionnaire, right? 16 questions that you ask yourself when watching these videos. To evaluate the videos, evaluate the treatment in this case of glioblastoma. Alright, so the results, what did they said? After sorting through more than 23 thousand videos, nine videos were identified and include it for analysis. So in this case, only nine videos were really about the treatment of glioblastoma. Of the nine videos analyze, 88% were from hospitals affiliated with the prestigious universities across the country, maybe Mayo Clinic, I don't know. Of the nine videos included in the analysis. Two or 22% scored above a three. This three just means this is part of the discern score. So three, it means it's a pretty okay quality. But you'll find more about that later. There was an average fifty-five percent overlap in the videos analyzed by key term and the keyword search of malignant glioma treatment had the highest percentage of videos above a score of three. Okay, so basically these guys put in keywords when they say they use keywords over here, six keywords they're just saying they put in keywords like treatment for glioblastoma or glioblastoma treatment or as they say over here, malignant, malignant glioma treatment and the hit search and they just watched some videos there, right? Okay, so conclusion, many patients with glioblastoma and their families access information on YouTube to familiar, familiarize themselves with the epidemiology survival, and treatment options for this form of tumor. However, the information that is currently available online is not monitored or vetted using an official filtering process prior to its release. Yeah. We already said this, right? This is this is why we need to conduct the study and they're just restating this so they prove that their paper is actually necessary. Alright, let's continue reading. Medical institutions must work to produce more peer reviewed content in order to improve the availability of credible health information on internet platforms. Alright, so I think now you got to kind of get an idea of what a study like this is, right? You watch videos on YouTube, on a particular topic. In this case, clearly less somewhat treatment. And then you evaluate them and you write a paper about it. What kind of information is out there? Is it good information? Is it high quality? Is it reliable? Is it something that patients can trust, and where does it come from? So that will be what your study is all about. And we'll talk more about some examples which Journals might publish something like this in the future videos. So I'll see you soon. 38. Examples of YouTube quality analysis studies: All right, get ready and congratulations for making it this far. And now get ready to get into the world of YouTube evaluation studies. So the most important question you're wondering, because you want to get published with journals, publish YouTube studies. And the answer, I'm going to give you a little hint, almost all of them. All right, so let's start. I'm gonna give you five examples. Now here is YouTube as a source of medical information about spinal cord stimulation. And you can see it's published in neural modulation, which is a good journal and impact factor for about four. And this is one of the higher ranked journals and neurology. And this was published his original paper. Here's a DOI published in 2020. So you can go check it out reader if you want. So, wow, pretty, pretty YouTube paper published in respect to journal. Alright. Can we go even more? What about other types? All right, here's the fun example, quality of information and YouTube videos on erectile dysfunction published in the Journal of Sexual Medicine or write impact factor of three about publishes original paper in 2020. So, so pretty good. You can, you can publish. And for, you know, a YouTube study on neurology about erectile dysfunction. You know, you can pretty much published a YouTube study on anything. And you can find a journal because, you know, there's journals for literally every subject that pertains to whatever topic you're trying to publish. The assessment of YouTube as an informative resource on facial plastic surgery procedures. And this was published in jama. Facial plastic surgery would impact factor of about 4.73 so forth. And this is one of the highest in this category published in 2019. So if you guys don't already know Java and the jama set of journals, this is a SR Journal rate. It's one of the biggest journals in the world so that it was published in jama facial plastic surgery is pretty huge. Okay, this means they can publish and we're the world's biggest journal as a YouTube quality valuation study. All right, let's do one more or two more. Quality and reliability of YouTube videos as a source of patient information on Rhino plasticity. And this is published in jama utterly oncology, Head Neck Surgery. Alright, with the impact factor of 3.8. And this is the highest otolaryngology journal in the world. Sorry guys, if I'm not pronouncing otolaryngology correctly, it's kinda hard to pronounce. Ok, anyways, this was published as a research letter. A research letter is just a shortened version of an original paper. So an original paper will be about how it'll be about 4 thousand words, but a Research letter, it'll be somewhere around a 1000 words, so it'll be a lot less. It's just able to give you the findings in a very, very short and concise way, which is nice for researchers because we, you know, you don't want to read a whole paper. You want to get the findings right there and then all right. Here's a DOI and it was published in 2019. So what I'm trying to say is these papers, it's 20-20 right now these papers are still being published. Ok. And last I saved this one for last. Youtube was a source of information on immunization, a Content Analysis published in jama. Jama is one of the biggest journals in the world with impact factor of whopping 45.5. So like 46, Oh my god. And it was published as a research letter in 2007. So that's published in 20071 of the biggest journals in the world. So yeah, you can basically publish these studies anywhere. Whatever topic it is from erectile dysfunction to surgery to, to some sort of neurology topic, whatever you want, you can publish quality evaluation paper in, and if you want to write something like this, I gave some more examples of good examples studies that you can read and follow. So for example, this one is derive the reliability of YouTube videos and patient, patients education for glioblastoma treatment published in the Journal of Clinical Neuroscience and the reliability of YouTube videos describing stereo stat, stereotactic radiosurgery, a call for action. So these are more neurosurgery topics that have been published in cool journals and this one in world neurosurgery, which is a really respected neurosurgery journal. So the possibilities are endless. The reason why I gave you this topic is because there are YouTube videos on literally every topic out there. And it's your job as a researcher to find out the quality of those videos. And then see, because if you look at the quality of these videos, you'll see what information the patient is actually obtaining, Right? So for all these, all these studies, they're literally going and they're watching YouTube videos and rating them. So your question might be, how do you rate YouTube videos? Well, that's a great question and I'll see you in the next section to give you the answer. 39. The DISCERN, JAMA and GQS instruments: All right, so now let's take a look at the YouTube evaluation instruments. So there are basically three of these, and these are the instruments that you can use on your study. So first, the discern instrument, that's the 16 part questionnaire, the global quality score, which is very similar to the 16th question of the cern, but it's a score on its own. And then the Journal of American Medical Association instrument, or shortened as the jama instrument. Alright, so let's go over these three instruments. First is the discern instrument. This is the biggest one. This is 16 questions. And on the website it says that cern is a brief questionnaire which provides users with a valid and reliable way of assessing quality of written information on treatment choices for a health problem. So it's directed towards treatment choices. And it says written information because that was what it was originally supposed to do. But it can also be used for videos, and it has been used many, many, many times for YouTube videos. And you can also use read the original paper. And it says that you can use it for other matters. And here's a guide on the website where you can learn a lot more about it. Instead of reading the actual scientific papers, it's much easier to go on the website. Okay, so these are the 16 questions of discerns. So let's go through a few of them. The first couple of question, questions are refer more to what the, what the piece of information is saying. And then the next question, select from nine, from nine afterwards. It's saying more about the treatment options. All right. It can be divided like that for the first eight questions and then from nine onwards, all right, so first question, are the aims clear? Second, does it achieve its aims? Is it relevant? Right, so for these questions, you would give it a score of one to five. There are some exceptions like for example, if the aims are, if the aims are not clear, if you give it a one which is lowest score, one, one-to-five, then does it achieve its aims? He wouldn't give it any score, right? Because if the names aren't clear, you wouldn't give it any sort. But other than that, you're basically gonna give the one-to-five scale for all these questions. So is it relevant? Is it clear what sources of information were used to compile the publication other than the author producer. As a clear, when the information user reported in the publication was produced, is it balanced and unbiased? Does it provide details of additional sources of support information? Does it refer to areas of uncertainty and then it gets into the treatment. So there's a describe how each treatment works. Is it described the benefits of each treatment? Is a describe the risks. Does it describe what would happen if no treatment was used? That's an important question. There's a describe how the treatment choices affect overall quality of life. So these are a bunch of questions for each video that you're going to watch. And I want to pay particular attention to to, to, when you're watching the video, you need to ask yourself because for example, here it says the set provide additional sources of information other than additional source of support and information. So you need to ask yourself if in your study you are going to be looking at the video description cap because sometimes in the video description they do have links. So in your study, you have to define if n your methods and materials section. Will you be looking at just the video and the title, you know, or will he also be looking at the video description and look if there are additional sources of information there. Right? So sometimes or you could have methods and materials where you say, well, you only look at the video description if the person in the video says there is additional sources of information in the video description, so check that. So depending on how you analyze it, you should state it because that will affect your scoring for this question. And some of the other questions as well. Okay. So let's go on to the next one. How to cite the discern instrument. Alright, so this was the original paper which looked at the cern as an instrument for judging the quality of written consumer health information on treatment choices. So make sure you reference this study when you're using the discern instrument. But also this study because this is the evaluating the reliabilities. This was done in 1999 and this was done in 2002. And this is just evaluating the reliability of the cern. Basically saying that yes, it's valid instrument are right. So the global quality score, before we go, before I go to the global quality score, I want to go back to the discern to question 16 and you can read question 16 here. Alright, so. 40. Database Template for recording your results: All right, so I wanna make things super, super easy for you. So I'm gonna give you a template for your database on how to do everything and all the data processing for your study. So for example, let's say you want to do YouTube quality evaluation on spinal cord stimulation, of spinal cord stimulation, just a background. It's implant that a neurosurgeon puts in your spine to help you feel less pain. And it's pretty cool because it reduces your dependency sometimes on other opiates and other painkillers. So you don't have to be taken drugs all the time. Pretty cool. But anyways, alright, so let's say you're doing your research on that. Now, you go on YouTube and you, your first keyword is spinal cord stimulation, right? So you go on YouTube and you type spinal cord stimulation. And for the first 30 videos, you literally just copy the links and you paste them here. So all over hair, you have all these links. Okay? And by the way right here, this left part, I made it. So even, even if you scroll up or down, this this only the left part stays the same and it's like frozen, but only the right apartments. And you'll see why I did that anyway. So you copy and paste the links, and then you choose, you choose another keyword. For example, spinal cord stimulation, chronic pain, because that's what patients might be searching for. And because it has to do, you get it if you have chronic pain. So then you also paste the link regardless of if there are any repeating videos. And then he is search YouTube, spinal cord stimulation, implantation, for example here. And then you paste the video. So you're basically, in this case there are three keywords. So 3430 videos for each keyword. So now 30 times three is 90, so we're going to have 90 videos altogether. Then you're going to choose a unique videos, right? You're gonna go, and you're going to choose only the unique videos here. And then you'll get only. What I mean by unique videos is you're going to delete all the repeated videos and just have the unique videos there, okay? Then you and your partner. Whoever your partner is, you're going to actually look at watched the videos. So let's say you watched the first video. You click the link over here in green. These are the unique videos that's for sure going to watch. You're gonna click the link and then you're gonna, you're gonna go through the certain criteria. And I have the discern criteria right here. For example, you are the aims clear? Achieve its aims. Is it relevant? So in this case, I just plugged in some numbers. In this case, I gave it a five. Yes, the aims are clear. Five, yes, it achieves the same. Remember the scale is from one to five. Ok, and Excel will automatically calculate the total score. So I have the formula here already for you. Then you and your friend will also calculate the jama score. And remember this is about authorship, attribution disclosure currency. And this is a 0 to one scale to, let's say I put 0 here and a one here. I'm just plugging in random numbers just, just for an example. So in this case it got a one and then I'll have the total score summed up here. It's not right now, but I'll do it basically. But, oh, this is a good idea to teach you how you can just press equals and press some. And boom, it even gives you the suggestion. So some C2H5 to see 28, press enter. Great. Now you have the sum. And then if you want to use the formula for multiple rows or columns, whatever, you just take it and you just take it at the very edge and just drag it along and boom, now calculated it for all of them. Alright, so you do this and I just put my name here as John Smith, but you're gonna put whatever your name is. And the second researcher, whoever it is, is going to be the same. And I color-coded hair blue. So this is John Doe, whatever. You're gonna do the same thing. And you're gonna go through all the videos and you're going to do this discern and do this jama thing for all the videos. Alright? Also you're going to write down some other stuff like qualitative information. Like for example, was the information clear? And this is going to be specific for your particular papers. So this, my example paper, this template is on spinal cord stimulation and so it has to do with chronic back pain. So I'll say Oh, where their symptoms of chronic back pain explained them video. If there were I'll give it a one. If there weren't, I'll give it a 0 or I'll just leave it blank. Depend, depends. You can just leave it blank or put a 0. You know, I like to put a 0 because then I know that I have done it, right. So then I don't get confused like, oh, did I just miss it or did I actually put it? Ok. So then the results of the treatment steps on how to do the procedures, the actual surgical procedure was a prognosis discussed. Was there animation where they're real images, I mean, radiological findings where their diagrams used was spine anatomy explained, was there a doctor speaking, was their patient experience. So I'll just go through and put output one if it was there and a 0 if it wasn't there. Then I'll do the same thing with the source of the upload. So was there did the person who actually uploaded the video, I'll look at the channel name. Was that a physician was at a hospital like Mayo Clinic. I don't know. Whatever hospital you can think of. Johns Hopkins Hospital, I don't know. Was it a health channel like promoting health? I don't know. Was an educational channel or was it some other channel? Maybe it wasn't news channel. And then you can explain chair for example, in this case it was NBC News, or in this case it was Seattle Science Foundation or in this case it was CBS this morning. So after I see a couple of these, I'll make another rho here, and I'll just say news, news channel, right? And then I can have it like that. Alright? And then there are other very quantitative elements that you can take from videos like the total number of views, the duration in seconds, you should convert it into seconds, right? Video description, wordcount, video description, link count, average minutes watched overall refers the word spoken per minute, the time since upload, you can go to this date because YouTube gives it time since upload as a date like, oh, you know. February 7, 2007. So you can go on this website and it'll help you convert that date, that t8 to now. And it'll give you the days right. Because you need the days instead of just, you know, January wherever it's easier to analyze it when you have oh, it's been 877 days since the videos uploaded till now, told you know, this date. Okay. Then you can record the channel subscribers, the average daily views, the average channel Daily subscribers, the number of comments, likes, dislikes. If there were any video tags or channel tags, the power index, which is, well, It's different than the lack ratio. So I made a mistake here. I should make a different one for the lake ratio. Glad I caught it now. And this is just a formula which I will make sure it's ready for you guys. And then the name of the channel. So here it was Mayfield brain and spine, here it was the spine and paint Institute of New York, whatever the name of the channel is. Alright, so this is the basic template. You're going to go through this and all your data collection is basically just going to be gone through this entire file and just plugging in numbers. It sounds kind of boring, but this is the main part of your data collection. So you're going to go through many videos and just wash them and put into discern and all the other information. Ok, so after that you're gonna go on the Chrome webstore and you're going to search a vid IQ vision for YouTube. And this is a plugin. And I want you to click this, and I want you to actually install this because this will help you with all the statistics on the, not only just the views, but other statistics from YouTube. Alright, so we are here on YouTube and I just wanted to show you the vid IQ vision plugin. So here it is, afternoon solid. You'll get this view. So here it shows you the, well, you can always see the views from the actual video and the data was uploaded and of course the title and maybe some of the likes and dislikes. But here it gives you much more information. So you get the views, you get the, all the other things like if you have a new refers to the video or the description word_count, the Video Description word_count, the Video Description link count, how many refers There were, right? So these are, if you ever confused, you can just hover over and it'll tell you whatever. It'll tell you about. Compare views and last in the first 28 days. I don't know, it doesn't say anything here. But it says about the channels. So the average daily views of a channel, last reason 30 glad last 30 days, tells me a bunch of information. And it also gives you the video tags and channel tags. So all this information that you're going to be recording is going to be handy. It's going to be done really nicely if you have this plugin. So I encourage you to download it and you do need the Chrome browser to do it. So if you don't have it already, you can download the Chrome, Chrome browser and download this video, that IQ extension. This'll help you. Sometimes I'll tell you some information is not on there, so some videos just don't it doesn't appear here the information. So in that case, just leave it blank or tried to get as much information you can. But yeah, so that's it. And this is your database. This is how you get your information. And now you can actually move on to the actual data collection of your paper. 41. Common excel problems with solutions: Common problems my students have had. So let's say you search YouTube for spinal cord stimulation and then you list all your videos here, right? And then you search YouTube for spinal cord stimulation, chronic pain, and you list your videos there and then you choose another keyword, whatever. And you list your videos here. In this case it's spinal cord stimulation. Alright. So how do you find and all these videos, how do you find the, how do you delete the repeating videos so you only have the unique videos? Well, I'm glad you asked, so I'm going to show you now. So what you can do is, okay, so I have this example here. I just have no link one, link two, link one, link three, just so you can easily see what I'm doing. So I'm gonna highlight everything. I'm gonna go up to data. I'm going to scroll down. And I'm gonna go to remove duplicates. And it'll give me this pop-up. Remove duplicates. Yep, you select these two and remove duplicates. Alright, and now told me five duplicate rows founded removed, and five remain. Ok, so in this case now I have one to link 1-2-3-4-5. Great. It removed all the duplicates, and now I only have those unique links. And you can do that the same thing right over here. I just did it over here just so you guys can see what was done more clearly. Alright, now, one more problem people have is, what if I want to take this and make it look sideways, horizontally, this vertical row, and what if I want to just transpose it? Okay, that's easy. You just highlight whatever you're taking. You go and copy. So you can go edit, copy. And then all you do is you go somewhere else and you go to edit, paste special and paste transposed. Alright, so now you have this and it's transposed. Alright? One more thing that's kind of confusing sometimes is this. Let's say you have your total score here. So over here, this is actually a formula which takes the sum of these, of these cells here. And okay, if I copy this, I copy it and let's say Paste it. I don't know somewhere. I paste it over here. Okay, so in this case I'm copying 47 and I'm pasting it over here. But when I pasted, I get this random number, I get 121. Why don't I get the number 47 when a patient well, the reason is that you're actually copying not just the number, you're copying the actual formula. So what it's doing right here, it's saying in this formula you are taking. And you can see in this box, you're taking all these numbers and you're summing them. All right? And so what happened here when you copied the number, you're actually copying the formula. And so now what it's doing is it's summing all those numbers according to the formula. What you can do if you don't want that is, of course, copy it like normally just go to edit, copy or Control C or Command C if you're on a Mac and literally just go to edit, paste special and paste values only. Now if you paste just the value, now you'll just get the number 4747, hair 47 there. And now this is just the number. There is no formula. This is just a plain old number. Alright? So these are some tiny things, but they're a little bit confusing. So I just wanted to tell you some of these tips now. All right, see you in the next section. 42. The Methods section for a YouTube study: Okay, the methods section for your YouTube evaluation paper. So you're going to follow all the rules as before, but I just want to give you some pointers, especially for this paper. For this paper you're going to choose synonyms for keywords, so don't. So for example, if you're going to write a paper about stroke, the quality evaluation of stroke videos. Ok, great. But you can't just use the word stroke because patients, you know, they might not use the word stroke. So you have to use other synonyms or other colloquial terms that might refer to the same thing. So for example, stroke or brain attack rate, hemorrhagic stroke, ischemic stroke, transient ischemic attack. So use all these keywords. If you're going to use, if you're going to do paper about stroke or just like anything else. If you're going to do it about hydrocephalus? Don't just do hydrocephalus do water in the brain. Do you know? I don't know. Big ahead. Choose keywords that are not only technical, but also, you know, that every day people would use and and use more than one, I would say use at least, at least more than one keyword. Because for stroke, you can see that it's very easy to come up with more keywords. The inclusion and exclusion criteria. You have to put a lot of thought into this because after you do your study, it'll be difficult to change it. So you have to decide if you're going to do 30 videos per search. I recommended because most people don't go past 30 videos. Are you going to analyze duplicates? Probably not. What language are you going to analyze? Well, I know English, but if you know other languages well, you could also analyze those videos. What about videos had no audio. Okay, well, maybe you could exclude those. What about videos exceeding 30 minutes in duration or maybe exceeding it Knauer, whatever the cutoff is, you have to say that Oh, more than 30 minutes or more than an hour. We did not analyze. And then videos just unrelated to your topic, will you exclude those? Are willie even analyze those? I don't know, sir. Decision. Will you be signed into a YouTube account while you're looking at the videos, right? Because hey, YouTube might tailor your search results based on what videos, what videos you actually use before. So I would recommend that you are not signed in to any YouTube account or into some Google account when you do your searches. And how many raters really have, right? Well, we have two or three or four or maybe more. And who will you aerators me? Will it be doctors? Will they be students who maybe just everyday people, you know? So you have to define these things, especially for this study before you get started. All right, so for the methods and materials section, I recommend that you use some kind of flow chart because it can be a bit confusing with all your criteria, how you evaluated them, and which one is you included and which ones you did not include. So this one is great. They said, okay, videos identified from the YouTube search that had 150. And then videos after the duplicates removed were only 108. So they removed about 40 videos. 42 videos. Okay. And then the videos that were screened were a 108. Okay. So they were all good. And then they excluded even more videos. They excluded 39 videos because somewhere in foreign language, somewhere more than our long, some had no audio somewhere just live video and apparently didn't want evaluate those and some were unrelated. And then so finally, they look at the videos that they actually analyzed, and that was 69 videos. The videos are finally assessed in their paper. So what I recommend is that you take a moment and before writing your own paper, you read the methods of other YouTube papers. It could be the methods of this paper. I have the citation right here so you can read that. But I want you to read the methods of at least two other YouTube papers so you get an idea of what's been published and what's out there, and how you could develop it for your own paper. Alright, I'll see you in the next lecture. 43. Making the figures: bar and pie chart: Okay, so for this tutorial, we're going to be making this beautiful figure right here, this pie chart, and also this graph right here. So let's make the pie chart first because circles are my favorite. Ok, so let's see what this is for saying. This is saying where the upload source was. So for example, was it from an educational channel like hair or from a hospital or from uploaded from patient or for miscellaneous or physician, right? So these are just my categories. But of course, if you want to have another category, you can have another category, right? This is your paper. Okay? So you have, you put a one, you know, if you had a hospital. So basically how the template is set up is that it will, it will sum everything up. So for physician we have two Uploads, right? It will sum everything up here you can see for the hospital, of course it'll sum everything up. So now what you should do is take this and paste it, copy that and paste it here, paste values only. Now after you paste it, I wanted to actually go to data and I want you to sort range. And in this case, data sort range is e to a. So the highest is first and the lowest is last, right? And that's what I did here. So I'm just gonna delete that. I did the exact same thing right here. And then I paired up, in this case, the the label with the number. So in this case, I know that 34 was with hospital. So this should be with hospital. Whoops. Let me just do this for you. Okay. So 34 was paired up with hospital, right? So we're going to copy hospital for their health channel was 11. So 11, health nine was with minus2, educational, five was with other. Ok. Other. I'm going to delete the explain here. So basically this is Muslim miscellaneous. And then two was for physician. Okay? Two was for physician. Alright, so now we have this and the reason why we ordered it from biggest to smallest is just so the pie chart looks nicer. Alright, so let's take this and all you have to do is go up here to Insert Chart. And let's wait a second for the chart to come up. Ok, so we're here and click the chart type and go down to pi. All right, now, once I've clicked it, the figure is actually somewhere here in the paper. There it is. Sometimes it's somewhere else in the paper. Ok, so now we have a pie chart. Now there are different variations. If you want a donut chart, great. You can have a doughnut or you can have a more 3D looking figure if you want. It all actually depends on you. I personally like the classic pie chart, but the doughnut is also cool. Let's go. Let's go the classic pie chart. Alright, so now we have these labels. One thing that's wrong here is that these labels are way too small. If you have labeled this small, your, when you submit the actual paper, they're going to complain. They're gonna say, Hey, make these labels much bigger. So what you can do is you can just click those and go over here. Just, just double-click any of these labels like, okay, I double-clicked other right. And then it'll take you to this, to this drop-down. Alright? And legend font size, you can just choose an 18. Alright, now it's much bigger. That's great. And okay. I also want to add labels. So I want to see in the actual chart how many videos are there. It gives me the percentage, but I actually want the actual value. So let's see if we can do that. Or let's see chart titled Access. Maybe the legend. Now not the legend. Let's see. Alright, so I figured it out. You go to pie chart and you go slice label, and then you can put in the value, boom. And now we have the value. You can also do percentage, but we already have the percentage here. So you can just click the value. And also, right now this is really small, the journalist gonna complain. So we can put the font size again to 18, or maybe even larger. How about 20? Right? Now you can clearly see it. So now you can see, okay, for example, health channels uploaded 18% of videos. And this translates to 11 actual videos. Alright, so that's how you make your pie chart. Let's go on to making this cool looking chart. And we're pretty much gonna do the same thing. So over here, you chose your video content like for example, you know, was there information about this, where their symptoms, about this, where the risk factors were, the results of treatment was their prognosis animation. I don't know, all that sweet stuff. So you tallied all that up, right? All these zeros and ones, whatever you put here. And you're gonna go all the way to your end. And you're going to tell you all that up, right? So this is just a sum of, sum of everything right here, as we can see, right? So pretty easy, okay? And we're going to do the same exact thing. So we're going to copy this. So Control C or Command C on a Mac. And we're gonna go here and we're gonna edit, and we're going to Special Paste values only. And then go up to data. And then we're going to sort range eta z. This makes it from smallest to biggest, Right? So that's what I did here. And then as before, I paired up the numbers with what was there. So for what I did actually was I made it smaller. So if it says, I don't know where their diagrams, instead of saying we're there diagrams, I just put diagram so it is a little bit cleaner for the chart. And then once you have this, all you need to do is go here, insert chart. And there we go. And you can have whatever kinda chart, but I prefer the bar chart like this. So click that. And now let's go find it because it always gets mixed up. Okay, here it is. Alright. So now we have this chart looks pretty good. The actually the size of the letters, everything looks fine. But what I would like, just like in my just like in pie chart, I would actually like the numbers here. So how do we do that? Well, it's pretty much the same thing. Pretty much the same thing. Double-click. And you get all the, all the, all the options. And in this case we're gonna go to Series and the drop-down comes and you're going to press Data Labels and boom, it's gonna give you a Data Labels. And if you want, you can make them bigger. So for example, the font, if you want it really big, make it 18. And then you can see it really, really clearly, but that's a little bit too big. I'm gonna keep it. I don't know, 16 or even smaller, 14. There we go. That way it fits in these bars. And if you want to make it bigger, great, make it bigger. There it is. Now you have two beautiful figures to add in your manuscript. Just like this. 44. How to import your Excel file into Statistica: Alright, and this tutorial, I'm gonna show you how to import your Excel file into statistics. So it's pretty easy just go to File Open and in this case, find whatever your file is. So in this case, I have mine hair open and import all sheets to a workbook. Hit that. And then four. As for me, I have this check, get variable names from first row because the first row has all the labels, right? So if that's the case for you, please check that box and then I'm going to select, okay. And now you see on the first row it has all the labels and then of course all the data. So when you're setting up your Excel makes sure the first row has all the labels because if you don't have labels, you won't know what the data is four and then have your numbers. So, all right, now here's your file and now you can get started with your statistics. So I'll see you soon. 45. The count function: Okay, in this section I'm going to teach you the basics of statistical. So in this section we'll learn about the count function, the t-test, the Mann-Whitney-U test, and what's the difference between these and when you should use them? The normality test, test, testing data by a 0 or one or whatever value you have to identify something and custom sorting of data. So first let's start out with the count function. And this is easy. This will literally just count how many zeros or ones or whatever value you have in a big long list so you don't have to manually. Alright, so we have statistical open and now we're going to go to, first of all, you'll probably be at home. So in portrait file from Excel, have all the data as it's presented here, where you have the label up top and then you have everything going down. So vertically, not horizontally but vertically. And so let's just go through this file real quick. We have, in this example, a YouTube file, a YouTube analysis file like it doesn't explain the physiology sciatica, does it describe the causes of Sirica? And then one is if it does and 0 is if it doesn't. And then of course there's other information like the cern for each video, the average interviews or comments like ratio, the video Power Index, and the duration in seconds. Alright, so first of all, we're going to go to statistics. We're going to highlight. Let's see. Okay. Let's say I wanted to see how many videos showed me the diagnosis. Then I go over two. I'm going to highlight that covert to basic statistics. I'm gonna go to frequency tables. Click OK. We'll get this thing come up and then we just hit summary on the top-right. And boom, we get the summary. Alright, so the category here, it says 0 and one, right? And those were our values. So for 0, the count is 65. So 65 of the videos had no, you know, didn't say how the diagnosis is made and 14 dead. And then they give other information by cumulative count, right? Percent. And cumulative percent. Overhead says missing. This is this says missing only because we had a bunch of empty cells, right? Empty boxes. So it says missing. But so this is not really relevant right now. So that's basically the count function. And I'll see you in the next video. 46. NORMALITY: Alright, welcome. In this lesson we're going to learn about normality, about the Mann-Whitney-U test and the student T-test. Okay? But before we actually start learning about these statistics, I want to give you a sort of understanding of why we are going to do these tests. All right, so in this case, this is my youtube database and you probably have yours if you're conducting your study. So we have some data here where we put things into groups, put the videos into groups. So for example, was the darker doctor a speaker? And we have a one if there was a doctor speaker and we have a 0 if there was no doctor speaker. So for example, this video right here, you can see that Dr. there was Dr. speaker, there was a patient experience and the discern score was 41, blah, blah, blah. And then you can see the average CLV is comments API, which is a video power index and duration for that video. Alright, so I want to ask the question. What was the discern score higher in videos where there was a doctor speaking, then in videos where there was no doctor speaking, right? So we have two groups. One group where there was a doctor speaking, and another group where there was no doctor speaking. So a 0 here or a one here, right. And so I want to see in the videos where there was a doctor speaking, did those videos have a hire, the cern score or maybe a lower discern score, adeno, or maybe in videos where there was a doctor speaker, Did they have a significantly higher or lower average daily views, right? Maybe people like watching videos with doctors, right? Because I don't know they're trustworthy. So maybe they have a higher average daily views. And so to make this statistical analysis, to actually see if this is statistically significant. If there's a statistically significant difference within the groups, we can use the Mann-Whitney-U test or the t-test. Alright, so Let's jump into that. But I am gonna make things a little bit complicated before we do the Mann-Whitney U test and the t-test, we first need to make sure that the data that we're analyzing is in a normal distribution. So what does that mean? Well, in our case that means, let's say we're going to analyze that the association between or the difference between videos where there was a doctor speaking. So here and discern score, right? So we want to know that hair, the discern scores, we wanna know if this column is in a normal distribution, because it needs to be a normal distribution for us to use the Mann-Whitney-U test or the t-test, right? So for us to make the analysis, it needs to be a normal distribution. Alright, so how do we do that? Well, we go to statistics, right? We have the cern Here, we go to Statistics. We go to Distribution Fitting. I'm gonna start a new one because I was working on before. You go to continuous distributions and select Normal. And then click OK. Then you're going to have this window. You're gonna click on variable. And in this case we want to see discern wasn't in a normal distribution. So I'm going to go on my drop down here and click the cern. Alright, is easy. The variable is the Cerner. You can see it here. The distribution is normal, okay, and hit summary. And now we see this complicated, scary-looking window. What is important for you is this number right here. All right, so right here, p equals 0.55206. Okay? So what does that number mean to you? Is that it's an, a normal distribution or not. Well, if the p-value is above 0.05, then it is in a normal distribution. So if it's above 0.05, it is in a normal distribution. So in this case it's 0.5. so yes, it is above 0.05. So this is a normal distribution, which means that we can use the student T-test or the Mann-Whitney-U test. Great. If this was below 0.05, this would not be a normal distribution and we wouldn't be able to use the Mann-Whitney-U test or the t-test. Okay? Alright, so, so we are back here to our database. We know that the discern here has a normal distribution. Whoops. So we want to make the comparison between was the speaker, dr or the cern. And now we can use the student T-test or the Mann-Whitney-U test. But before we, you might be asking, well, which one do we use? Do you use a T-test or the Mann-Whitney-U test? Well, it depends on how many values we have. So in this case, how many values means, how many videos that we actually analyzed, how many data points do we actually have? So for the cern, let's scroll down over here. So in our case, we only have 79 videos. You can see analyze 79 videos in our database. That's it. So because of that, we cannot use the student T-test. Because why? The student t-test can only be used when you have more than a 100 values. And the Mann-Whitney-U test should be used when you have less than a 100 values. So that's the basic cutoff. So if you have, in this case 79 values, you should use the Mann-Whitney-U test. So let's say if you have, I don't know, 500 values, right? Then you can use the student T-test. Alright? So in this case, because we have less than a 100, which is 79, right? We should use a man with new test. Alright, so how do we actually do that in statistics as well? You go over to statistics, right? You go over to non-parametrics, you click that. I'm going to start a new one. Ok, cool. And you see this window right here, and you're going to click comparing two independent samples, groups. Ok. Click OK. Alright. And now you, oops, where did it go? Okay, continue current. Alright, so we're going to go to variables because we need to click identify are dependent and grouping variable. Alright, so we click variables. And in this case, we're going to look at discern and we're going to look at the actual what was it in this case was the speaker, dr. Now, we can, let's pretend that we have found the normality for everything else. So we can actually, I'm going to hold Shift and I'm going to click here so that it highlights everything. So we can actually all at once do the statistics for the cern, the average yearly views comments like ratio of EPI and iteration. And we can compare that against the doctor. So what does that mean? We we are saying is there a difference in the discern score or the average daily VSCO or the comments are, you know, like Ratio or whatever. If the speaker was a doctor, you know, maybe more people like the video. If the speaker was a doctor, maybe they're more comments if the speaker was a doctor. So we are asking if there was a difference between the groups. Okay. So make sure you have the discern score and all this good stuff on your left because that's the dependent variable. And was the speaker Doctor on the right because that's the Independent or grouping variable. So it's important that you have this on the left and on the right. Okay? So once you do, click OK. And you can see, okay, that's the dependent discern two duration or it grouping ten. Alright, cool. And we had the Mann Whitney test. Alright, so we see a bunch of information here. What's important for us is the p-value. Ok? So you look here and we see the p-value and a, right? So for the cern, and in our case a cutoff will be 0.05. So yes, there was a significant difference between the discern score and people that had a where the doctor was a speaker and where the doctor wasn't a speaker. And the average LIV Is there was also a significant difference in the comments. There was also a significant difference. And it was a significant difference, right? Because the value, the p value is less than 0.05 over here. So those are actually highlighted in red for us, right? So statistical made it easy because, well, OK, they're highlighted in red so we know that ok, they, there's significant. But the light ratio, for example, this is 0.11, right? Two blah, blah, blah. So this is greater than 0.05, so this is not significant. And then the VP Vi is less than its right again, so it's less than 0.05. Okay, cool. So actually having a doctor speaker, in these cases, it was, there was a significant difference between the two groups. Wow, that's really cool. That's a significant finding, and I would love to put that in my paper. Alright, so now we need to see if this, now we know that there's a difference between the groups. When there's a doctor speaker and when there isn't a doctor speaker. But now we actually need to see that what the actual difference was, for example, was the discern score. I'm assuming that the discern score was higher and videos with a doctor, right? Or the average delay views was higher. Videos of the doctor because maybe people like watching a doctor talks about health instead of some random person, right? Or maybe the, you know, that there was a significant difference, but maybe was there a higher number of comments and videos with a doctor or not? So to find out, we can do the student T-test. I mean, we're gonna do the student T-test not to get the p-value because we have the p-values, we wanna do the student T-test just to get the mean, mean scores, right? Because in the Mann-Whitney-U test, these numbers, the u, z, all these numbers, they don't really make sense. They're not very friendly numbers for us to actually analyze the data that way. So now you can write this down, you know, whatever your word processor is, write down all the significant values, all the significant relationships. All right, so let's continue. All right, so we are here again and we're going to do the t-test. Now, of course we're not gonna do the t-test to actually get the p-values, but we're gonna do it just to get some numbers because statistical reports, the actual mean values per group. So yeah. Just just for the sake of not having to manually calculate the means by myself, but having a statistic, I do it for me. Okay, so we go to statistics and we're going to do the t-test. So we go to basic statistics. Let's start a new one, okay, and then we're going to go to t-test by Groups. Click OK. And now we're gonna do the same thing. We're going to click. We're going to identify the dependent and independent or grouping variables. So we go to variables. And in this case, we can actually go from, I'm going to do the same thing. I'm going to hold shift and click so that it highlights all these. And then on the right was the speaker Doctor. So these are the dependent variables on the left and the independent variables on the right. And I'm going to click, okay. And everything looks good. Okay, so I'm gonna head summary. And now we see the mean values. We don't care about p. The reason, the only reason why I did this was to get the mean values right over here. Alright, so, and so just, just so you know, what's going on. Alright, so over here, we can see that for the cern, right? The one, so it says Mean one and mean 0. So mean one is right. One means if you actually have a doctor and 0 in our case means if you don't have a doctor. So when he did when he did have a doctor, the discern score was about 39. And when you don't have a doctor, that discern score was 33. So we can see that, wow, there was a 6 difference between the two groups. You know, 6 difference. That's a really big difference. So we can say in our manuscript, there was a statistically significant difference between videos that had a doctor speaking and videos that did not have a doctor speaking. And then we can give the p-value like P-value. I think it was less than 0.05 something. I don't give that value. And then we can say 39 versus 33 points. And we can put that in parenthesis, 39 versus 33 points so that people know that, oh, it was 39. The average the mean value is 39, discern versus 33 when there was no doctor speaking. Okay. So for example, for the comments. Actually when you had a doctor, you had much less common. So only 151 as compared to 487. Which maybe means that doctors are kind of boring and people don't like watching them and don't like commenting on their videos compared to people that are not doctors, right? Because maybe if you're not a doctor, you're better at creating more entertaining videos that people comment on. Ok, so you can start to understand now through first, the first we did the Mann-Whitney-U test to get the p-values so that we can see that if there was an actual difference, statistical difference. And now we can get the means using this t-test, but we're not actually using a t-test. We're just using it to get the mean values. We're using it so we can understand what the difference was. Alright, so this was quite a technical video, but I hope you get an understanding of what we were talking about. We talked about normality. Normality, we just need to do and make sure the data is in a normal distribution so we can do our t-tests and Mann-Whitney-U test. Okay? And then you do your t-test if you have more than a 100 values. In this case, we didn't use the Mann-Whitney-U, Mann-Whitney-U test. So then we got the p-values. We saw which which differences were significant. All right, and then we did the t-test just to get the mean values right here to see what the actual difference was. Do doctors have a higher discern score than non-doctors? And in this case that was true, of course, and it makes sense because doctors usually give more medical information, you know, they're very informed, they know about these sort of things, right? Okay. So I'll see you on the next video. 47. Fisher's exact test and chi square test: All right, so in this lesson you're going to be testing your data by a categorical variable. So you can use the chi-squared test or the Fisher Exact test. So when would you use which? So it depends really on your sample size. If you have a sample size greater than 1000, use the chi-squared test. But if you have a sample size less than 1000, I recommend that you use the Fisher Exact test. So in this case, Let's look at the number of our sample size, okay? Our sample size is 79, okay? And I'm just using the SIGCHI database as a sort of example. So we have 79 videos that we analyzed. So in this case, outward, I would want to use the Fisher Exact test. But anyways, let me give you a general overview of what these tests really are. What does it mean by testing your data by a categorical variable? Basically, you're looking at the association between categorical variables and seeing if they're independent or related. So for example, is it related that I don't know in this example, if there were diagrams and the anatomy was explained because maybe, you know, people show people explain the anatomy by diagrams, right? So maybe there is some kind of association between these categorical variables. And to see this association, see if they're related, right? See if people actually use diagrams to explain anatomy, to see if they're related in these, in the data that we have, we can use these tests. So the Fisher Exact Test and the chi-square test. Alright, so enough about that, let's get to actually doing the test in statistical. So here we are. We go to statistics, go to basic statistics, go to tables and banners. Click OK, then go to this tab stub and banner, and then specify the table. So click this. And so alright, so let's say there were exam, there were diagrams and was the anatomy explained. We click OK. Alright. Go back to cross tabulation. Actually, no, don't do that. Just click OK. Alright, and now, now go to options. And in Options, click this, click, this, click this. This is going to give you the percentages, percentage of total count, percentages of row counts, percentages of column counts. You can hit this if you wanted this all just highlight counts above ten in this example. Alright, so I clicked it and then hit this, the Pearson ML Chai squared. So this is a chi squared test and the Fisher test. It doesn't hurt to do both tests, but we have the fisher one here. This is the one we're going to be easing. Alright? So that's basically it. Go back to Advanced and hit detailed two-way tables. And there we go. Here we get our results. So we have the Pierson chi squared, the ML type squared, and the h i square there, there a little bit different. And you can read about them. And then we have our Fisher exact one-tailed and two-tailed p-values here. Alright? So in this case the value is less than 0.05, which means that there is some kind of correlation between them, right? So they are dependent variables, which is cool. So in this case, diagrams and anatomy are not independent variables. They are related. 48. How to switch windows in Statistica: All right, so just a quick tip. One thing that may be annoying after you do whatever statistical calculation, let's say you just did this calculation and you want to go back to your database to see it and do some more. How do you do that? You know, it's kinda difficult. Like where do you go? All you do is you go to home. You go to, you can go to cascade, and then you can see all your different windows. So in this case there's a database and I can just go to that and boom, or I can just hit one at like title vertically and see them both or horizontally. Or for example, if it's like this, I can just switch windows and I have a bunch of windows, lets say, okay, I can go back here. So over here, if you ever stuck somewhere and don't know where to go, just go to home. And this Windows section. 49. What is Google Trends?: Okay, so what is Google Trends? This is the homepage for trends dot google.com. And here you see some examples of some fun searches. Taylor Swift versus Kim Kardashian, you know, World Cup where people are searching for it, football, American football, alright? So basically you can explore whatever the world is searching wherever in some period of time between 2004 and now. So for us we're, we're more focused on health problems. So let's, I don't know, choose some kind of health condition. So maybe depression, I don't know. And here we get the search term, the mood depression, mental health, major depressive disorder, and the Great Depression. And another's. So we're looking for, let's say depression, the mood. Alright. So I'm gonna click that. And let's search. Fun, fun arrived. So as we can see, we have a couple of filters here. First of all, we can see where we want to do our search. So in the United States are worldwide or wherever, the timeframe, so past hour, it can even lead to pass day and you can do a custom time range. Maybe I want to do it from, I don't know. Let's say 20162 now. Okay. And then I can see whatever's happening. Ok, then there are the categories. Now, because this shows you the depression mood like this is a topic search. This is cool. It already narrows down your results. But let's say we want to look at depression, mood in the terms of Health. So let's turn search Health, okay, Health. And now last but not least, we can analyze the web searches or also the image searches and new searches, Google Shopping and YouTube searches. So cool. Alright, I actually let's look at YouTube searches. That's fun. Alright, so now we have the data for Google searches on health from the last five years in the United States. Okay, so you can see some cool patterns. What you'll notice here is that the scale is from 0 to 100 and it's always going to be from 0 to 100 because Google Trends is never actually going to give you the exact number of people that searched for that thing. I think they just want to keep that information for themselves because they are kind of an information company. So they're only going to give you relative values. But anyways, these are still valuable for you as a researcher. And what I also want to point out is if you search, let's say search for depression. But you do the search term, you search for the actual search term. It's a much different type of search because depression, mood, and depression, the search term, there are different, there are two different things. Depression search term is if a person actually searched the exact term, depression and depression mood is Google Trends has made a category for it. So it smart category. People can search for things other than depression. And Google will index it as depression if it thinks it's, you know, if you're actually trying to look at depression. So maybe if you misspell a word, it'll say, oh, you know, you misspelled the word, but obviously you still meant depression. So for example, if I misspell depression maybe with one S, you might see that the results will change, right? So now there are very, very few results here compared to depression. So I recommend whenever you can use the topic searches where it says, OK, depression, mood, right? And last but not least, you can download it, download the FVC, and look at the data on Excel. And then you can see, in this case, we're looking at America. So the United States, we can see where exactly these searches came from. So in this case, the most came from Wyoming, Montana, Wisconsin. And then I can look at other sub-regions are right. Then we can look at the interests by subregion. Alright, cool, related queries. So these are the rising OR breakout vines. They look at vines, occured cure depression, crippling depression. I have crippling depression. So these are some cool related queries that you can also use. Then we can also use the top. So that's the rising category and this is a top. So depression was the number one related query, Vines was number two. And Nino depression cure. So you can kind of see some cool analytics and interest by subregion. This is for depression, right? The actual right here, the mood. And this is for depression would spelled wrongly. So you can see, okay, who spells? Who's bells depression the wrong way. It's mostly California and Texas and Florida or Florida is the most. Yeah. So alright. And Fun related queries. K S, depression, I think that's Spanish. Alright, so let's look at the top searches for this law, the pleasure on, alright, so cool. They were searching in Spanish. That's probably why they only have one as their. Alright, so this is just an overview video trying to give you the idea of what Google Trends is. And this is a really fun tool. And soon in the next lesson, we'll, I'll show you how you can use Google Trends to write papers, scientific papers, and publish them in journals. So I'll see you soon. 50. Examples of google trends studies: All right, welcome to the world of Google trends. And in this lesson I'm going to give you four examples of Google trends studies. So you can kind of get an idea of what you could do with your own study and right. Ok, so the first example, this is a really big paper that was published detecting influenza epidemics using search query data. This was one of the first beg, Google Trends papers that really changed and brought attention to Google trends and how it could be used as a tool in medicine, right? Okay, so detecting influenza epidemics using search engine query data. And I just wanted to show you here how popular this paper really is. So right here, this paper has more than 2 thousand citations. It was published in 2009. And it is more than 2 thousand citations, which is a lot is published in Nature, which is one of the biggest generals in the world. And you can also see like an alt metrics. So alt metrics or you know, social media and those places it has been mentioned more than 500 times. So this is quite a big article. So let's, let's read just a little bit about it. So you kinda get an idea of what it was. So the big thing about this paper was, here's, here's a part of the abstract. It analyzed large numbers of Google search queries to track influenza like illnesses and a population. And they could accurately estimate the current level of weekly influenza activity in each region of the United States with reporting lag of about one day. So they, they concluded that this approach may make it possible to use search queries to detect influenza epidemics, right? So you can actually detect influenza epidemics and areas with a large population of web searches with, with Google search queries. So this was kind of a ground-breaking paper. And since then it has really spawned a lot of research into Google trends and how it can be used. And now we know a lot more about it. So let's go on to some more examples that I think you could do because this paper was great. But this, this information isn't really available and the Influenza tracking with Google search queries has its limitations. We found that out. So now I'm going to give you some examples, more modern-day examples that you could do. And here we go. So these are ones that you can actually learn from. Alright, covered 19 symptom Google search searches proceed local incidence surges, evidence from Spain. Okay, so basically it's saying the covenant symptoms, people search on Google for symptoms of covert 19. It is people search about it before we actually get a big incidence of those surges of covert 19. Alright, so the methods, what did, what did they actually do? Our method consists of the linear correlation between the Google Trends search data and the data provided by the National Center of epidemiology in Spain. So they took some epic epidemiological statistics from their local center. Dependent on the Institute, blah, blah, blah. And cases of covert 19 reported with a certain time-like enabling the id