FastTrack LIVE #40 | Which Type of Literature Review Is Right for You?

Narrative?
Systematic?
Scoping?
Umbrella?
Critical?
Meta-analysis?

They’re not interchangeable, and choosing the wrong one can cost you months.

In this live session, I’ll break down:

✅ Traditional Narrative Reviews – when they work (and when they don’t)

✅ Systematic Reviews (PRISMA-based) – ideal for publication & PhD by publication

✅ Scoping Reviews – mapping a field without over-claiming

✅ Umbrella Reviews – reviewing the reviews

✅ Critical / Theoretical Reviews – building arguments, not just synthesizing

✅ When to avoid meta-analysis (and why most early researchers should)

As ever we'll cover your video questions and provide feedback on your research too - to participate submit here: https://forms.gle/gp9cceQfWrXXWcXb6

Transcript

SPEAKER_00 0:00

You should you do? It's a question as a professor I commonly get asked: should I do a narrative review, a scoping review, systematic review, critical review, indicative review, uh systematic review? It can really be bewildering and seem mystifying when you're just starting out, but not today. We're gonna help you wade through the different types of lit reviews, take the confusion out of the mix, and help you stay focused on what it is you're really trying to achieve with your literature review, and from there pick from a menu of options which type is gonna best get you to where you need to go in your research journey right now. So this is gonna be relevant to you if you're just starting out, maybe you're grappling with a lit review, you don't even know what type of lit review you're doing. It's also gonna be helpful if you're in the thick of doing a review and you've been getting stuck because sometimes what you'll come to find is getting stuck in your review means maybe you didn't have clarity on an earlier foundational step that you just kind of glossed over along the way. I see this especially happening commonly with people who, in absence of feedback or maybe not getting the support, they need outsource research judgment to AI that takes them down a rabbit hole. Um, for those of you who are new to the channel and to these live sessions, I'm Professor David Stuckler. I've been a professor at Harvard, Oxford, and Cambridge, and this channel is about providing you the support that I wish I would have had when I was just starting out. Because frankly, I learned the hard way. I learned by making mistakes, and that's a way to learn. But the faster way to learn is to ask somebody who's been there and done it to show you how. You'll get to the same place just a lot faster. Now, I've provided that benefit one-to-one to my students in the Ivy League over the years. Now I want to make that open access and available to everyone. And that really is the goal of Fast Track and our programs to make that implicit research logic that's often handed down, explicit, and available for all. As ever, we're going to take your questions. We have several that you've submitted at the end of the session. Um, if you have some as well, I always check the chat in the comments. So do drop them there. You can also see them off-site today, so I do apologize in advance if we have any hiccups. Um, but I've decided this year, rather than wait for the perfect recording setup, I want to protect this time that we have every Friday at 4 o'clock uh Central European time. Uh, that's 9 a.m. US Central and uh 3 o'clock UK, uh, so that you can consistently know I'm gonna show up and provide feedback to you on your research, uh, as well as cover themes that you suggest throughout the week you'd like me to cover. So think of this really as your time. So, with that, what I'm gonna do is I'm gonna pull up a whiteboard and let's dive straight in. I'm gonna say, uh, yeah, and I can see Israt here. Israt's asking how to choose a good topic. You know, we just covered this uh a few sessions ago. So, guys, we have a lot of resources on my YouTube channel. And if you go through the live sessions, you'll see a lot of live sessions on topics. You'll also see videos that are pre-record videos using our two-stage method for finding topics, identifying gaps, and helping to confirm if it's a winning topic using pico models, nearest neighbors, other tools that we use inside our fast track systems. So um check that out because it'll go into more depth on the topic choice than I can get into today. But we do have some questions and time at the end, Israt, so I may be able to come back to that. Um, and Akari, hey, uh, welcome. We're truly international. If you're on Team Replay, by the way, give us a like. That helps the algorithm find people who might benefit from this message and wouldn't otherwise get it. So the algorithm helps us to reach and serve other early stage researchers like many of you. Okay, let me go ahead and share my screen. I love pulling up whiteboards because I find the people who I work with uh tend to be quite visible. Uh visible, uh visible online, but they tend to be quite visual in terms of how they they think and approach research. So, first, I think it'll be helpful to uh just demystify the types of reviews. So, some of you, if you're doing the most basic kind of literature review, the more traditional one is sometimes called a narrative lit review. And this this is what you may have been more familiar with as an undergrad. You might have had a topic or theme, and you start Googling around for stuff and cobbling it together, and uh sometimes in a way you're just sort of winging it to put together an argument. Um, that's well and good, but at the PhD level, a lit review uh is is much bigger and more formalized. So some of you get asked to do a literature review at different points in your journey for different purposes. So the most common starting point is someone's trying to figure out a topic and their supervisor says, Oh, well, go do a lit review and come back to me. And so they're doing the lit review to try to figure out their their topic. Not necessarily to publish, but to just get a feel, kind of the lay of the land, understand what's out there. Other purposes is it can be required. It's part of a research proposal, it's a chapter inside your PhD. And whichever reason you've been pulled into doing a literature review, and you're almost always gonna have to do a lit review, it's helpful to know which style you're doing. So, narrative is one that's that's really uh it doesn't really have a built-in structure. So I'm gonna put in some attributes, has no built-in structure. You've got to have to make the structure yourself. And I think this is why some people get lost, uh, because they just dive in and they're kind of muddling around, finding some articles, reading that, finding other articles, and sometimes then they're finding, well, I'm not finding enough articles or I'm finding too many, and it's because there's no built-in structure, and you have to define that structure yourself. And so, in any literature review, you need to be aware that there is kind of a funnel-like structure. And this is also almost why you need to define, understand why you are doing this literature review for yourself. Is this uh for my general knowledge, is it for my supervisor, is it to find gaps, is it to find topics? Typically, um what you're trying to do with a literature review is you're trying to justify, sorry for all the caps, guys, justify the the reason that your study needs to exist. Alright? Uh and so that that's probably the most basic reason reasoning for a literature review. So what that already means is lit review is not what a lot of people think of it. Is a lot of people think it's just just a summary, but it's not. It's actually a strategic argument for something. And I I think the lit review is a bit of a misnomer, uh, but for that reason. So think of it as a strategic argument. And the and the way to think about this is a lit review is gonna follow a funnel shape. So we're gonna have to get into some basic comments about a literature review, but it follows a funnel shape in the sense that you need to go one level up and sometimes you need to go broader up here. So you're gonna read a little studies that are a little bit wider, and by the end, you spew out this justification for your study, which might involve setting out what a gap is, and maybe your research questions that's gonna bridge over to your methods later on. Now, this narrowing structure of the funnel, where you go broad to more precise to ultimately very specific about what you want to do, that's where you have a narrative arc in your lit review. And so this is what a traditional kind of narrative summary is not systematic, doesn't have a built-in structure, um, and it is not aiming to be reproducible either. So you're gonna go around and read different things in the literature, but it's not like just just looking at the chat, Akari does this one way, and then Isra would be able to reproduce exactly what verbatim what Akari did. Uh hope that that makes sense. So uh so this is uh very and I can see Fun Shu's asking, is this a live presentation? Yep, we're live, Fun Shu, so uh shoot questions away. Um, these are always always live, these are not pre-recorded like the rest of my channel. Um so these are two features of a narrative literature review. Often these are, I find, harder to publish, uh, and they're often the preserve of experts in the field, especially in natural sciences. So sometimes people want to hear more your opinion and you're thinking about the literature just because you're an expert and you have a perspective, and that expert opinion is quite valuable. But if you're just starting out, I I find these are very hard to construct. So I'd say these are the most common, but they're also the most difficult because of this lack of built-in structure, they're the hardest to publish, largely because they're not reproducible, and they're often, often they're invited by editors. Um, if you are going to do this kind of literature review, um, you need to be very clear uh about what you're trying to achieve with it and where you're trying to get to. And you need to make sure you build in a structure by uh having a funnel. And if you know where you want to end up in terms of justifying your study's existence, it's much, much harder to get lost. And it makes it clearer because as you start summarizing literature, you can start evaluating it saying, Does this help me justify the need for my study? If not, it's interesting, but it doesn't belong. And um, that will solve one of the biggest problems of this kind of lit review. If you guys have any questions, if you're doing a narrative lit review, let me know in the comments. Just comment narrative. Yep, I'm doing that. Uh, if you don't know what kind of lit review you're doing, hopefully by the end this will be be much clearer. But I'd say the vast majority of you who don't know what type of lit review you're doing are probably doing a narrative literature review. Um, okay, the next kind of most common type really falls into two kinds of categories and they share a lot of similarities is scoping and uh systematic review. These are two separate types, but I lumped them together because they're they're quite similar in practice. And the difference here is that they are going to have built-in structure, and they are going to be reproducible, they're gonna be easier to publish, and they're typically not invited. Um, so it has these features. So these will go so far in the systematic review, um it you you actually have to pre-register your method, like you would do with a trial study. Um, and your your methods have to be incredibly robust. Systematic reviews will often also have something called a formalized quality assessment, um, where you not just evaluate the literature and draw conclusions, you actually show how you've systematically gone through and assessed, well, these studies were weak, these were strong, and and try to balance your conclusions on the basis of the strength that you've estimated, often using a tool uh of the literature. So I like these a lot because they just by following steps, they actually have guidelines and step-by-step protocols. Uh, they force you to follow a funn process just by following the steps that are laid out. Um, that said, if you need something quick and dirty, say your supervisor just wants you to find some gaps, go get familiar with the literature review. Well, here narrative is okay, but you just need a quick and dirty maybe summary uh to get to explaining why you've got a gap. Um, but if you want to publish, these are definitely the way to go. I have a personal bent. I prefer systematic reviews because of the pre-registration. If somebody ever asks, you can turn a systematic review into a scoping review, but you can't go the other way around. And systematic reviews just have a little more gravitas, they're a little more respected. So I always prefer starting there. I've had several researchers, one you can find on my channel. If you go into some testimonials about our programs, uh her name is Nahal, a doctor in Ireland. Um, she started off doing systematic review. Reviewers asked to convert it to scoping. No problem, converted it to scoping during the revision, got published like that. Um, the main difference for them comes with pre-registration, and I won't get into this, you can see this in other videos, and what tool you use to define your topic. Um, by the way, guys, I highly recommend you use tools to define your topic. It just is kind of that extra check. And I find researchers I work with like checklists and gates so they know if they've done it right. Um, but yeah, uh scoping review is going to use something called PCC. Um and uh systematic review is going to use Pico. Don't worry about these outcomes now. Um you can Google them later and you can find them in other videos uh on my channel. Um so then there's there's a third type here that sometimes people ask me, well, what's this? I don't know what this is. And then just not knowing the terms, people get worried about things that are thrown out there that they see or don't know. And they sometimes see something called an umbrella review. And this is a very specific type of review, uh, called a which is basically a review of reviews. Um, so this can be really highly used when there's a dense, dense literature, and there's maybe a lot out there, and maybe there's a bunch of scoping and systematic reviews already, and you want to review those reviews, and that's why it's called an umbrella, because it is funneling in all these different reviews. And and so what's different here is often in your systematic and scoping review, you're unintentionally excluding reviews and only going for original evidence. Umbrella review does the opposite, it only wants the reviews themselves. So it's a review of reviews. Um, I won't get into that. This is a little bit rare, and I don't recommend it. But I want you to be aware of what it is. Um then you've got a fourth kind of miscellaneous mismatch category, and I think people get really confused on this that they sometimes see, where there's lots of quirky terms for things, like there can be a critical review, there can be an integrative review, um, you guys might even come up with some other quirky names. They're much less common. And so if you search, say, take one of the big databases like Web of Science, which is a general repository, and just search for all critical review or all integrative review, you'll see the numbers overall in those databases of what's like the universe of everything being published, is much, much smaller. These are sometimes niche to certain fields. So critical review can sometimes be more in critical theory. Sometimes people say critical review if they really want to emphasize the nature that they're critiquing the literature. Uh, but you should really be critiquing the literature in a narrative or a scoping uh or systematic review anyway. So I don't find critical review says that that much. Same with the thing with integrative review, they want to emphasize that maybe they're integrating dispersed narratives or different fields, but you should be doing that kind of synthesis in your analysis elsewhere. So, what I find is that these are the main types, but you have some other names that are out there, like these, and you probably might be aware of others. Maybe drop those in the chat if I haven't covered one. There's a bunch of these quirky ones that are less common. Um, but typically I find these are actually in structure just a narrative lit review. Now, the second thing we have to understand about the lit reviews that you superimpose here is how you do the analysis itself. So, in a lit review, in a way, you're right, if you're doing a qualitative study, your data are from interviews. Or a quantitative study, you have numerical data, maybe from a survey or some data you've collected. Well, in a lit review, your data are the research articles themselves. So you have kind of two universes to evaluate these articles. And uh guys, I can see my video might be lagging a little bit, but I hope you can hear me. If you're having trouble hearing me, uh do let me know. It's one of the perils of being off-site. But um, you have two universes for your analysis uh to differentiate. And it it basically is kind of like a qualitative, quantitative display. And so one is kind of a qualitative analysis, and another is you're gonna remember what you're doing in the literature review is you're treating your articles as your data, and another is a quantitative analysis, and I clearly can't spell quantitative, you'd be amazed how how difficult until you've taught yourself, even just in front of a whiteboard, just talking and writing at the same time, it's different neuro neurological circuitry, and it doesn't always work. Um, so these are the two kind of buckets, and that's where you get an qualitative analysis. Sometimes you can get a thematic analysis performed of the literature, you can get even a discourse analysis and look for how people talk about different things, the language they use across fields. Um, in the quantitative analysis, you can get lots of different things going on. Uh, you can get something called a meta-analysis where you take different papers, pool them, and actually do your own quantitative analysis of the data. Um, you can do also something called a network analysis. This is common in medicine, where you might say there's studies that compare a treatment A to B and studies that compare a treatment B to C. And now I want to compare A to C with the idea that there's transitivity across them. And this is often used in kind of big clinical comparisons when they say we want to look at the best first-line treatment for depression. We've got all these pairwise comparison studies, and we want to look at uh across the universe of all of them. So different quantitative analyses you can do. Sometimes this is called here for system archives, this is called systematic swim or systematic uh review without meta-analysis, and that is more this kind of narrative synthesis that that's qualitative and and really kind of encodes the difference between the two. Um, but yeah, so sometimes people then get confused in the lit review when they're like, oh, I'm doing a meta-analysis. It's like, well, if you're doing a meta-analysis, you are doing a systematic review and your analysis of the meta-analysis. So you've got two layers. So there's a layer of how did you collect the data for your review, and then how did you analyze it? So there's nothing to say. You can't do a narrative literature review and combine it with a quant analysis or a network analysis. It just would be a little bit quirky and you probably would get destroyed by reviewers. Um, if you're you're trying to be that formalized, but you're not using a uh, I spelled this wrong, this is not reproducible, um, and you're using a not reproducible method, it is kind of problematic to pair narrative literature review up with these types of analyses. So almost always you see narrative literature review paired with a qualitative type of analysis here. Um, and you'll see scoping and systematic review paired with one or the other. Um, and then there's there's other tools out there. Um, this network analysis, I give you the specific meaning that's used in medicine. I I often do there's sometimes bibliometric analyses here that are done that analyze co-citation patterns. I've done some of these myself, I've lost favor them because I don't feel like they create thick insights in the literature review, but you can also, these are also some qualitative tools of literature. You can do networks and analyze who are the key authors in the nodes, um, where in which journals is there the most activity at the moment. I just lay I've done them myself, I just have found that they don't add enough to justify the extra effort. But don't let me deter you from doing that. Sometimes there's a discussion of choosing the right tool for the job that you have. And for the questions that I've personally been asking in our researchers, um, this is something that just complicates the paper without actually adding something really exciting or significant. Um, okay. Yeah, my narrative. Okay, I'm glad you guys can hear me. That's that's the biggest thing. Uh the video is is usually the thing to go go the fastest. So sorry guys, but uh offsite, I wanted to join you uh no matter where I am in the world, if I can. So with that, uh so we've got one here. So Maria asks, what's the difference between a lit review and a narrative review? Exactly. So the the uh basically that traditional narrative lit review is your most common review. If people don't know what kind of lit review they're doing, they're almost always doing a narrative lit review. 90% of the time. And so it really gets confusing because the name, there's two dimensions going on. It's like how are you analyzing the literature, and then what it was the way and setup you're using for defining your study and collecting the literature. And and narrative is basically this one of not following a reproducible method. I'm just gonna kind of Google scholar around and find some stuff and put it together and analyze it uh myself in a narrative way that's not reproducible. Um hope that makes sense, Maria. Um, but thanks for asking. Uh so with that, guys, yeah, we got time for a couple questions. I'll keep the whiteboard up in the background. I'll go through the questions that we got this week. Um I can see binary asked ones here. And Binaria says, for an emerging topic like AI and education, how we do we decide between a scoping review, Prisma-based systematic review, or a critical review? So I think you know my answer here, uh, based on what I said. I I strongly recommend a systematic review. Um strongly recommend a systematic review. Alina asks, case study. Uh case study is not in the world of a lit review. A case study, you're evaluating a specific case. Um so that's that that's not a liter literature review. So a case study often you get returning to the world of medicine, could be a rare patient comes in. Presenting with some particular conditions that you want to describe because that could be of interest to a lot of doctors out there. So you describe that case study. And in the environmental field, later I know you work in the environment, maybe there's a very unique innovative recycling program, and you want to showcase that. And so you did a case study evaluating that program that you think has broad relevance for people who work in the circular economy area that I know you're active in. So that's not a lit review, it's actually an empirical analysis of some form of something that happened in the world, and that's why it's a case study. Um but good questions. Good questions. Uh Funcho, I don't know if you had any questions. I can see we have some other questions about um how to use AI in academic writing and avoid plagiarism and how to choose a good topic. So we'll come back to those guys. If you can be more specific about your questions, that always helps. But Minary, I hope I've answered your question there and you've got some more clarity, uh, as I promised, uh, in making your decision. Um I do see that you mentioned critical review, that often is one that causes people confusion. All right, let me go through the questions we got this week, and uh I'll keep an eye on the chat for whatever you have. Um, but yes, so uh we've got Felix writes. Uh Felix wrote in and says, I need help. I'll copy this in the chat so you guys can see it. He needs help finding a research gap on the role of the central bank in corporate governance and the stability of individual banks. Evidence from the Nigerian banking sector. Okay. Alright, let's think about this for a second. And this is something you're not gonna solve uh on your own, um just ruminating or reflecting. You've got to roll up your sleeves and start reading. So here would be a case where you want to go do a maybe mini literature review for yourself, going out and trying to understand what's been done and what's not been done on this topic. Uh one of the things when you say the gap, so if you go back to a few lives ago, uh we talked about our publishability formula. I just want to recall that for a second. So your publishability formula is going to be a function, it's a multiplicative function. So publishability is a function of the strength of your gap times the value that you can add times the alignment your study has, times the clarity you have, and the fit of the journal. And if any of these things are zero or small, it's like you multiply anything by zero and the publishability is gonna be zero. So if you do everything fantastic, but you submit to a journal, it's just not a fit. Imagine you Alina did a great analysis on the environment, and she submits it to a biomedical engineering journal. It's fantastic, but it's not a fit. Zero publishability there. And what you've done in setting up your topic here on your gap is you've made your gap very small. By doing something and say you're providing this evidence in Nigeria. Well, why do we care about Nigeria? Nigerians care about Nigeria, but typically, if you want to publish in big journals, high-impact journals, it's got to have a broader general relevance. So I worry, already structurally in setting up your topic, you've you've you've taken a gap and set up a value of your study that might be considered marginal. Unless you can describe why maybe Nigeria has a very unique banking system that has some very unique features that maybe other countries can learn from. Now, if you've got that element that others can learn from what Nigeria is doing, then it has broader relevance. Um it's not to say that Nigeria isn't important, it's just this is just part of the publishing game that you've got to be aware of. Um, so in terms of your topic, so you need to know what's the debate here, the role of the central bank in corporate governance. Well, what I know here is there's a lot of discussion on independent central banks that are independent from government decisions, and that that's talked about. But uh I I don't know. So you need to look up the literature and look at this. But this is almost like two questions in one. What's the role in corporate governance and and the stability of individual uh banks? These are kind of different questions. So if you want to see like how does the central bank stabilize individual banks, seems like a different question to me than one dealing with corporate governance. So I would separate those, I would try to get clarity on why Nigeria is important and can maybe answer something that others haven't been able to. And you need to go out and actually uh connect this to the existing literature. So you need to figure out like what's been done before and what's not been done before. So take us right up to the edge of knowledge and figure out what's missing. And the only way you're gonna find that, the only way you're gonna find that is by looking at actual studies on these topics. So to show you that very briefly, what I'd be doing. So I'd be going into Google Scholar and I would be going to impact central bank on corporate governance. Just get a sense of what the the ev evidence is. Um, so here would be a study. I'm already worried because, like, look, this has got nine citations. It doesn't look like there's a very big debate going on here. Um this is what I was worried about. Uh there's I I don't know. You'd have to trace out the mechanisms for me on how the central banks are are affecting corporate governance. My understanding was just more that I'm not an expert in this, I'm not an expert macroeconomist, but they're just setting the interest rates, especially if it's an independent central bank. And sure, that changes the climate of lending for uh corporate actors, but why is that directly engaging with corporate governance? So I think there's some part of the logic here that that's being lost on me, but it's probably clearer to you. So I would encourage you to think that, think that part through. Um, and again, uh you know, if you don't have kind of clarity on what you want to show why you're interested in this, it's gonna be very, very hard to get to the next step of defining your gap and what you want to show, which is really critical for a good topic. Um, okay, I'm gonna take a couple other questions in between as I've got a few others on the list. Uh, we've got a long question here from Mokhtar, who says, I'll try to read this out to you guys. And let me show, it won't show the full thing here, but says, Thank you for your invaluable guidance throughout the PhD journey. Your advice has deeply shaped my pressure research and publishing. Awesome, glad to hear it. As an early career researcher aiming to build a strong high-impact publication record, love that you're doing that. He says, I'm at a crossroads. Should I pursue a prisma-based systematic review to establish scientific career and credibility, or opt for a critical review to argue for the necessity of this interdisciplinary paradigm and material science? Um, well, again, a critical review is just going to be harder to publish. So um I I I always lean to a systematic review because it's just easier and it can accomplish the same things as a critical review. Uh so is there a reason you wouldn't want to do a systematic review? Because I I tend to take that as a default good option just because of its easier publishability, uh, especially for material science. Um, so yeah, you're asking which approach would you recommend an established authority 100% uh systematic review, uh unless you see a lot in your field with critical review on the tin. Because sometimes critical review can be very niche in certain fields, but I haven't seen that necessarily in uh materials science. Um, so especially because some of those lit reviews, like I said, are invited and they're because the editor might know someone senior in the field, or that person's even on the editorial board. Uh, so you just come cold with a lit review, it can sometimes get a tough ride. Uh, my narrow also saying SLR would be the best choice. That's what I think, too. So uh Funcho, Funcho has a great question. So the introduction part of the paper I want to publish will be a narrative review. Excellent. Yes, 100%. That introduction of a paper is typically a narrative review, and it is a strategic argument in your introduction for your study. It is basically you're going to be driving your gap. And so a successful introduction is that same funnel structure of going from the kind of the introduction of why are we having this conversation now? Why is this topic or area so important, to what do we know and don't know on this topic, to kind of gliding right into your research question or hypothesis and what you're gonna do. So very much that that kind of funnel broadening to narrowing to your specific study, so that by the end of it, your study should feel almost inevitable. Like it needs to come into existence. That's how your reviewer should feel reading it, that's how your editor should feel reading it. It is a strategic argument in the introduction of your paper for the existence of your paper. So, yep, 100%. Um, okay. We've got another uh material science researcher asking the same question uh uh uh as Mokdar here. Uh no, I think this is Mokhtar asking again in a different light. But uh yeah, Mokhtar, I answered that just a moment ago. Thanks for the question, though. It's it's a good one. And Fun Show says, yeah, yeah, 100%, Funcho. So really glad that you you asked that. Um I think also, right, when people do the lit review of their paper, they're not asking which type is just the lit review for the paper. But it does help to know what type of review you're doing to make sure you you build in the structure yourself and you know the purpose of that lit review, you know where you want to end up so you don't get lost. Um yeah, so briefly again, so this is what what we went over, um, John. So uh the core differences is the scoping review is gonna have a built-in structure, it's gonna be reproducible, it'll be easier to publish. Um, it won't have a quality assessment, that will be like a systematic review. But these these are two in the structured category. Uh, scoping review is gonna follow this PCC model. If you want to read more about this, uh you just Google PCC scoping review, you're gonna define here your topic using the population concept and context. Uh and see it here, it's saying it replaces Pico. I I still prefer uh systematic reviews for the reasons I said before, that you can always convert systematic review to scoping, but can't go the other way around. Um, but both of these are great because of the built-in built-in structure. The narrative review is is just harder to publish. So the way I would think about this for your masters, if say your masters is just the deliverable of your master's thesis is the lit review, then I would make it a scoping review. If though you're planning to say go do a data analysis or something else, I would do a narrative literature review, which follows the funnel I talked about. If you just jumped on, rewatch this part of the video, um, and just kind of delivers, like I was saying to Funcho a moment ago, the strategic argument here for why your study needs to exist, for why that empirical part of your master's needs to exist. Um, so at the master's level, that's that's how I would think about that that trade-off there. Uh John, I hope that makes sense. Let me let me know if you have a follow-up question. Um, Veronica asks, uh, greetings, prof, how can we pull out literature review and applied linguistics and language studies? Sometimes we're stuck as to review to use. I think you mean you you don't know which review to use. So uh these lit reviews, think about it. The analysis inside the literature review, qualitative or quantitative, doesn't matter which field you're in. Those are kind of your broad tools for analyzing literature. It's gonna fall in one of those two camps. Same thing. Like the the tool you use, are you gonna go look in Google Scholar, basically? You're gonna be in narrative review land. Are you gonna use a formal search of databases? You're gonna probably be in a scoping or systematic review territory. Are you gonna be looking at just existing reviews? You're gonna be in an umbrella review care territory. But that is field agnostic. Right? So the type of review really, I think you gotta step back for a second, Veronica, and it's not which studies you're looking at is gonna necessarily dictate the review. Um, I would put it as more do you want to publish this review? Are you using this review just for your own knowledge? Is it is it just a quick review at the introduction of a paper to justify the existence of your article? Why get get real clearly, why are you doing what is this review for in your research journey? Um Does a systematic review apply if you have to do data analysis? Uh good question, uh, Hamza12456. So if you want to do data analysis, is the data analysis you're wanting to do of the articles themselves? Um, but if you have an actual data analysis, I wouldn't mix article types here. I wouldn't have a systematic review and then do an empirical evaluation of something innovative. I would just have a traditional narrative lit review at the front end of your paper and then have your empirical data analysis component of the paper. Unless you're doing some kind of quantitative analysis of the literature and you're doing the review to collect the articles, using it to create a data set, uh, and then your data analysis is based on that article data set you constructed. That's more meta-analysis or one of the other types or a bibliometric analysis, one of those things we we carved out a moment ago. Um, and then then, yes, systematic literature review makes sense. Uh Veronica's saying, like, that makes sense. Cool. Um, please, please that helps. And Elena's saying, Veronica, thanks for asking that question. Guys, I love you asking these questions because just think about that. Elena is a good example. There are other people who have these questions, but might be too scared to ask. And so, by I'm not saying you you are Elena at all, but I'm just saying a lot of people out there are sometimes just a bit scared to ask questions. That's totally okay. It can be a bit of imposter syndrome. You feel like, oh, people are gonna see I don't know stuff. Well, you have to lean into not knowing stuff. That's where you're doing this training. And in fact, the whole enterprise of research is not knowing stuff, and you're doing the research to figure it out. So you actually have to get very comfortable with not knowing. Uh that that's kind of the name of the game. Um, so that can feel very discomforting, if especially when you're starting out, because you came from a world of grades, there's a right or wrong answer, and how you perform is you personally being judged. Uh and it's like everything changes once you start start doing research from like how you proceed to the rule book to how you get evaluated. Um, and so um that that means also kind of updating how you respond to feedback. Um, don't take it so personally, treat it like a gift. Um, realize that when you feel imposter syndrome, you're being stretched, you're actually growing, and that's a good feeling. It's like when you go to the gym, yeah, it's painful to train, um, but you're growing and you get stronger, and and in time you get addicted to that feeling because you feel really great. Uh and research is like that. Uh, so just lean into that growth and lean into that discomfort because I I love things that are a little bit uncomfortable because that also tells me not a lot of people are gonna be able to do it. Um, so intrinsically, it can often have more value that you've been able to achieve something that's hard that other people see, try, and run away from. So uh yeah, just treat it like the challenge that it is and lean into it. Okay, um, we take a couple other questions uh that I had from the list. So Joshua asks for feedback on research, cover letters, and quantitative or qualitative analyses. I mean, uh, okay, how much time do we have, Joshua? Great, great question, but guys, keep the questions focused for me. But let me point to you where where you can get this. So, of course, guys, I'm biased. I love our research community because we have dedicated quant drop-in sessions, we have dedicated qualitative drop-in sessions, workshops. Actually, you know what? Let me just show it to you. Um I mean, we've got something going on um going on pretty much uh pretty much every week here um in all these areas. But let me just pull this up so you guys can see uh what I'm talking about. And uh I I really think uh you guys love this and give you kind of a map micro tour. Uh so here's where we are. Okay, here's where our community lives. Small but growing, 224 members, and you can see if you head over to our workshops, we got stuff going on uh all the time. So uh we had a a quant workshop, dedicated stuff on quant. Um next week we had a really fantastic editing workshop uh with Peter. Whoops, we've got systematic review workshop, and it's everybody working on systematic reviews. Um next week. Let me head over here. Two sex next week. We've got lined up go on to the next week. Okay, this is getting buggy. Go to the next week. We've got a really great uh qualitative workshop that I'm I'm excited about. So, all right, what's great is it just closes the feedback loop. So you get feedback a whole lot faster. And and I found that feedback really is critical, but feedback's not alone, you need an actual system. So, for all things, like if you're getting stuck on, well, I don't know how to write a cover letter. Well, uh take one example. We have a really nice navigating submission process, shows you how to live submit. Um, this is just one example, help you avoid scam journals. Um, really good cover letter guide and template in our videos of training showing you how to write good cover letters in your field to optimize the chances that you don't get desk rejected. So I can't possibly go through all this now, but I'd encourage you to just check this out. Um, it's it's just a quick trial. I'll put a link here. $10 uh quick trial. Um, it can cancel anytime and see see if it's a good fit for you. Um, would love to see you on the inside. Uh so yeah, I can't answer all that here, but I've got a lot of really valuable uh free resources. It's just here that there's actual hosting costs that we gotta cover, even though it runs on a uh non-profit basis. So yeah, check it out here. Um other questions I've got lined up this week. Umsman has a project thesis. Okay, this this looks like this could be quite challenging. Usman says, please the screen is not really clear. Oh, okay. Sorry about that. Uh Joshua, I could uh maybe zoom in a little bit more. I'll go to this next one here. Umsman says he's doing a project thesis for BA mission. The topic is theological studies of factors influencing sustainability of SIM mission field after missionary withdrawal, a legacy of the lisky mission field in Gigawa. Um, so um well, I mean, it's really hard to understand what's going on from your title. This is hard for me to make sense out of, honestly. Uh but for the BA, usually I just do I keep it very, very simple. Um now's not the time to do huge project. You want to do something as contained if it's an undergrad thesis. My undergrad thesis was just a lit review. I think mine back in the day, it was I was just looking at some of the causes of homelessness, or I think it was the the impact of homelessness on mental health, and I was just summarizing the literature. It sounds like you're trying to do a case study here, but um I don't know why a theological study of factors influencing sustainability and why missionary withdrawal is important. And I don't know what the Beliski mission field is in Chico, why it just just too much stuff going on here. I I would just even just looking at this, make it so much simpler. Just look at look at maybe maybe you want to look at why the missionaries withdrew and from this the this mission and How can you better stabilize missions? I don't know. But I think you got too much going on, is my initial reaction here. Um, yeah. Uh yeah, guys, if there's something Joshua, if there's something here specific that you wanted to see, um, let me know and I'll go back and uh show you that. Um asks, what if I have a PhD thesis with a narrative lit review, but now I want to publish an article based on it? How should I change my narrative lit review into a systematic one? That's really tough. You almost have to redo the whole study. So that is unfortunate. I would honestly I I I wouldn't. Don't want to deliver frustrating news, but um you can't really reverse engineer that effectively. Whoops. Sorry about that, guys. I got disconnected for a brief moment there. Hope you're still with me. Um but yeah, uh Ellen, I was just saying you can't really reverse engineer that. I know that's frustrating, and I don't like to deliver that news, but you you basically, in a systematic review, are gonna have here's I searched these databases with these criteria, and I got these articles so that anybody could follow the steps and get those articles. There's not really a way to reverse engineer a formalized search and get exactly the final set of articles in your set. I just don't think it's gonna work. Uh so now I think I would just, I mean, now the cool thing is you've done the analysis already. I would just start over and do the search, and maybe your analysis will come out the same. You'll get a broadly simpler set of articles, maybe you'll get a few more. Um, I find often researchers are surprised when they get out of a filter bubble, and when you're searching Google Scholar, you are in a filter bubble. Um, when you get out of that, you will find articles you didn't even know existed. You'll often tap things in other adjacent fields you didn't even think to search. Um, when I say filter bubble, it's that the algorithms of Google Art are producing things that it thinks you're gonna like based on your past search histories. So you're systematically being blinded to stuff that might be highly relevant, even though it is distant from what you've looked at before. So um, yeah, hate to deliver bad news for you, but I I you you could try to publish it as narrative lit review, but like I said, in general, it's not impossible, it's just harder to do, um, in my experience. Uh, okay. I know. Uh sorry, Ellen, I'm glad you asked that. Uh, that it's really helpful for people who are just starting out now. See, I would go the other way. So I would have done systematic review first, and then if they they insist on you having a narrative review, well, you can always turn that into a narrative review quite easily. You you you've done it, you have the funn structure there. You just had a different tool for getting the literature review in. So you can turn systematic review into something else. You just can't go the other way. Um so oh Mark Tav, don't worry about asking twice, it's okay. Um says you got a practical question. Um well, the quality assessment tools sometimes there aren't quality assessment tools out there. Insider Secret here, I don't in the first pass of submitting to journals, usually I don't actually include a quality assessment. Even though I know the reviewers are probably gonna ask for one. There's a couple reasons I do that. Um so one of the reasons I don't put a quality assessment in initially is that you're gonna have to add about another month to the process, which we will find start to finish it takes about three months, investing about five to ten hours a week. And that extra month is just enough to where it can get overwhelming, and that I find sometimes people drop off and never get it done. So there's that pragmatic component. The second is that you sometimes in a paper want to leave something obvious out that's not a big deal, so the reviewers can just be like, ah, you need to do a quality assessment, and then they feel like they're smart, they came up with something, but it's like great. It's almost like I just kind of left this little hole here, and you could walk into this hole. Imagine if that hole was not there, then they're gonna dig around and try to find other holes that are more annoying to deal with. So there's that. Usually I find they're not gonna reject it just because you didn't do a quality assessment. Because they know they're gonna reject when they think, oh, this is really bad. But if they say, Oh, you need a quality assessment, they know, well, you can just do that. The third reason is because I've seen this happen. They do a quality assessment with one tool, and then the reviewer happens to love a different tool and says, Well, I want you to do it with that tool. And you end up having to do the quality assessment over again. So you might as well just wait if you get a quirky reviewer to see which tool they want you to use. So for those three reasons, I don't do it. Even though I'd say about 70% of the time the reviewers ask for it. And that's also because a lot of them are using AI to do peer reviews now, and the AI spots it, and it's like, oh well, the systematic review has to have a quality assessment. So they ask for it, even if it doesn't necessarily add very much. I guess that's the other component. It usually doesn't add much, it's kind of a box-ticking thing. But um, if you don't have a tool off the shelf, sometimes you just make one. Um, you make one. Uh you just say these are criteria of good quality studies in um physical models and look for some somebody else who said this is what makes good model robustness, this is what makes good reproducibility, and uh do some tick boxes around that. So you could invent something. Um Joshua says, general view, really interested in research as a young professional. Yeah, um again, I'd encourage you to check us out. There's others out there, but uh, we've got a complete ecosystem and a lot of research groups you can join. Uh so yeah, check us out. Um again, uh not really anything anything to lose. Um see if we're a good fit and you like the way that we approach research. Uh, I mean you can see kind of my ethos and my approach, and um, you know, you'll find naturally you gravitate some to some people of different styles and different systems. Um, that's totally okay. Um, but I just want you to be getting kind of the support you need to to thrive, whether from us or from someone else. Um, you have a Chitty says, I have a project thesis using discrete ecents. I I don't really know what your question is, guys. Try to ask me a focused question. I I do tend to be quite liberal and want to respond to everybody if I can. I get a lot of questions coming through in the chat, but um do let me know. I'm gonna go to earlier in the chat uh where I got a question here um about using AI in academic writing to avoid uh plagiarism. Um this is a good one. This is something that's provoking a lot of anxiety, and I don't think it needs to provoke that much anxiety. Um look, guys, just declare how you used AI. Um obviously don't use AI for references. Um, make sure you're heavy on citations, but if you're worried about it, just cite it. Then you're on the side of angels, and that's allowed. Like Elsevier's guidelines for publishing, as with many other journal families, are totally okay with it, as long as you haven't had AI do the original parts. But you should just be using AI anyway to maybe edit your your language lightly. So don't have AI draft large blocks of text for you. That's not a great idea. Um that said, you can use AI to say, hey, help me cut words, help me say this in a more in a leaner way, or um get it, you can get it to edit writing you've already done, and that's fine. Watch it closely, make sure it has not deviated from the precise scientific meaning. It does that a lot. I have some other videos on my channel where I show how AI edits will actually change the scientific meaning in subtle ways. So you really need to check that any anything that AI has edited or touched has not deviated from what you wanted to say. Um English isn't your first language, I know that can sometimes be hard, uh, but AI really has been a game changer for non-native English speakers in its ability to produce better written text. But still, if you I highly encourage you to do the first pass, and again, coming back to it, happily repeating myself, just cite, err on the side of transparency of how you've used AI, and you'll be fine. Israt. So I'll give you a very brief overview of how to choose a good topic. So first you need to get in the right topic neighborhood. The example we had before about the Nigerian banks, it was kind of in two topic neighborhoods, and so I was encouraging it to pick one. That's phase one. And so usually you want to look for something where there's a good debate, and then turning back to that Nigerian example, I didn't see a lot of citations, I didn't see signs of a healthy debate, so I didn't love it. Um, you want to make sure it's something feasible, you already have some background knowledge, or you can get that knowledge very quickly. Um, you can do a topic, you can do something you're not setting yourself up for a randomized controlled trial that's gonna take a decade, right? Choose something that you can actually achieve. Um, and something you're passionate about. So that's our convergence method. You want to get in that sweet spot. That's phase one of choosing your topic. Phase two is getting more fine-grained, and you need to, and again, I've got a live session just a couple weeks back. Um, look for it on my channel where I went over this in detail. But you then you need to make sure you're not duplicating something that's already been done, or duplication test. You need to further forecast your impact in a more granular way, like I've done, and you need to find specifically this idea of a conceptual nearest neighbor paper. That's the paper that is the closest to yours, and that's your benchmark for calibrating. This paper got us to here, that is the edge of the literature, and from that paper, my whole idea of my topic is to get us to here. I do recommend running your topic through one of the tools, like a Pico tool, just to make sure it's crisp and well defined and very, very clear. Um, I haven't done that today because that's not really the theme. I wanted to help you guys navigate uh the confusing array of literature reviews that's out there. And uh and I hope that makes sense. And uh exactly, uharegis nailed it, AI is a tool, not in the driving seat. Yep, you are at the AI accelerates, um, but you gotta steer. And so if you are going the wrong direction, AI is gonna get to you there faster. That's why AI lowers the cost of being wrong faster than it lowers the cost of being right, and I see people getting into huge messes. It creates system problems because it bypasses the you go so fast, you zoom past the normal error correction and friction you would have early on, and then you wake up and you find yourself three months into a project that's completely unviable. That's one of the AI failure modes. Um, and you can see some more videos on my channel about common AI failure modes that I want you guys to avoid. Um, you know, uh Chitty discussion follows a common template. Um, check out I've got a how to write a perfect discussion in my how to write a paper playlist on my channel. So check that out. It'll show you the ingredients for the discussion discussion section of paper as well as discussion section of uh a discussion chapter of a thesis. It'll have the same ingredients, so check that out. And um Joshua says, some paraphrasing tool is seen as AI content. What's the way forward? So I've got a great video on my channel on how to paraphrase with AI. I show you two methods that work really well and will keep you on the side of angels. So um, yeah, check that out. Uh any you can do it with any LLM, but just follow the guidelines I have on that video of uh basically I can't remember the title now, something like how to paraphrase with AI. But um guys, uh fun session. Thanks for bearing with my connection. I I decided to, even with bad connection, I did not want to miss you every Friday at this time consistently. We're here. If you made it to the end and you do want to participate yourself, I would encourage you to submit a video question to us. I love video questions because I can just better understand, and so can people watching on uh what your your question is, what you want help with. You can also upload a research document for me to look at and provide feedback on. If you have your PICO model for your topic, send it in. If you have a draft systematic review and you want me to look at a section, send that in. Even if it's messy, I like messy stuff because I can see through the mess to see diamonds in the rough. Uh that cliche is really true. I'm used to looking at a lot of messy drafts. Everybody starts in that place. That's the whole process of science is bringing order to disorder. You go from a messy state of the way we think about the world to getting clarity and order. It's a great feeling uh when you get that in place. So submit your video question. Um, if you are interested in working with us, I've got another QR code at the top. It'll help find which program is right for you and show you a bit how we think about research. And if that resonates with you, um would love to see you on board. Um, and with that, guys, uh I wish you all a very good weekend. Um glad, Emmy, uh, that uh you got some nuggets and takeaways. That's great. Uh uh Joshua says send the link to the videos. They're all on my channel. Um, just go to my channel and you can look at the playlist tab. So YouTube, just go YouTube, put my name, Professor David Stuckler, and uh then you'll you can see the lives and you can see the playlists and uh ton of ton of value there. Uh ton of value and try to give you 100% free what other people would want you to pay for. Um so uh yeah, Mock Char, that's a great question. I think we'll do a dedicated session uh coming up here on using AI and academic writing. But if you want to see my my latest thinking on that, you can see that uh on my channel. Um guys, thanks for sharing your Friday afternoon with me. This is your time, and I will see you all same place, same time next week.