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I'm just waiting for the green. Yeah, Red, actually, but, um Okay, great. So the participants can see us now. I'm just going to give a quick introduction because it looks like some people are in. Thank you so much for coming to the I C. A one written assessment talk. We've got Chubby Josh, and they're going to take you through. Um, this very difficult first assessment, apparently, Um and they're gonna give you some tips and guidance and everything through it. As I know, all of your deadlines are coming up. Um, if you guys would like to introduce yourselves and then tell us your B s C s and then you can start whenever you're ready. Yeah. Hi, guys. I'm happy. I'm currently in fifth year, but I did, uh, pharmacology for my B s c. Last year. And I'll be doing the first half of the Taxol introduce you guys to the structure to some general tips and tricks. And then, um, Josh can go from there sick. Yes. My name is Josh, a PhD student. And last year I did. I studied neuroscience for IBSC, so it's not severe taking you through the structure. I will then take you through some of the critical appraisal and some of the future implications you you need to think about when writing your essay. Um, if you guys have any questions at any point, just pop them in the chat. Um, I think the key is keeping an eye on it, and we'll keep an eye on as well. And then there'll be a coupon at the end with all the Panelists. And you can ask them specific questions about your like pathways. Because just before we started, you want to say that the written assessment is very different for each of the B S. C s. So it is quite valuable to talk to someone who was in your specific BSC. But all the tips that we're sharing hopefully will apply to everyone. Um, so yeah, so in general, the talk, Um, like I said, I'll be going through the general structure and then we'll split it into the stages of writing. Um, Josh. Well, then take you through the critical appraisal and future implications, and then we'll give you some personal anecdotes. So what we thought was useful throughout. Um, so basically, they're an assessment. You're given or asked to choose a paper, depending on which BSC pathway you are. Um, for me, it was pharmacology. So we were given a specific paper and everyone had the same paper. But I know in other bs CS, some people were given, like in groups like groups of five or four were given papers or individually. You were asked to find papers from a specific journal. Um, for the task itself, you've been asked to set the scene on the paper and the findings of the paper and then go through the following things. So you've been asked to identify the hypothesis hypothesis that's being tested to summarize the results, Um, to further go on about to see if the conclusions are supported by the results and then comment on the limitations, which is a key aspect of this task. I think if you take one thing away from this talk, um, it should be that the emphasis on critical analysis and focusing on a pertinent point that you think the authors have missed or something that you feel the paper is lacking, um, and what the implications of these limitations are, But then also, um, appreciating that your count. Your counter to the paper has its own limitations as well. So to be able to identify those counter arguments and understand the implications of the bigger picture and still appreciate that there are strength with within the paper is something that, um I think will really set you apart. If you can say that, yeah, there's a critical There's something that would make this paper better or, um, but then say that there are still strength or there are still, um, insights that are valuable. I think that shows real critical thinking rather than just going through and being like this is what is bad about the paper, Um, and then applying that to the concept of robustness and bringing that full circle. So I didn't have to choose a paper like I said earlier, but I spoke to some of my friends who had, and these are their main tip. So pick something that you are interested in and pick a paper who's methodology you do understand and can critique. There's no point in picking something where you can't explain the statistics that were used or why those statistics were used, because then you fall into the trap of not being able to identify like what the actual problems are. Um, in terms of for your specific pathways, follow the instructions that are given regarding the journals and the date. Because sometimes, for example, in the surgery VSC it is such a narrow, um, date, schedule or specific journal that you are limited to the choices that you have. Um, and then from there, just narrow down specific subspecialties you like, um, and pick a topic. Like I said that, you understand? Um, I think this is a good thing, that if you have to choose the paper, um, ask the specific reps in the break out rooms for what they did and how they found their papers and what they found you. So because I think speaking from experience, um, it helps a lot when someone's done what you've done, So just ask them, and I'm sure they'll be happy to explain to you what specifically they did. Um, so the structure of the written assessment I think it varies, um, for pharmacology. We had to write what we call an editorial, which is very similar to the letter to the editor. But some people have to write like a more, uh, follow a different style. But the structure itself stays the same. So I'm just going to go through the letter to the editor, and it should apply to everyone. So the first thing that you start with is an introduction paragraph. And, uh um, you start with a stylistic feature. So you'll say, like, dear editor or deer all or whoever you're addressing in your letter, Um, and then you'll identify the article that you're going to critique. So we would say something like, we thank you, and I'll show you guys an example of this later. But we thank thee authors for their article on this and then, um, explain what they found. So explain the brief summary of the study, Um, in terms of what they did and how they concluded their conclusions basically, And then each of your next, um, paragraphs are going to be your appraisal points. Um, so the way that I structured it was my first paragraph was the bulkiest of them all. And that was my main counterpoint to the was my main sort of flaw in the article. And then I went into why that seem was such a big problem and why the author should address it. And the way you structure that is, you say your point and you explain it so you can provide the evidence from the paper directly and then say this is what is wrong with it or this is my critical appraisal point. But then say, however, I recognize that this critical point is limited by something else. So, like, rebut your own counter argument and then bring it a little whole circle and suggest an overall improvement to, like, fully bring it home. And then depending on how many words you have, because I think you are tight onwards itself, um, you can do other to really detailed points or you can do what some other people did is do one really detailed point and then have to smaller points that are easier to sort of, um, structure in a smaller paragraph. And then obviously you finished with the conclusion. Uh huh. So the strategy, I think when you're given the paper itself is to really hone in on the method section because that's where most of your critical analysis will take place. Um, so you need to ask yourself the questions of whether they clearly report their methods and then try to find a critique points in the forms of Do they have relevant sample size? Are there any bias is in recruiting? Are there any, um, like are the outcome measurements relevant to what they want to conclude or what they're testing? Um, and then for qualitative studies, see if there is an appropriate number of interviewers and an appropriate manner of analysis and then also read the limitations of the paper themselves have identified because sometimes that can help guide you further. But also, you want to make sure that you're not just commenting on the limitations that they described because that is kind of I would say is like preliminary critical analysis you've already been provided with. So you're not providing any of your own novel insights? Um, and then, like I said, you have once you have a really good understanding of the methods themselves, and this is something that I found really useful to do with everyone else in my B S. C. So if you just get together with a group of four or five of you and you go through the methods and you first figure out. Okay, Look, what did they do? Like when you first get a paper, it is really overwhelming to understand exactly what they so talking through that and explaining that to each other can really help you get a good understanding of what it is and then think about what are the whole. So you can start simple with things like sample size or recruitment biases, but that will help you, Then build up the stronger critical points and then you can pick and choose from the many that you identify. Which ones do you feel most comfortable exploring? And then when you move on to the discussion includes conclusion, See, Are they reasonably drawn from the evidence and then see whether the article itself fits in in the field? So is it something that will benefit us clinically? Or is it just redundant is improving something that's already long standing like Why is this paper adding something to the scientific data base is a good question to ask as well. Um, I think Josh will go into this later, but there is a useful tool that you can, um, consult, which are called cast checklist, so I'll leave that to him. Um, but other things that you can do is look at other letters that are published by the Journal, Um, or like similar things other people have published. So letters to the editor are very common sort of practice, so you can find very like many exemplars. So I think just having to read through a couple would be really useful. And I'll show you guys, um, the introduction and the first paragraph of mine so that you have an idea of what one sort of way to go about it is. But it's really important to remember that you need to take it forward in your own way, like there's so many ways to write this. So it's what you feel most comfortable doing. And then another thing that I didn't personally do, but I did get told last year, is that you can offer perspective from a medical student experience and form an opinion from that side. I just found that out a little more tricky to keep that formal, but that is also something that you can explore and consider as a form of critical analysis. So the introduction specifically, Um, these are sort of the main structure that I followed. So you will start with dear editor and then you'll write something like we read the following article or we thank, um, the authors for the article on and whatever that article is, and then you move on to what you specifically are going to address in your letter. So we would like to discuss or highlight or comment on the method like methodology and the conclusions drawn. And this is a really good idea or a really good opportunity for you to comment on the strength so you can say, like we congratulate their use of X, y and Z Um, but however, find an issue regarding this and that's a really good way to show that you have identified positive about the paper itself because they're not going to give you a paper or you're not going to pick a paper that's completely irrelevant to the field. Um, that's very unlikely. So there's got to be something that is beneficial about that paper itself and showing that really, um again illustrates that you've been thinking about the picture as a whole or the paper as a whole and then finally just briefly summarize what we've done. So like the results of the study. And, um, it's a really good idea to weave in some actual data here. That was one of the comments I got on my B s. C was They do like seeing numbers, but they don't like seeing numbers that are without context. So if you're going to say, for example, they found a positive association and then you put in just the specific numbers for that, um uh, conclusion that you're explaining that works really well because you get, like, a scientific grounding of that point. But if you just lift all the data without any context, then they're not going to like that. So I think it's a really good idea to weave in numbers, but just be cautious of doing it with a purpose. Um, so this was my introduction. Um, and just to go through it a little bit, I'm not going to read it all out to you. You guys will get the slides after, but basically, you start with a dear editor, like I said, and then you start with, um, and this one It was mine was more of a form of an editorial, so it wasn't directly to the authors. That's why I start with more of a like a scene, like setting the scene and what the paper is about. And then you talk about what the hypothesis was, what the results were. And then, like I said, I have a sentence that starts with commendably and then what the strength of that study was. And then you say what your main critical analysis point was. So for me, it was, however, the use of national data archives does not stratify exposure from non exposure. And so that was my main point. And then, from there you can talk about why that is a relevant critique. Um, or whatever you think is relevant to explain to set the scene for the introduction. So something that your readers need to know for them to understand that point and then just bring your full circle. So everything that you're going to discuss, obviously signs posted in your introduction, but don't do any sort of analysis. Um, but this will be given to you. So it's something for you to go back to, and it's just to show you how I applied that, um, sort of templates I spoke about earlier. Um, this is another example that I got from last year's talk. Um, like I said, there's a stylistic features bit. So in this case, they were writing to the land set, and it was a letter to the editor, and it was a very specific sort of format that they had to follow. So if you're giving, you're given a journal to follow. Just follow that. So follow those guidelines specifically. And then, um, the next part is, of course, identifying the article and what its purposes. And then what your argument is, And then details on the study and it it's up to you. What order flows best for your writing? There, for example. Like, I put the details of the study earlier, but again, you have some room. Uh, you can be flexible with that as long as you address all the points. Um, the conclusion itself. So, um, you want to bring it full circle again? So you want to say what your recommendation is? So what would make this paper stronger? You don't want to just conclude by saying, Oh, this is what's wrong with the paper. You want to give a future direction. So you want to say, Like, how could this be addressed? Or how could this study be made more valid? More robust? More, um, more clinically relevant. Whatever it is that you were talking about in your and you're, uh, in your editorial itself. And then again, this is a good idea or a good place to Also, we've been the concept of validity, Which there are notes about that and other talks. I'm sure. Um, but basically, it's just about like where the paper stands, um, in the wider context. So there you have it in a bit of my conclusion, and it can be really sure it can just be, um, again, we thank them. We know that there are strengths, but these are the limitations, and we think that this would bridge that gap. Um, and it's pretty straight forward that way. So that was my little brief, um, on the structure. I think Josh is going to go through a critical appraisal and if you have any other questions, just popped into the chat, and I'll be looking at that, so I can answer. Awesome. So, yeah, So she has taken us excellently through the structure of the I see a and literally how to get your essay. I think that's really helpful to have you guys, and that was really useful. Uh, what I'm going to do now is trying to give you a sense of what sort of points to pick out what they're looking for. I'll then give you like a road map on how to structure these points into your essay. We've been gone from Chevy said. And then finally, I also want to give some sense of the importance of future implications. Like Charlie just mentioned, you're in the conclusion you want to say how this research can be taken further. I think that is a key part. Bs A. And it's something I got feedback that I should have been more of in my essay to get a better job. So I'll take you through that as well. One thing I want to say right off the bat, just sharing a person I like to know. From when I did this, I see A is initially I hated basically avoiding papers because I thought, you know, Who am I, some literally medical student trying to appraise the brilliant work. Don't worry too much about that. You know, it doesn't matter who is saying it. What matters is the quality of your arguments. And naturally, most research papers are flawed. You can't control the every single variable. You can't account for every single limitation. So it's expected there our weaknesses in every single research paper you see, even if it's in the top two channels like nature of the onset. So don't be afraid to really speak your mind and point out where you do the floors, because that's what they're looking for. They're looking for you to take charge of your own learning and for you to point out what you see the work to be flawed. So if you think it's a flaw and you can develop, develop that floor when you talk about it in your essay, do not be afraid of like appearing too critical or appearing like to or knowledgeable. You've got the knowledge, if you can see it. So just to try and get you through to a critical appraisal. Oh, I decided to go cool. So there are three main question. You need to ask yourself in critical appraisal. Is the study valid? Can I trust this study? And what does this study add to the wider field? So starting with the validity of the study is that a clear and does the conclusion much what the name is? So in research, we see researchers try to answer one question, and their conclusion is completely different. So if you see mismatches in the conclusion compared to what they were trying to look for, the night is automatically the floor because likelihood is they've collected data, not got the hypothesis they wanted. And then suddenly they changed the whole paper just to try and get a positive fighting and to try get published to look out and mismatches between a mom and conclusion. I think Charlie mentioned this in a talk already. But one of the key sections you want to look at a critical, critically appraising something is methods. The methods is going to be the place to look for where you can see a lot of the floors present. For example, if it's a randomized controlled, uh, controlled trial, have they selected the correct population? Have they got a an appropriate control population and reduce the risk of can founders. Some methods are place to look for these weakening points coming onto the trustworthiness of results. You want to be certain you read the paper. Okay, I can see what they've collected. I can see the results are clearly stated, and there's a nice chain of command going on. If the results are really hard to interpret, if it's a bit scattered, that's a bad sign. You also want to make sure that the values they are referencing are also reference in Table's as well. You'd be surprised at the amount of times that they quote a value in the text, and it's sort of like not really matching what said in the table. So, for example, sometimes they can say Oh, you know, we found a positive difference between the control group and study group. But when you look at the actual table of results, it may be that there was no significant results of the confidence. Interval may overlap one, But in the text they're saying as a positive finding and because sometimes what they do is they do subgroup analyses. So let's say you're looking at the risk risk of stroke in a population population you're seeing if your new drug works. The new drug may have been shown no difference between the control and the intervention across all the participants, but it may have been beneficial when you did a subgroup analysis on participants over 60. That's a and that's the finding them a report in the text. But that's not in the table to be careful of mismatching like that. Now we're looking at the value in relevance. This is really important when it comes to thinking about future implications. You know, your study of choice, maybe a novel therapeutic agent. Uh, for example, let's say it's a monoclonal antibody, but they've only assessed it in red cells. And then, in the conclusion was like, Oh, this therapy is fantastic. It can It can cure cancer. That's clearly not the best conclusion because it's shown in rat models, you know, for a stronger conclusion. And if you're going to say it cures cancer, you want that study in human subjects. So be careful where they are. So over exaggerating the claims. Best methods we have, it's okay to go to the next side. Sorry, cool. So for a more granular approach, too critical appraisal, I think Try to follow this QR PICO Rambos of the FCC structure. Um, I think the main wants to focus on for the purpose of your essay PICO and Rambos, because those areas are really rich for your analysis, I'll take you through each of these ones briefly. Next time, please. So starting with peak Oh, I think he made an excellent point in saying like, you know, when you get the paper, try and discuss with friends what they actually did, because when you get the paper, you want to understand how they actually answered the question they were trying to answer. The way you do that, if you look at the methods you try and get a sense of Okay, who or what was the study conducted in? Was it patients? Was it a cell line? Was it animal models? What was the intervention they were trying to look at, and was there an appropriate control group that were much for confounder to the intervention group and finally, were the outcomes that they measured relevant? You know, if you're design, if you're doing a randomized controlled trial to see if a new agent to treat stroke works. Your album of interest is going to be dead from a stroke, right? So you want to make sure they are actually picking the appropriate outcome measures. And again, that can be a source of limitations If you feel that they are not looking at the best outcome measures. Another source of limitation would be inappropriate control groups. For example, if you're looking at a new therapy for heart failure, so you're doing cardio cardio vascular B S. C often cardiovascular sciences. When you do a new randomized controlled trial for a drug that should be against the current gold standard, gold standard exists. There's no point investigating a new against placebo if we already have a very good treatment paradigm for X disease. So if if a solid treatment paradigm exists for the disease of interest, the best round of controlled trials will compare any new drug to the gold standard not to a placebo. Because you're trying to get a new drug on the market, you therefore want to show it's better than the more we have currently got. Not just the sugar pill, for example. That's a good one to the California on, um, next slide, please. Okay. Oh, yeah. Next time. Again. Sorry. A good place as well. Particularly if you're doing a randomized controlled trial. Is that the recruitment methods? Now? Something you may not be aware of is that there's two types of recruitment consecutive and nonconsecutive, essentially in consecutive recruitment. You advertise your research, you know to the population of interest, and you recruit in order anyone who meets the inclusion criteria. So it's literally a first come, first serve basis. A nonconsecutive recruitment? Not necessarily. It's not. It's essentially not a first come, first serve basis. So even if you meet the inclusion criteria, the researchers may say, Okay, we don't want you in this study. Now there are pros and cons for both. Consecutive sampling is very time. It's very. It's less time consuming because you literally just advertise. It can get as many people as you can, quickly nonconsecutive sampling because it is more time consuming. And it may introduce a sampling bias if the researcher is systematically excluding people who, who, he may think may not better benefit from the therapy. If that makes sense to take a close look at as to how exactly they're recruiting patients for under control trials. The best ones will be multi center because they can reduce the risk of selection bias. So let's say you're doing a surgical science and technology B S. C. It could be you're looking at, you know, outcome rates from gastrectomy is across the UK if you're only picking hospitals in London, which may be the best hospitals that may not be representative of how that surgery is performed throughout the entirety of the UK, So ideally, you want a multi center recruitment to account the regional differences in the quality of care and the quality of the surgeon as well. I think that's particularly important for the surgical science of B. S. C. Where, of course the skill of the surgeon and caliber of the surgeon may confound the results seen. So try and make sure it's a multi center analysis for surgery, feasible and please. And again, um, you want to look at how controls and intervention groups were obligated. Obviously, the best one is randomization, because that was sort of even out the distribution of potential founders. Of course, there's no guarantee in that it is random, so there's enough chance you may get a systematic differences between the two groups, so it doesn't always guarantee that does reduce and sort of like the risk of the founders. Of course, the best ones will be blinded, ideally, triple blinded, whereby the patient, the researchers and the scientists conducting the research are all blinded to what? Who's got, who's getting what and what the outcomes are. You know, if it's not blinded, then you've got the risk of placebo effect. You've got the risk of, um, procedural bias, which we'll talk about later on. So again, you want to be looking out for all of these things. Now, in Randomization, there are two different types, so you've got blocked randomization where you let's say you get eczema. Patient half will be randomized to each arm, irrespective of where they come from. Close randomization again a bit better than multi center studies, because this ensures that X number of people from each center are allocated to each group, so that can account for differences in surgical care in the standard of care again, very important for a surgical B S C, where you could be looking at a multi center analysis across hospitals in the UK The most appropriate randomization for something like that would be close to randomization if they're doing a multi center study. But doing a block randomization, then there's no guarantee that you've controlled for those for those regional differences in the quality of care. So multi multi center studies must have cluster organization ideally, to actually reduce this election rolls. And this side, please. So going, zooming into the randomized controlled trials a bit more, Um, take a good look at the maintenance. This is a This is a potential place where limitations can occur. So you may have heard of the intention to treat protocol. So the intention to treat protocol is where once you randomized people to the control group and the intervention group, you treat them like like that throughout the entirety of the study. So you analyze as you as you saw, they organize the study. That makes sense. So if you put someone in the control group at the start, you analyze as they if they're in the control group at the end, you keep them in the same place. That's even if they drop out So even if you leave the study and don't take part in it, you are analyzed as if you were in the original group you were randomized to. That's really important because that can minimize attrition. Bias. Patrician bias occurs when you've got a systematic differences in the people who are leaving study compared to who are staying in it. You want to try and keep that less than 20% to preserve more of the study. So one thing to California randomized controlled studies would be how many people drop out, and they should also report the quality of the characteristics of people who drop out. If they don't report those qualities, it could be that they've got sort of a systematic difference compared to the original population. And that may be explained the results. For example, again, if it's a stroke study and everyone who leaves the study smokes, they have a terrible diet, and they're older. That may explain why your new therapy is looking like it's working purely because you've eliminated all the unhealthy people who have the risk factors to take a good look at the characteristics of the people who are leaving. The study because that may be some room to discuss a limitation. And ideally, you know, when you're doing a randomized controlled trial, you want to keep both groups equal in terms of how often they are visited by a healthcare professional, how often you measure the outcomes of interest. You know how often you actually engage with them. Because again, if let's imagine, you're on two different groups and one group is always seen by the doctors, the other group isn't. They may start to get a sense that they're the they're the control group if they're not being seen by anyone. So again, make sure you're looking into how they actually maintain a trial going forward. I've already mentioned the importance of blinding and again triple blinding is the best. Um, obviously, that can be hard for surgical surgical studies. Obviously, if you're investigating a new surgical technique, the surgeon is performing X technique and knows what he's doing or what she's doing as well. So in cases where it's hard to blind, it's off like way to make it more robust. For example, blinded outcome adjudication, where you've got like a objective observer analyzing what's going on rather than the surgeon himself or herself. And please. Yeah. So this part, the only thing I want to take away from this slide is the public calculation. You know, you really want to keep our 80% to reduce type to error and a false negative occurring. Um, the way you can calculate power is looking at G style power. That's an online software where you can put all the parameters and that will tell you the power of your study. They should be reporting the power in their study because that gives you a good sense of have the avoided the air or not. So if it's if the power is quite low again, that reduces the quality of the findings to make sure your comment on that Like I said, 80% is a good level of power. You also want to take a look at the effect size. Now, this is really important and something I didn't really appreciate until I started the B S. C. So you can naturally, you can find statistical difference is you know, a lot of things. You know, a lot of things do correlate and do coincide with each other. Obviously, some correlations stronger than others. So whilst there may be a statistical differences or the, uh, the outcomes of interest, the effect size, maybe something like no 0.1. Which means that the two are very, very minimally minimal related, even though the difference is significant if they reported effects, eyes comment on the size of that again, you know, in research typically 0 to 0.2 is weak. 0.22 point five is moderate, and anything 50.7 and above is sort of strong. So, yes, you may have a significant difference, but the effect sizes tiny. You know how important is it then? So make sure your comment on that as well, because often the papers like Oh, yeah, significant, you know, look at look at these significant findings nuclear effects eyes. And it's tiny, making you question. Okay, How important is this trend? Because it doesn't seem to happen too often, albeit it's significant. Another one to cover for is the difference between absolute risk and relative risk. If they report relative risk, that may be massively exaggerating how strong the link is. So let's imagine I'm investigating a new drug that can reduce the risk of colorectal cancer. Let's just say the natural incidence colorectal cancer is two out of 100 with my new drug or with my new risk factor, let's say risk factor with my new risk factor of interest. Let's say smoking that incidence goes up to three out of 100 relatively. That's a 50% increase, your two degrees a 50% increase, and the study may report that to make it seem stronger, but the absolute risk is small. You know you're only going from 2 to 3, so they're reporting relative risk. Take a look at the sample size because if it's not a large sample size, then the absolute risk is going to be tiny and therefore minimal and probably irrelevant. So again, take a look at the type of risk the report and be very careful with relative risk because it's often over exaggerated. And next time, please, obviously, and next night again, coming on to sort of like x amount of the time now. And this is really important when it comes to actually looking at the quality of the conclusions made. So in external ability, you're looking at how generalized the results are the rest of the world, you know. So based on this study in this sample, what can I take from this and apply to other similar instances now? Resource availability is a big one, I think, for the surgical Bs CS and also a remote medicine. Let's say you're looking at a study that was conducted on a surgical center in London. How applicable is that to a surgical center in the poll or another less developed country? You know, you can't really generalize the findings to well, therefore limiting, limiting you know how great the study is again. What is the cost effectiveness, effectiveness of the therapy If the studies are investigating, you know, really expensive monoclonal antibody or a really expensive, you know, surgical imaging technique again, you know, how can we that limits how well you can translate that into the real world and therefore limits the future implications and relevance of the results. Again, you look at the population as well. The demographics really important for this and, for example, in my neuroscience BSC projects and my final project for big right up. My study was conducted in elderly participants because I've only conducted it in l two participants. My findings are not to generalize able to younger people, and the findings may be different. So you want to make sure that your you know your sample of interest is quite diverse so that you can apply it to more context if they're only looking at males. If they're only looking at old people, you know how limits how well, you can generalize that over context, and that's that's a big limitation in the research. So again, when you get the study, you want to look at a sample and think, Okay, how generalized is this to the rest of the world and the rest of the field? Because again, the strongest studies are more generalized able. So I've taken you very quickly for the critical appraisal and some some of the nooks and crannies to look out for, especially the big ones. Now, how does that translate into your actual? I see? A. It is the large trunk of your essay. You know, a lot of the marks that they want that they give in this exam are sort of dedicated towards your ability to critically appraise the research because anyone can solve a comment on what they did, what the results were. Most of you can do that. What the harder technique is is actually looking deeper and analyzing it for yourself, which is why it requires, you know more was dedicated towards it because you're going to get more market that potentially so you want to keep it balanced. First of all, try and comment on 2 to 3 strengths because there will be strength of the research. You know, when I talk about strength, I mean, have they blind in the study, have the control to keep the founders? Was the recruitment strategy good? What did they use? An appropriate cell line, for example? These are all the things you want to look out for, are trying to work for. The weakness is like we said they will limit. They will discuss limitations in their own research, will volunteer some limitations. So don't just, like, copy and paraphrase what they said. The best critical appraisal for the I C. A will be your own ideas, and people marking your work want to see your own your own ideas. They want to see your own analysis. So what you can do to help you with this as like a cheat code to sort of corrections. Bring in similar papers. Bring in the papers, which you've answered a similar research question but may be doing it in a different way. And you think it's a better way. You can mention that the limitation of the paper you're looking at them because they have another paper is better, and it's answering a similar question automatically. The limitations of your paper is that it didn't do these things that a good paper did to try and bring in other papers on the same research topic. To see just the amount of different ways. You can actually answer the same question because that will give you some inspiration for the limitations. Also, what you can do is like whilst looking at the similar papers, look at limitations that they included but wasn't included in your paper of interest. And you can sort of copy those if it applies. That's another good place to look for the mutations if you're really unsure. And again, try and name of a bias. Um, it's always an easy way to get simple marks, and like Charlie said, biases are a good place to start because sometimes they are simple spot, and then you can build your analysis further. So I'll include some analysis on the future side. And it's like so here are the nicest looking out for So you've got observer bias where? Let's say your study isn't blinded and you've got a doctor who knows who is in the control group, who is in the intervention group. The way they ask the questions can sort of influence the results. For example, let's say a doctor knows you're in the intervention group, he may say to you, or she may say to you, Oh, you feel better now, don't you? Whereas to the people in the control group, he or she may say, Oh, you feel a bit worse today, don't you? Can you see how that may bias the results slightly? If the researcher knows who is in each group and is asking them questions that may influence the response to the questions, a big one is sampling bias. So this is what your sample that you you've chosen to investigate a question don't really represent the appropriate population. For example, you know, if you're investigating risk of stroke you want to include people from different ethnicities, people who smoke, people who don't smoke, people with bad diets or great diets. People who exercise you do exercise. You want it where you know you've only got males. You've only got people from a certain ethnicity. You just don't want to have these confounder. Essentially. Do you want to try and get a good mix of confound ear's to make sure your sample is more germane, liable to the wider population and finally, response by us? This ties in with something called health or social desirability by us, and this is important in question is so subjects can sometimes give answers that the interview wants to hear. For example, let's say you're doing I think that's a sport and exercise B S C. And you're sort of trying to get a sense of how often people exercise on a week to week basis. Most people in the UK know that they should be exercising, you know, 3 to 4 times a week. They know they should be eating eight portions of fruits and veggies every single day. They know that, and therefore when you get these questionnaires, they'll say, Oh, Yeah, I go to the gym every day. I eat all this. Verge you all this fruit when in reality they don't They're lying because they know what the researcher will want to hear because you want to impress the researcher. So be careful of questionnaires because they are very open to people. Not telling the truth. Do to help desirability bias. So try and name. Drop these biases and any other one you see fit when you're doing your paper. Now she mentioned as well looking at the cast checklists. So I've included the link on the subsequent slide. Essentially, cast is a tool kit you can use to analyze different types of studies so that the checklist for randomized control trials there's a checklist for systematic reviews. Checklist for co studies. Essentially, what caste checklist does is it tells you what are the strengths and weaknesses to look out for when conducting the studies. So what you can literally do is if you picked a cohort study if you picked a randomized controlled trial, get the correspondent cast checklist. Have it next to you when you read the paper. When you read the methods and results, you know take a look at the things they've missed. Take a look at the things they've done well, using that checklist. So I'm taking you. I'll just take you through. Casodex is under control trials, so if they randomized it, that's going to reduce selection bias. If they blinded it, that's going to reduce detection bias. So look out for these things because they are literally giving you water comment on, you know, under control trials. You want to make sure. Have they told you how they're going to analyze the data? So if it's intention to treat, that reduces attrition. Bias protocol analysis is the opposite of the street to impair protocol analysis, even if people if people drop out, you don't analyze the data. So intention to treat is the best one because you analyze even the ones who drop out, which minimizes the tuition bias affecting the result. So every randomized controlled trial they should tell you have the used in addition to treat, or are they used for political analysis and again, look at the treatment's effect, the effect size maybe very weak. So again, look out for that. So even if the results are significant that is not the full story. The effect size is also very important, and you become a checklist tells you the pros and cons of randomized controlled trials. So you're making the point. You can say, you know, by randomizing getting funding it. This has helped the researchers determine causality and have a higher internal ability. You can the point you make to the pros and cons, respectively. So make sure you're looking at these cards checklists because they tell you what's good and bad about each type of study and what to look out for. And I think you know the the link, and you can use that when you wish. Sorry, just just I'm just going to drop off now. Guys, I have a basketball training, but it's going to take over and do the rest of the presenting. Obviously, shoot me an email if you guys have any other questions from specific or not at all. My email's in the beginning of the sides and, um, enjoy the day. Yeah, two seconds. I'll just bring it up. All right, Let's see. I'll just bring actually, no, I don't wanna do that. I'll just share the slides. Mhm. Mhm. any questions. Feel free, obviously, Keep taking it. Mhm processing Slide one of 27 I'll tell you when it gets to you. Brilliant. I'll just click through these. I'm just waiting for it to move along now. 1 13 almost now. But honestly, it's focused, too. And anyway, you just need the future implications. Go ahead and ask questions on the chat guys, if you haven't. I think this is the perfect time. Uh, I will say one thing is what is happening? Um, if anything, you want to make your essay easy to read and quite creative, you know? Trust me like our colleagues in neuroscience that you told us. You know, if your essay read well and the structure is good, likelihood is you're going to get a good mark. So, like, don't worry too much about the content. What's also important is how you structure it. So at the very least, you know, make sure your essay is nice to read. It's got a good flow because that will help with the readability and that may, you know, bias them to give you a good mark. That's just like a little. It's a hard and fast rule. But if anything, the USA, easy to read. It goes along with trust me. Okay? I think it's this one, isn't it? It's like 24 cc. Yes. So here's the castle checklist reference. You know, when you get these slides, look this website up. And if you picked a cohort, so do you find the relevant one? If you pick the RCT, find relevant one that will help you in your analysis and make the points. It will give you all the terms of looking looking out for, like, the liberty. You know something by us. Your markers. Want to see these words? These checklists literally give you these words and you just bring it together. Excellent. So future implications. Now, this bit is actually really important. And it's something you want to think about for yourself, Okay? Because the researchers don't always say it, and this is another key skills are assessing. So one key still there assessing is can you critique a paper? A similar but different key skill is Can you see where this research is going? Can you see what it adds to the field? Now? I got knocked down a little bit for not talking about this in too much detail. I only did. I think I gave it to two senators marks. So when you get the paper to get the so let me try and give an example. So let's say you're on the cancer Therapeutics, B. S. C. And your paper is looking at a monoclonal antibody, a new monocle antibody to treat to treat colorectal cancer. Let's say Okay, that's what he may have been conducted in a rat cell line or or a colorectal human cell line. Okay, Obviously you like, you're not going to read the paper, and I think, Okay, I'm going to give my patients this agent, you know, it's working these human cells, It's working the rat. It's going to work in humans for sure, right? You know, actual human is going to work. That's obviously not what you're going to do from that research. What you're thinking is okay. We've shown it. Works in the cell line were showing it works in animals. Next, we want a better animal model, or we want to know an actual human trump to try and think the steps of the research that can aid the translation of the drug into something useful. Okay, again, it's It's very easy if you're looking at a drug, because often you'll do a study that's looking in human cells or red cells. And obviously that's not generalize able to an actual human. So you want to say, Okay, next step would be either a full animal model, like a rat, or it could be an actual huge trial. Okay, so you want to actually question, Okay? How am I going to use that result? Am I going to look at this paper and think? Okay, we can implement this right away. If not, you want to say Okay, what can we do to aid? How well we can implement it? What can we do to a the translation? A good one for you to see if they're looking at rat models. Rat models obviously limited because their brains are not, You know, they're not going to get dry or so psi, and that's different to a human brain. Which does the term for that. If you're doing the neuroscience, B S C. And they're giving you a rat study is that rats are listen cephalic so that just means they have not got the ridges and curves in the brain, which humans do, and therefore the brain can behave differently to a human limiting. How generalize about the findings are, that's just a tangent. Neuroscience. Now, once you've sort of questioned how relevant defining our clinical practice or two informing guidelines. If there are gaps in that, you want to design a study which would address those limitations and then a this translation Okay, so this goes hand in hand with limitations. Limitations are nice segue into this section. You can say, you know, having discussed the limitations and important for you to study would address these and literally say how you dress limitations and take the research further to make it more applicable to your clinical practice. So this will really help your structure if you do limitations and then stay away nicely into future studies, which address the limitations in the research but also are designed to add further information or to make it more generalized able. That's a nice Segway into it. So essentially, the key question. What you want to ask yourself when looking at the future implications? Are the these two? What does this research add to the field. You know what does it contribute? What, what? What are the new things that tells us And therefore, how important is the future work going to be further Follow up on the research question because obviously it's really hard to fully answer a research question with certainty. There are always limitations in the methods used, the animal or cell lines. So you want to be looking at the future work you can do to address those natural limitations. You know, having started my PhD, I've realized how step by step research is. You know, I can't jump straight to a human clinical trial. I have to first start off with that sells, then human cells, then wrap a full rat. Then then for humans. You can't just jump straight to the human thing. Okay, so what you want to do when you look at your paper is give the steps needed, and that in most science, is that they are the steps to D three d. You know, an animal, then three d and human. Okay, those generally the steps. So if you're struggling to think of the future steps, just think that pathway to de animal human. That's normally how the research plans out to try and dedicate some time to this because you want to discuss this in a bit of detail. And this is the part where you can be creative. You can literally design the future studies and say how you think they should go based on your analysis. So there's no really right answer for this. Just try and be creative and try and design a few study that would add something more important. And we'll address the limitations in the current research. That's a possibility. The weak side. That's okay. It's a personal jokes. I've tried to get these throughout. I think the first important point is, you know, plugging reas mentor scheme. Try and contact your B S C mentor. They're really important to have. If you've not got one, you know, I'll put my email on the chart, and you can literally feel free to send us A. If you really do have anyone to, I'll be happy to say, Just give me some feedback Trying. The point is, try and get some feedback as you can from all the years you have done the SC or VSD mentor. That would be a really good one. Um, I think another way is just making it digestible. You know, it's your You are tight in words, and that's a blessing and a curse. So I tried to do is like in a consolidation week. I think I tried like 1 50 to 200 words a day, and I did. It's section by section. So for okay, today, I'm going to introduce the topic, right? My word for that. Next day I'm going to think, Okay, I'm going to talk about the methods and results, and then after that, I'm going to actually critique the study. After that, I'm going to do the future implications. Try to split it part by part, and that will help you. So you have a nice structure. It'll prevent you from being overworked and overstressed, and it means you can literally focus on one part party and therefore maximize how well you do each of these sections. So I think it's nice just to split it up like that. Like I said, also, finally, anything make it nice to read. It is a psychological bias where, like higher scores are given to essays are that are easier and nicer to read. So if you're worried about you know the that for your analysis, just make sure it's nice and structured. Make sure the flow is clear, because that does take you a long way. Trust me, I know it's not a hard and fast rule, but it happens. All the best universities where better marks or an average gives those essays that are easier to read to make it easier to read. So that's it. From my end. I am more than happy to answer more targeted questions, and I can see some of the chart, and I'll answer them now. So a good question about critiquing the funding this can apply where, like you're looking at a randomized controlled trial investigating a new drug, and then that trial is funded by a pharmaceutical company, for example, Fighter that does limit how strong the findings are. But it's not a hard and fast rule. There are some excellent Reece papers investigating the drug that's all sponsored by pharmaceutical companies. It's not always the best place to look out for, because it's not hard and fast rule, but it does increase the likelihood that some bad science has been conducted, but not always, because that's how you can treat the funding. Good question about finding the effect size versus for a statistical difference besides more relations. But essentially, when the report, the values or the confidence intervals, they should also give a beta value so literally about the value. And that will be on a scale of 0 to 1, with values close to zero being weak values closer to one being stronger, it's essentially like spearmint frank correlation value. It's like our value again. Not every research needs to report it, but if they do report it, look at how strong the effect sizes. But it'll be a beta value. It will be the beta symbol equals X whatever okay, or like a small are equals x. They are looking at the effect size and that that will be reported with the values. But that only applies more to correlation. Good question. Do you add the future implications in the conclusion or in the appraisal paragraphs? I would personally do it in both. So based on the limitations I've said in the sort of critical appraisal, I would then sort of think about ways to address those limitations, to make the research stronger. After that, I would then talk about you know, the value of the research and what further steps needs to be done to complete it in the conclusion. So I talk more about, you know, designing better studies in the limitations part, and then secreting into the conclusion, I would say the value of the research and where it's going in the future and what needs to be done in the future to make it better. If that makes sense. So you allude to it in part, so one in one part you're addressing the limitations of this study of the only this present study in the conclusion of talking, talking more about the future locations, your your sort of saying what else needs to be done, what their work needs to be done to increase the value of this current study. And that is that's technically different to addressing the inherent limitations, the research, because you're talking about the next steps and therefore the future implications. Um, you have to expect a call when you use, you know, you can assume the reader with in the sun, so yeah, There's no need, like difficult bias, you say or define every single key word you use. They want you to use this scientific language because that success that's assessing your skills, a researcher to communicate, you know your work. So I assume that technical knowledge is there because it's designed to be published in the journal, right to people reading. The Journal will know what these words mean, most likely, so there's no need to define them. I'll explain. Brilliant. Thank you for your questions, guys. Thank you so much, Josh. That was a brilliant talk. Um, and thank you so much, everyone. So we're going to start now the Q and A, and this will be a specific to the B. S, C Q and A. So if you look on the left hand side of your screen, you'll see four icons. One will say mainstage. The other will say breakout sessions below that will be event info, and then there'll be sponsors. So if you can click on break out sessions, you should get a pop up that you can scroll and it'll have anaesthetics, too. Critical care. Write down to what's the last one? I think it's translational respiratory medicine. I believe, Um, just click on your desire breakout room, and your tutor should be there, but I will come through and check. But thank you so much. I'm just going to send the feedback from in the chat. And I would really, really appreciate your feedback because I'm always looking to make these events better for you guys. Um, and it will help me when I'm passing things on. Right. Great. So go ahead and go to the break room. Josh, if you're willing to stick around, you can click on break out sessions and go to the new rash breakout room. Yeah. Just share this. Brilliant everyone you can head off now to the breakout rooms. Um, and I'll be checking to check that everyone's They're brilliant stuff. All right, See you. Look, everyone. Thank you so much.