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Hello, good evening everyone. Myself, Doctor Raja Singh Doc, I'm of the co founders and co chairperson of the Georgian International Medical Student Society. And we are happy to invite you all and welcome you all for the monthly medical journal meeting. Today is the first general meeting that we will be discussing about what we are going to be doing in the monthly medical journal meetings. How we're gonna proceed? We have Doctor Neil with us here. He's one of the co founders of peer research group. He's also a graphic uh illustrated and motion design minor and he's going to be discussing about what are the different types of research. And also he's also going to discuss about the importance of biostatistics. After Doctor Neil. We will have our amazing research director Maha Qassim. She will be discussing about how to write a research paper, how to write a scientific paper. What are the basic steps in world? How do you begin as a beginner? And what are the key steps involved to write a good paper? Okay, so now I will be inviting Doctor Kneel on this stage. Welcome, Doctor Neil. Hello. Uh I'm glad to be over here today, we're gonna be talking about research all in all. It's a fancy word. People make it sound arcane. It's not that hard if you find it, Zuma and find very, you're comfortable. So, yeah, I think because it's a good job the way it was presented by the co founders and the chairman, I believe, I know what you call that position of Jim socket is really good. So I'm gonna be just briefly going over this. I'm Neil. I'm one of the co founders of peer research and I'm glad to be uh invited to speak over this topic over you're on this platform. So starting our presentation, I'll just go over this briefly. Um I just talked a little bit about what we do. Uh Could you at least let me my screens visible. I just wanna have a confirmation for that. A screen was visible. Yeah. All right. That's good. Thank you. So I'm gonna go founders of the research, as I just mentioned and we have a mission, what we do, it's me. Uh and two other co founders. Yeah, Shandra Nadja. So we started back uh last year in the initial part of the year where we saw people who wanted to work in this field and they wanted to have some added dimension for their learning. This could be probably for their CVS or even if they're just genuine interest in that, it was great. We had a good response. So we worked around this and we noticed that a lot of people who are applying for certain foreign medical examinations wanted to have some degree of research on their CV and some are genuine interested as as mentioned. So this is the need of the are we need to identify data especially from peripheral regions and regions which day where data is just lying in paper in many developing countries? This is a reality. So having that data computerized and analyzes a thing which is not very commonly done. Of course, there are census reports, but this is stating data, not all the data is analysed, especially biochemical values and test results. Some of these results can actually under undermine real issues which go on in places. We've had a lot of such. Um uh I can say papers management we have worked on very uncovered some severe issues and peripheral regions which goes all the way to contraception or reasons why certain diseases like diabetes. And we lent we actually identified D K being common in the region. We found out the common denominator for that is because they were having lesser incident than required in that PHC. So these things can be uncovered only even peripheral situation, the peripheral regions, data is analyzed and that's what we are doing over here. Everybody who want to help in some way and anyone who wants to improve their C V wants to work in this field, whatever the basis maybe finding these people at any position, wherever they are and doing their bit. It's helping us to analyze the data and add more information out there. And that's something which is helping everybody literally speaking. That's what we do. And we have had a good response and be really grateful and Jim Sock has invited me to speak over research and give a few tips. I'll see if I can do a good job today. Let's see. All right. So I'm not gonna be boring you with the details. I'm pretty sure didactic will be covering that. I'm not saying that's boring, but I'm not going to go over that. And this is the basic types of research and we're going to lab researches clinical research, what's in that. But I'll be giving you a brief overview. Of course, this is not an exhaustive list, but it's good enough as far as what you can have a basic idea what's being done. Now, lab research, basic science research. This is what you can also refer to as transitional and something which goes on in the lab. This research is the basis of everything which happens as far as let's see. Medications go. So something which goes on in the lab and after this translated to the clinics goes in the lab, re so this could, this is not necessarily limited to drugs, it could also be some physiological responses. And on the other side, the outcome of drugs, how drugs act on patient's whether that's um let's say, is it giving a good response? This could be any of the phases. You must be learning 0123, which composite interventional clinical trials or it could be something like um let's say there's an adverse effect of a drug and you're trying to identify whether this adverse effect was actually related to the drug or not. All these things come under clinical or epidemiological research. We have two prongs to this thing. It's observation and interventional, interventional. You intervene, you do something in observation, you simply observe, there is nothing which you would do to alter the normal course of Axion. You solely observe. You'll identify your analyze. I'm coming back to intervention in interventional. You have got clinical trials. This could be of any kind. This could be quasi experimental. This could be randomized are ct's which you're here. Normally very commonly are CTS for this drug. That drug, it could be non randomized clinical trials. It doesn't matter. But your intervening, you're doing something there. This could be giving a drug, this could be taking it probably if you're looking at um you know, let's leave the drugs. I don't make it too complicated right now. Drugs, it's the court thing which falls in clinical trials. Let's not go beyond that observation studies. This could be how you look at it, code studies, case controlled studies, cross section series, ecological studies and even case reports. You obviously this list is not exhaustive. We have got case series over your, I have not even mentioned reviews which also would be coming in some form in this domain itself. And this is not even the only classification which exists. This is one of the classifications. You could look at this in many different ways in this one of course. And even within this thing, you can even go deeper and you can make it more comprehensive. But as far as we're concerned at the court level, at the basic level, when you're starting out, this is something that you should have clear in your mind. Cohort studies prospective. Generally it cause to be retrospective prospective, this is gonna be covered in didactic. So I'm just giving you a broad overview, you create two groups, you see the outcomes and you see what it leads to at the end. I mean explosion, you see what the outcome is at the end in case control, you have got the outcome and you go back in time and you see it cross section. It's today you're carrying a cross section. Ecological series is a slightly domain which will not be catering to this, these with the population and ecology. I will not be going on with that right now. This is more so relevant for public health and in case because you know, you see a good case, you see a case which is relevant, something novel, something new, probably treatment which is try differently, which turned out to be good or some rare presentation and or timing in a presentation, anything will fall in your case report. This could be frankly anything, even the most simplest of things, let's say, for example, I've been going over the diabetes a lot. So let me just go an example of that. So let's say you see a patient who has DK was decompensated that comes to you after 48 hours. Now, it's unlikely this patient would survive for that person had a decompensate situation. But if the person did survive, this would merit a case report. So it's not only the uniqueness of the case is also any aspect which can lead to some significant development and that's what we are going to be catering to under any form of research which you want to develop it. This is the pyramid which is frankly seen everywhere and a lot of people will be seeing this thing as a part of the part of their props. And you'll be seeing okay like this, the pyramid will be asked to draw this pyramid probably as a part of your didactic in your exams are not sure how it runs in different places, but this is a pyramid, which is something I want to emphasize the point. But the order of this is not suggesting that the parts of the bottom are replaceable. You'll see, I've actually made the lower part slightly thicker than the upper parts, it doesn't mean that the lower parts are lower. So that's not relevant. It's relevant. Frankly, without the lower parts, you could never reach to the upper parts. But if you're going to be seeing in terms of what the value of the result is a systematic review and meta analysis will give you a stronger result. Why? Because the pool of patient's is larger. Let me give you an example. Um You're going to generalize a figure. Let's say you try to generalize BP, you take three people in one study and your right away. If okay, this is the average. Now, let's say that 1000 researchers who took random people like this and identified an average and you're actually taking a group of 1000 into previous 3000 people and making a generalized figure, which figure do you think will have more relevance, which would fit better in the whole population in the situation in that scenario, which is more generalized. Obviously, the one which is a larger sample, it's intuitive. And that's why we say as we go higher, the results have more value, it's stronger, it has more relevant, but it doesn't undermine the thing at the lowest level. And that's something which often I've, it took me quite a while to get this logic. I was always under the impression these studies are more important. Those are not after I got out in the first time I worked on a paper, I realized that, you know what? It's not true. It took me some time when I was in my props even I was having the misconception that the upper studies, this is what you should be doing. Everything else is, you know, pretty much nonsense. So it's understanding that everything and every level has its own position and something you cannot replace under pay research. I'm just going to go over that a bit at our level without involving a lot of authority. And a lot of let's say money, you can perform studies which is simply based on data analysis. If you just have the tools to identify that, which involves biostatistics and which studies could you do when it's cross section of studies, you could code studies, your case controlled studies. Now, co studies, I would say it's a bit limited because the groups which are there might need some money and some incentive but not as we just discussed in the previous like these are observational. You do nothing. You just need manpower to observe and to note to take data. If you're to intervene, you're giving something, you're observing a behavior. This will be falling under some kind of intervention and this would involve more manpower. Sorry, I apologize, more manpower, more money. So this is something that you could do at your level. Even if you do not know anything, I would ask you to zoom out what do you know, you know, you know how to talk in the language, right? You know English, probably, you know your local language. Even this could be something useful. You can talk to patient and identify some information. You could form the basis of what people can work on. And slowly you can build your position and you can learn that, you know what I can actually contribute from this small thing to the large thing. And this will be a growing tree for you and you actually learn to enjoy the whole process. Instead of feeling that this is an arcane topic. In reality, it's not all that arcane, it's not abstruse. It's really easy. Once you understand what you're doing, the status expired, you know what we have computers. Now, you don't go into the depths of what do we do want to calculate, make a calculation mistake. What started you, you should understand why you do that. That's more important. And that's something which I say we should be focusing. Now, we have tools which can help us identify, let's take advantage of the stools and don't go into depth of understand why and how. Besides this is a topic which is entirely by, by statisticians. So you can probably even refer and ask them to help your understand topics when you will be working on your own study in the future. Probably for any of these studies, you will require a research proposal, any study at all which you want to do, which involves data. Now, this could be data from patient's. This could be data from even their family members or even doctors. You have any kind of data, you need ethical approval via any data. You never know whether the data can be used wrongly used correctly. What's your aspect? What's your, what's your gain? So they want to check via cleaning the data and whether the data being collected is relevant. Is it useful? Will you add something? So this is to be done? And you have to be presenting that to a review board. This is called the our our be it may vary a different places. They call it our be at my, in my, in my country, it may be called something different at your place. But at the end, it's a review board, it's a research review board, they'll be reviewing whatever proposal you have and this proposal is going to be dealt with extreme scrutiny. Now, it will be like if I'm just performing an observation, start even I'm observing, probably let's say potassium levels in a person. What's the big deal of this? And frankly, it's not, but a lot of studies, let's say, for instance, you're performing uh an interventional study in this situation. There are funds involved, maybe receiving grant from the government, you will be receiving grants from pharmaceutical companies in these situations. You need to, they need to know that what you're doing is actually valid. It's something which is substantial and you're adding real uh substance to the literature out there, you're adding something new, which is helpful. So once that goes through the R R B, which is the research review board and they identify that what you're doing is relevant. It's going to be presented. You're representing rather to the I C which is the Institutional Ethics Committee. If they accepted it, then you're gonna go, you'll be given a sheet where you're like, okay, you know what? You're given the permission to use this data or whatever the data, maybe this could be, as I said, put us in values simple as that or this could be information which you obtain online. I like to clarify this point that if you're obtaining data online, this could be any even a Google form. You need to take an institution ethical approval. It does not O V eight that this is not needed. If you're taking data online, I want this thing to be clear because this is a point often which is misconstrued by people that if you're taking data online, you don't actually going through the institute. Why do we need to do that? No, you need to do that. You're taking any kind of data. This even need not be patient data, any health data, you need to go through this process. It's pivotal. It's important generally nobody lands into trouble because of this. But if you want to be by the book, this is something that you should care to do. Once you have all this done, you have obtained your data, you've gotten your recent proposal sorted and you're like, you know what? I have all the things I want, I want to look at this topic. I'm giving you an example. Now I have done a paper of this in previously. So I'm going to give you an example. We were, we were working on a paper and mucus my courses and COVID back in I think it was last year benefits a big deal. And we found that how can you identify vegetations are going to be having a more severe presentation where there's gonna be invading more or probably it would be retro vital going. It could be the cerebral region. But how do you identify that? And the I don't got a lot of data and this could be like eight versus that this could be gender versus that this could be ferritin levels versus that this could be D dimer levels anything. So you realize that a lot of these values are coming up and you're like, what's the common denominator between them? How do I do something about this? You can see age, okay, ages what age can be? Numbers, it's numeric. So this year like, okay, no, it's order numeric. There's a discreet value, it's not continuous, it's discreet, but it's in order. So, but you know what? This is a quantitative variable. On the other hand, you'll be looking at something like um gender, gender is qualitative. They're only two. It's this or that like it's qualitative. Is there any order in this? No, there is no other in this day. So there's gonna be qualitative, this is gonna be nominal. So there are different kinds of data and there's a different view approaches all this data. Obviously, I'm not incorporated the entire thing in this and I don't make it seem very like, oh, you know what? I don't know anything about this. Calm down. Take a step back. Look at it. You see the age, you know what, what is age two things like that? See types of data. First, you got to do types of data. It's quantitative quality. If you've heard this thing since long, nothing fancy. I'm just going to give you one more small tiny inside into this. You can divide quality to data to do parts. I don't think I have a slide of that. I'll just say this thing. I hope it's not very, it's not very complicated. You can divide quality to data to do parts. This could be nominal or, or, or journal, it's nominal. There's no order. It's like mom, dad, you know what doesn't matter? Dad comes for his mom's come. Second, doesn't matter. But on the other hand, if you have ordinary, this is going to be like a B C D, you see there's a pattern to this 1st, 2nd, 3rd, 4th 5th. This is a pattern. I'm not saying 1234, I think, 1st, 2nd, 3rd, 4th, retraining that point. So there's an order to this but it's qualitative. So this is coming under ordinary mom, dad, brother, sister, these relatives, these are different facets. You could also have different reasons like it's in your, in Georgia, you're dividing in four different parts. North, south east, west. This is also gonna be qualitative because it's, it's qualitative and it's nominal. There's no order. You can say East, west, north, south because north, south, east west doesn't matter, it doesn't change the situation, right? So these kind of things, once you get a grasp eater, you know what I can actually interpret what I'm doing. It's this simple. Frankly, if you don't get something, identify what's the common factor, what's different, it's more like pattern recognition when you're small. You know, you know, we're trying to feed those legos feeling or you know what this fits their, its pattern recognition. This is something very much like that. Once you get the hang of this, you can review more information and you can identify what can I do. I'll give you an example right now you'll see over here we're talking, you're talking about four different charts, I'm showing you that this is a chart on one axis, this shot on another axis and you're like, you know what this is twerking. I can't in British. Do you know what probably you're not wrong. It is. There's a lot of information you, you'll see partial positive correlation. You see perfect positive correlation like, oh this is too daunting. Yeah, I probably could be not taking it away from you. But you know what, what you can actually infer I ask you, what kind of data do you think could be on the X axis? Do you think mom dad could fit on the excesses with the line? Think about it. It's not possible you draw a continuous line. You cannot have discrete variables which have no order. It's 02 X. It's an increasing value. It has to be something continuous only in that situation can fit in the X axis. Same thing on the Vioxx is if it is qualitative, how can you fit something on the X? It's always the age, age is 1234. It's also 1.11 point 21.3, you see it's continuous. So this is the kind of thing you can identify simply by seeing by instead of thinking, you know what I don't get this, just try to give an open man. You'll see something that you could not see and it'll make your life much more simpler. So what I'm trying to convey over your is that bio statistics and research all in all, it's a bit obstructs if you look at it from far. But if you go close and you try to identify it, you'd be like, you know what? It's not that hard. And sometimes I've heard people tell this, why do I need to even know that? And you know what? You're not wrong. You don't need to know a lot of it. But let's say you went to the market tomorrow. I'm going to give a few examples. You know what? Um Okay, this is a classic example, which I've heard my, one of my mentors, you should let me this example. Previously, you go for purchasing a hair loss. That's all your hair growth cream. And they say, you know what the results of this hair growth cream are significant. You're like, you know what? It's good, it means it's significant but little. Do you know that it's written over there? The effect sizes is something X Y Z and you make it's significant. How significant is it? It's significant that if you use this product for 100 years, you'll see a difference in the growth of your hair by 0.1 millimeter or one millimeter. You know, you know what that's irrelevant, but that's not, that's not what they were right on the product. They write that this is scientifically program to be significantly beneficial to human hair growth. You know what? It's certainly let me take it. But there's certain things that go between the lines and this is a real life relevance of these little things. I'll give you another example. Um A lot of people go and work out and they'll be like, you know what we're having, they, and you're having different kinds of protein X Y Z. We got Casey and we've got V and we've got P protein and there's a lot of proteins out. Then you're like, what's the best protein out there? You know what? Let me open the books, let me see the studies and let me see which one I could use and which is gonna be having the most relevant like they'll be associating this. Like you'll have dismissed gram itch of this protein and you have probably two Sinemet growth and biceps over here. You were having three centimeters only that was used. And this is a quantitative way of identifying which is the best. This is something which is relevant to your daily life. And you're like, I don't want to know that frankly speaking, you want to ignore that. In that case, this is really relevant data and this is something which anybody should be able to understand. You're in this field. This dictate, this is dictated to you that you should probably at least get a bit try to identify the real life benefits for you beyond research. And you actually find a group, your groove for learning a bit more and further in that another example, this is an example which obviously taken both these examples from a book Mohajirs Methods and Biostatistics. You could actually review that book if you want to. It's an amazing book from scratch. If you do not know anything I really appreciate. This is a book which I was recommended by my mentors and I started off with this book. I read a few books. I had also offer that, but this is one of the best books, in my opinion, for a person who's starting off in this front. Anyway, please tell me if I'm, if I go a bit over time, I'm not keeping a track of time right now. All right. That's all right. Take your time. All right, thank you dot All right. So if you could just, just a random chart over your four different groups of people, you like, what's the difference between these four groups? Imagine? I'll give you a real situation of this. You're working and you're at a job somewhere. You see, you know what I'm, I'm in this position and somebody excess in that position and your salary ranges are significantly different. How can you say that your salary range and the person who's in a position higher than you? Is it actually significant? But how significant is it, what's the difference? Is it really that much of a big deal even if it is significant? So these things are real life examples of where you could use this thing. And if you notice, you know, I just government calculate that thing because, you know, when I have the data with me, but you should be empowered enough to know this should be like it's not something obstructing me. You know what? I can't do anything about it. Why this was actually a part of your curriculum. If you just saw a little bit you have been doing and dealing with this information when it was fresh with you and that's something I want you to understand. Don't look at this thing and make it feel in your head that it's something you don't want to work on. This is really good information. It's something which you can use. And if you know the basis of it, you can diversify your knowledge in different other fronts and you'll actually enjoy this much, much more than you think it is. All right, I'm not going to be going a lot with the other stuff. We have a session underpay research coming up. I'm just saying this, this could be helpful to you guys and we're covering a reference management software and certain other peripherals in that this is involving how do not insert references at all and sinking it with other different sort of research are bed and how to export them and stuff like that. If you're interested, you could just scan the score. That's pretty much nothing fancy, nothing heavy. And if you're interested, you can just uh take a shorter down, just call it for 15 seconds or something or take a screen chart or if you don't take a photo on your screen as it's convenient to you. And after that, I'll be just giving you my contact details. If there's anything going to contact me for any information, which you, you know, I just need some kind of uh guidance on this. Of course, you've got your mentors at your place. If you're more comfortable with me, of course, you're free to contact me. And it's just basically how you, whom are you comfortable with? You go with them. That's how you get into this thing. All right, I'm going to the next slide. This is basically us. You can check out your website, check your information if you want to contact me, my E mails at the bottom over there. Uh be available anytime you, it's gonna be into you. Thank you so much, Neil. Thank you so much for all the insights that you've provided. I believe these will be very helpful for all these students who are here. Also guys, make sure you follow peer research on their socials and please free, feel free to contact Neil. He is very kind. He will make sure he will help you and all sorts possible. And also we have our research director, Maha Kazim, she'll be joining soon and she will be sharing the insides of how and the basics of how to write a research paper and what are steps you need to follow while uh analyzing and what all steps you need to do while doing a scientific paper. So I'll invite Marcus into the stage. Yes. Uh Good evening everyone. And thank you Dr Neil for this, for this amazing presentation. Uh I'm sure it was very helpful. It was for me and I wanna welcome you all for uh this multi medical journal and meet up again. And uh today as uh Doctor Logic, I said, I'm gonna be uh share ing with you how to structure uh study, like how to go through study, how can we uh structure it and how to write a scientific paper. And I'll hope this will be helpful for you too. Uh Can you see my ice cream? Yes, your screen is, is a boom. Okay. So um to start briefly, what is the scientific writing? Of course, scientific writing and articles are an important way for scientific to, for scientific people to communicate with each other, to communicate their scientific finding. Uh And in order to do so your scientific writing must be very clear and simple, simple and straight to the point. Uh in order to uh make this communication very effective. And uh as you may know, scientific writing is mostly written in English. What you will see in literature is mostly in English. So you must use proper English which will give the sense of the sense that you want in a few short words. So how can you conduct your study? How, what are the steps that you should be taking? Uh Well, first of all, of course, you need to have an idea what are you searching? What, what is the question that you want? What is your aim? Uh What is the outcome that you need to get from uh this uh study? Therefore, you need to identify a scientific research question that you want to answer. So uh this question should be very specific, clear and of course relevant to your field after it. Of course, this is, I guess the most important part in your study, which will be the literature review in the literature review. You have to search about what your peers have already uh found in the field related to your study. OK. So uh let me give you an example. For example, you're talking about vasospasm as a complication for aneurysmal rupture. When you go to the literature review, you need to find out what, what is the knowledge that we already know regarding this topic? Because you don't want to do the same, the same study with the same results over and over and over again. That's why you need to do the literature review so that everything is clear in front of you. So you need to go to conduct a thorough literature review to find out what research has already been done. And in order to do so you can use online database such as for example, pub med or Google Scholars or Research Gate. Because of course, you cannot get your information from Wikipedia, I mean, sure, Wikipedia get their information from different resources. But for your article for your publication, it's better to have your information from a trusted uh scientific websites such as these three that I've mentioned here, Parliament Google scholar and uh research kit after this. Now, you have a little bit of a clear idea what you want. Where do you want to go? You need to start designing your study. So you need to ask yourself, am I doing a systematic review? Am I doing a cross sectional study, a cohort study? Uh Am I gonna be talking about a new case for example? So I want to do a case report. So all of these things needs to be clear for you in order to stop, you need to also make sure where are you gonna collect your data from? Uh Are you gonna get samples or you're gonna get medical record or just online research? Where are the inclusion criteria and exclusion criteria for for your study data collection method? How are you gonna analyze your findings and all of these things? You must design these in order to uh continue with this after it now that everything is clear for you, you know, what is your study in or your your aim? You can start with the actual work. So you can start by collecting your data uh depending on your type of studies. So where are you going to collect this data from? And of course, the analyze of this data that, that you already have now that you have your data ready, you will start interpreting your results. What does this mean? Okay. What the result that I have? What does it mean? Does it match my aim or it doesn't? Uh So, and of course, you should present this data in a very clear and concise manner. You should use tables and graphs because it will make it easier for the leaders uh to understand what is going on instead of breeding long paragraphs. And of course, uh using the statistical analyze where appropriate. And finally, we reach the step where you have to document all of these steps, everything you have already done your, your aim, your results. What does this mean? All of these things? You have to document it uh by writing an article. So uh writing an article, uh an article usually is written following uh this simple format which is uh in rat formats. So you will start by an introduction in this introduction. You're gonna talk about your aim, you're gonna talk about general review of what the what did the literature said about this topic? Uh like a brief definition, uh brief. Uh you, you go through briefly about what you find in the literature. Why are you conducting this study? Maybe because no one else has talked about it, maybe you want to find out uh new results in a specific sample. So you will state your aim directly. Uh at the end of the, the introduction after it, you have the method part in the method part, you will show the leader. How did you come up with? Like you will show that either the design of this study, how this problem was studies? What were your inclusion criteria and exclusion criteria? How did you do the uh statistical analyzed? How did you get an ethical approval on this study? How did you get it? How did you do the uh the interviews, for example, with, with people if you need to do so? And uh the important thing to talk about is you need sometimes to define, to define the uh for example, tests that you're using uh if you're using any type of test. Uh For example, again, in the vicious pas um uh topic, for example, uh you want to assess the severity of vasospasm. So you are using something called Linda Garden issue. You need to tell the readers what is this because maybe they don't know what is the kindergarten ratio. So you need to give a brief definition of the uh all the tools that you have used in your study after it, we can move to the result part where you will state all of the results, everything you have found. When you are doing this study, you will state it and all of these results will be discussed in the discussion part. Of course, however, we don't need to discuss everything because sometimes some results are not that significant to be mentioned. So only focused on discussing the results that are significant to your, to your study that are uh that are matching your aim. Not necessarily this is what you want exactly. Uh but they match your. Uh so um of course, the uh the other essential part, the title which will describe the court contents of your paper. It will be the first thing that a reader will read to know what are you talking about? So title is very important. The abstract, the abstract. Personally, I love the abstract. It's the most important thing in an article to me. Why? Because let's say for example, you're writing a systematic review in a systematic review are just collecting data from everything that you have in the literature regarding this topic, all the relevant articles and you're gonna combine them in one article. So you cannot go and read all the suggestion that you have improvement. For example, regarding this topic, it's too much. So what you do is you will read the abstract in the abstract. It will be mentioned background about the topic, the aim the method, the results and a brief summary about it. Like what did we find? So the abstract is basically just a mini article. It's your many article. That's why it's very important to focus on the abstract. And of course, the introduction material method results and discussion that we talked about. And finally you summarize everything with the conclusion part, just a closure you um finalize this article. Of course, sometimes we need to do acknowledgement for the people who helped you because maybe you cannot, right everyone as author, you cannot state them up. Maybe sometimes you want to acknowledge the nurses who helped you collect your data. Maybe sometimes you want to acknowledge you, it appears who helped you in writing this article. So this goes in the acknowledgment uh part. And finally, the references, everything you write in an article must be uh you must write a reference for it, whether it's an article or a book or a website. All of these must be uh written. Now, of course, some tips to take into consideration is always use clear and concise language, always go straight to the point uh and be very concise with what you are saying. For example, you cannot try uh four line long sentence, it's not very practical. Uh So be clear beacon sized, you need to include all the necessary sections that we talked about and follow the journalist guideline. See the journals guideline might differ a little bit from one journal to another. Uh Because for example, some journalists uh want you that the abstract want the abstract to be, for example, 300 words, other journals might want the abstract to be sectioned. Others want it to be combined in one paragraph. So this will go during your design steps. So when you are designing your study, when you have a clear idea what you want, it will be clear to what journal you're gonna be sending your article. So you can follow their guidelines in writing. And of course, as we said, use tables and figures and proof, read your article, make sure your grammar is correct, your words are correct and everything. So um to give an example about what we have covered here, just a short example. Uh I'm gonna be going with you through uh this paper. So uh and the D O I will be shared now in the announcements in the chat uh if you want to go and check it out. So uh this will only be just a brief uh example on what we have said. Uh So as an application, uh so as we said, there's the title, there's the author section, the abstract, you will state briefly what you want, what you found the objectives, the method, the result and a small conclusion. And sometimes we stayed uh uh keywords, the keywords section here uh because it will, it will be important for people who want to search for this article. What should they talk? So you just type the most important 5 to 6 words uh in this article. So here, this article speaks about uh the relevance of suicide in uh in patient's in psychiatrist hospital and whether religion and spirituality actually affect uh suicide risk or no. So, in the introduction or the background, what you want to focus on is these important topics. So you need to talk about suicide. Uh What did the literature say about suicide? Uh the epidemiology of it, the causes? Uh all the recent, the recent findings. If you are doing your research in a specific area, you can also get uh brief. Uh you can talk briefly about what were the findings in this area? For example, you can find find here. We have talked about the relevance of suicide and and uh uh psychiatric disorders in the Arab countries because this was done in Lebanon. And so it was important to mention the surrounding Arabic countries. And finally, uh we have also stated, gave a definition about spirituality. What is spiritual spirituality that we are talking about here? And uh finally, we are mentioning here. Why did we do this study? What is the importance of this study? What will it add to the literature? So we have said that in live on this study hasn't been done before. So uh we haven't done any uh study among psychiatric in patient's and assessing the correlation between suicidal risk and spirituality and religiosity. And we have stated our aim. Okay, after it, we have moved to the uh moved to the method part as I told you, the ethical approval is necessary here. Why? Because we are working with patient's. So these patient's personal data are uh being worked on here. So we need an ethical approval. Uh You also need to mention that all of your patient's have been interviewed, but they have uh a written informed consent, which they have red and they have agreed upon. This is also very important because you're working with people here. So an ethical approval and a consent to participate. Uh the study design you have, we, we have talked about how we did the study. What is the type of this study? Uh which patient have we included? Which one we have excluded? How many patient's, what is the period of time? How did we do the interviews? Also, as I told you the questionnaires, what are the questionnaires that we have used here? Like a brief definition about this questionnaire, uh brief literature, sorry literature review about them. Uh For example, uh here we have used the ASQ the mini scale for psychiatric disorders and the major religiosity, stool and spirituality scape. So uh you have to breathe your readers about all the questionnaires that you have used because maybe they don't have, they're not uh they don't know what is, what are these skills? So it's important to mention these uh And finally, the statistical analyze, did you use any specific software to do these analyzes or what after it's your results? So as you can see what I mentioned is you will have tons of results sometimes like for example, we have all of these results, we cannot come in the discussion part and discuss all of these because this would be too much. That's why in the in the result part, right? All of your results, social demographic. What did you find blah, blah? But then in the discussion, you focus on the main part, discussion, you uh brief again the aim of this study and you focus on your most relevant or significant uh results. So, for example, here we said that um 45.9 were screened positive in A SQ so uh positive uh suicidal and we have found that higher level of spirituality were significantly associated with lower suicidal uh risk. So, these were the most important important uh uh result that we find and these are the results that we wanted to discuss because the other results weren't that significant or uh they won't affect much. Uh the outcome of this study in the discussion part, you will discuss these two important uh result that you find, are they the same as you find in the literature? Are they different if they are different? Why, why do you think it's different than what you find in the literature? What the first your study from other studies, this has to be mentioned. And one important part to be written at the end of the discussion is the limitations because sometimes maybe a few things have limited your study from getting a perfect outcome. For example, in this uh in this study, our limitations were that uh for example, the scales that we have the questionnaires that we have used weren't verified in Lebanon and they weren't verified in the Arabic language. Uh Maybe sometimes your limitations can be information bias or recall bias. Uh Maybe we have chosen patient from one specific hospital. So this is also selection bias because maybe if we did it in entire Lebon in all of Lebanon, in all of the Lebanese Hospital would have got different results. Maybe your sample size can be sometimes a limitation. Maybe the duration where you took your sample can be a limitation. So this would be taken into account white. It doesn't actually affect your article as an article because you still gave something, gave an addition to the literature, but it will be good for your peers when they want to do something similar. Maybe they can take your limitation into account to try and change and ameliorate it more. So it doesn't affect your article because you still gave your results, but it will help give better results in the future. Okay. And finally, after your limitation, you will summarize everything everything you have done. Um just as a brief closure to your article, the acknowledgement if present and uh finally, of course, the references. So um I'm gonna stop share ng. So this was a brief introduction on how you can write your article, uh how you can conduct your studies Uh I hope it was helpful for you all and uh in the future for our future meetups, uh we will be having more interactive sessions. Uh We will be having debates. We will be asking you to get, for example, some cases that you find in your hospital, we were going to discuss them. Uh We're gonna ask you to, to search for some topic, the newest information we have about this topic. Uh So uh yeah, so this was all of it. And if anyone have any questions I'd be delighted to answer. Yeah. Thank you so much, Maha for the amazing insights. And I would like to remind all the people who are present here. Please make sure you follow gym sock on social media and those who have already registered for gym sock. They are registered members. We will be in future reopening the registration forms again to become members of gyms, okay, because certain events would be members only event so that we can provide equal chances to all the people. Okay. And we have our link tree here. The link is provided in the chart. You can go to the link tree. You can see what are the upcoming events. You can register for the upcoming events. Also, you can follow our Twitter, you can follow our Instagram and you can also follow a linkedin. Thank you so much everyone for joining us today. If you have any questions, you can reach out on the gym sock email address. Also, we have our gym sock inquiry, email address. And later on when we have the monthly journal meetings, we will have certificates because that would be a members only event. Thank you so much, everyone. Goodbye. Goodnight. Have a great weekend. Thank you, everyone. Bye bye.