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Expand your running knowledge, identify running misconceptions and become a faster, healthier, SMARTER runner. Let Brodie Sharpe become your new running guide as he teaches you powerful injury insights from his many years as a physiotherapist while also interviewing the best running gurus in the world. This is ideal for injured runners & runners looking for injury prevention and elevated performance. So, take full advantage by starting at season 1 where Brodie teaches you THE TOP PRINCIPLES TO OVERCOME ANY RUNNING INJURY and let’s begin your run smarter journey.
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On today's episode, using data to prevent injuries with Dr. Bradley Neal. Welcome to the podcast, helping you train, rehab and run smarter. When I first started running in my 20s, I knew it would be something I'd be passionate about for the rest of my life. But, unfortunately, developing injury after injury disrupted my progress and left me under-trained at the start line on race day. Even with my knowledge as a physio, I still fell victim to the vicious injury cycle and when searching for answers, struggled to decipher between common running myths and evidence-based guidance. That's what this podcast is here to help you with. So join me as a run smarter scholar and let's break the injury cycle by raising your running IQ and achieving running feats you never thought possible. Welcome back Run Smarter Scholars. We have Brad Neal on the podcast today because a paper has emerged a couple of weeks ago and the title was Using Wearable Technology Data to Explain Recreational Running Injury, a prospective longitudinal feasible study, which Brad will talk about exactly what that means in a second. But Brad is a great academic running researcher, mainly specializing in patellofemoral pain or runner's knee. but has branched out and collaborated with a whole bunch of researchers to come up with this study, gathering data to see if we can prevent running injuries. And it's a fascinating conversation. Like I said, he spent a lot of time with PFP, patellofemoral pain, and has a website team pfp.com and also the same handle on Instagram. His Twitter is Dr. Brad Neal. And he helps clinicians treat this condition, but also helps with patients or people who have this condition to better understand it. So if you want to check out those socials, they'll be in the show notes and he'll explain at the end of this interview exactly a bit more detail. But today we're going to discuss this paper and exactly what you can do, what data, whether you have some wearable technologies or not to reduce your risk of injury. I was very interested in the results of this study. So I thought I would reach out to Brad and I was very grateful that he came on to have a chat. So let's take it away. Brad, thank you very much for joining me on the podcast today. No pleasure. Thanks to be asked. It's a, it's been a while since I've done one. So, uh, yeah, thanks for having me. Excellent. Let's shake off the cobwebs with an easy one then. Um, I'd like to dive into your career. And I'm particularly interested in researchers and how they get involved in this sort of field. So would you mind just bring us up to speed of what, how your career has developed into where it is now? Yeah, sure. So I'm a, I'm a physiotherapist. Um, I qualified back in 2006. So I've been a, I've been a physio for a fair while. Um, how did I end up as a researcher? Uh, kind of. Very organic journey really. Possibly slightly unusual in that I went to university on a swim scholarship. So when I finished my undergrad, I wasn't quite ready to stop swimming. I thought I had a couple of extra years in me and needed to keep studying to keep my funding. So rather than just do a sort of start a throwaway second BSc or something that I was never gonna finish, I asked the university if I could start a masters. And they said, yes, but you need to start with the research modules because you've got no clinical experience. So we don't really want you to start on the clinical modules. So I then went on and did master's level research methods and my master's dissertation pretty quickly after graduating. So I've kind of involved in research very early on in my postgrad career. I then did something fairly standard, I would say. I went and worked in the NHS for a couple of years. Once I stopped swimming, I did some elite sports stuff, worked in rugby, worked in football, or soccer, as you guys would call it. Did a bit of swimming and athletics and stuff, and kind of didn't love the elite sport side of things as much as I thought I would. Knew I'd always be sort of MSK focused, so after a couple of years... in the NHS decided to move into private practice, did a couple of years floating around here and there and then ended up at Pure Sports Medicine, London's biggest multidisciplinary sports medicine clinic and worked there for the next 10 years. Pure's got a real research culture. Dr. Christian Barton, who I'm sure you're aware of, was working there at the moment. We started working together, pretty good friends and started working on a couple of projects. And after a couple of years, it seemed logical to maybe take on a PhD. So I did that at Queen Mary University of London in the Centre of Sport and Exercise Medicine there where Christian was also working. And how did I end up looking at patellofemoral pain? Again, I haven't really got a particularly exciting answer, rather than the fact that I always liked lower limb stuff. you know, knees were interesting clinically and that's kind of where I landed. And, you know, at the time, it wasn't a run on myself, but kind of naturally started looking into running and biomechanics. You know, that was my real, my real interest at the start of my PhD. I, I liked going into the lab and sticking markers on people and, and kind of seeing, seeing how people move and, and linking some of those variables to, to patellofemoral pain. And yeah, kind of I've ended up moving a little bit further away from biomechanics now, but yeah, wrap that up. Did a couple of years at QM as a postdoc and then probably similar to lots of people. I think COVID hit and you're kind of sitting at home wondering what to do with yourself. And I'd been flirting with going into academia full-time for a while, but had always been a bit apprehensive of... what would happen if I stopped seeing patients? Would I suddenly become very out of date and how much would I miss it? And yeah, COVID hit, couldn't see patients for a while, kind of did a bit more academic work, realized actually I'm enjoying this a lot. And it was a difficult wrench because I worked for Pure for 10 years and loved the team there and the people that started the company and found it really hard to walk away. But the opportunity... came up to take a full-time role at Essex with a research contract, which I was after and thought, let's dive in and see where we go. Excellent, mate. Yeah. And I know most of your work is around patellofemoral pain, but the one that sort of got a lot of my interest a couple of weeks ago was this recent study around, you know, wearables and talking about running related injuries. How did that topic come about? And did you, were you the one who initially like, brought up the topic? Like how did the whole topic eventuate? So I've always had a big interest in running from a from a research perspective. You know, like I said, at the start of my PhD, I wasn't a runner at all. And I was one of those rare beasts that research running but didn't actually care at all about doing it myself. And have actually now been a consistent runner for the last five years, I managed to to sustain a fairly nasty cervical radiculopathy about five years ago and kind of worked my way back to fitness with walking and then kind of slowly started a start to run program because I couldn't really do much else and kind of now run quite regularly because it's a fairly easy hassle-free way of keeping fit regardless of what you're up to. So my PhD thesis was fairly heavily centered around runners, the actual titles. of my thesis is escaping me at the moment because it's quite long when it was something like the role of biomechanics in the development persistence and management of patellofemoral pain in recreational runners. So pretty much everything I did in my PhD was with that kind of running slant. But I've always had a particular interest in why things start. I've always been a bit of a closet epidemiologist. So I've always looked at running as a real challenge in the... We know it's good for us, but it also comes with a very high potential for musculoskeletal injury. So I've always had that interest in trying to unpick why runners get injured. So that was one of my aspirations when I went to the University of Essex full time in my interview and my sort of proposal for the research contract. a big part of it was at that sort of start end of musculoskeletal conditions. Why do people develop pain? Why do runners become injured, et cetera? And I'd always had kind of the aspiration of making it a lab study, you know, and bringing people into our biomechanics lab and collecting this big suite of baseline data and then following people for... for a prolonged period, but fairly quickly, the logistics of running a study like that with the numbers that you need, you struggle. And that's probably partly why we still have a very poor understanding of why runners get injured, whether you're looking through a biomechanics lens or a metabolic lens or a training load lens, it's difficult to get a number of people, a critical mass for such a study. So again, it was a bit of a COVID conversation really. I ended up having a chat with, a guy called Jeff Moreno who's based out in the States who runs a company called Dash LX, who are a sort of GPS inertial measurement unit, a sort of data mining company from a performance and injury standpoint. Jeff's a physio by background. And we had a chat about possibly running that type of study using wearable devices. And then I reached out to all of the author colleagues that are on the paper. So Izzy Moore. who's at Cardiff, who I think you've had on as a guest and one of her post-docs, Molly McCarthy-Ryan, some colleagues that I know well out in the States, Max Paquette, Alison Gruber, Chris Napier, and then a good friend, Chris Brammer up in Salford as well and said, look, why don't we get together and kind of have a bit of an international collaboration and see what we can do. And it's gone from there really. Wow. As soon as I looked at the paper, I'm like, such a juggernaut of authors listed on this paper. Like it's a couple of had, I've had Chris Bramber on the podcast before as well. I'm talking about like, you know, he's done a paper on the pathological traits of injured runners versus non injured runners and some really exciting stuff with his work. And yeah, just read through the list. I'm like, this is. great paper, you've really recruited and collaborated with a lot of people from all over the world as well, which is really impressive. And so you managed to get a sort of data company to sort of, you know, get this, a whole bunch of these metrics to then piece together. What was the proposal or what were you expecting to find? What was the particular design and that sort of stuff? So the first thing is that it's a feasibility design, right? So the, I'll use a really cheesy pun with this type of study, or with this type of research question, you mustn't try and run before you can walk, right? We're doing something relatively novel. We're using a technology that hasn't been particularly well explored from a research standpoint. So the most important thing was to determine, is this a feasible method? And that's relatively dry and boring, but ultimately it's about Can we recruit enough people in a timeline that would mean a large study could be done within an acceptable time window? Are people accepting of the method? So will they sign up? Will they link their device? Will they provide us with data that we're looking for? Will they then be adherent to the method? Can we follow them for the period of time that we want to follow them for? And do we not lose too many people? And then can we collect adequate data? So how much data, with any study, there's data loss, right? Whether I'm bringing you into my lab or whether I'm mining stuff from your watch, there will be a degree of data loss, data corruption. Can we keep that sort of within the minimum threshold that we consider to be acceptable? So it was a primary feasibility study, which is a bit dull for some people, but because we were collecting a variety of other variables, we also... wanted to have a look at which of these variables appear to be associated with injury. So that's the other key point. This is what we call a prospective cohort study. So everyone in this study is pain-free at baseline. They're uninjured as they enter the study. We follow them for a period of time. And then at a certain point, they either become an injured runner or they remain a healthy runner up to and including the 12-week time point where we... where we cut things off. So that allowed us to have a healthy group and an injured group, and then we could make comparisons between those groups for all of these variables. And whilst we found a variable that appears to link to injury and several variables that don't appear to link to injury, there needs to be a fair degree of caution with that because the number of people we recruited was relative to our boring feasibility questions more so than genuinely answering the question. It does give us now an idea of what variables we should include when we run this study at scale. You know, if we're now going to do this with 1500 runners instead of 150 runners, there's no way we can collect all those variables. So it steers us in the direction of which one should we look at effectively. So they were the two aims. Is this feasible and what stuff should we look at? If you were to say, Even before this feasibility study, if you were to try and guess what the outcome might be, if you gather all this training data and all these metrics, um, and try to link injury, uh, what would you expect to find? Um, I mean, in, in terms of a, of a hypothesis. What would we expect to find? Or like your guess, like if you were to do this study and say, I'm going to do this study and gather these from 150 runners and see if there's any links to injury, like you personally, before doing this with the knowledge that you had prior, would you make any assumptions or guess as to what you think might emerge? Yeah, I think I would in the same way that I think we all would, right? It makes sense to me that it would link to running. So, you know, how many more systematic reviews do we need where someone says the biggest risk factor for injury for running injury is running right if you don't run you don't get a running injury that the biggest risk factor is running and having had one before so it makes sense to me that it that it's relative to either how you're running how much running you're doing whether that's distance whether that's effort whether it's whether it's something else it makes sense to me that it's how you're running and how much you're running. And I think those things interact. You know, I'm not, I've moved away from thinking that biomechanics can explain lots about why people get injured or why runners remain injured, remain in pain, but I don't think we can put biomechanics to bed in the same way that I think metabolic and training load variables are likely to explain more, but I don't think it explains. everything because the elite of the elite often do lots of running and don't break down for various reasons. So I think it interacts. I'm not surprised that... So we included as an example, we included mental well-being, sleep and intrinsic motivation, primarily as a very exploratory look. You know, I hear so often whether it's talking to colleagues, clinicians, at conferences, etc. people talk with real confidence around, you're in pain because you don't sleep well or your injury came on because you don't sleep well. I've never been sold on that. I'm fairly comfortable with how I think those variables can moderate pain. And if you have a pain state and then you're stressed and you're sleeping poorly and all those things, it makes sense to me that can moderate pain. I would use the analogy with a patient of, It's like plugging yourself into an amplifier. These variables increase the volume, right? But I've never been overly sold on their ability to cause injury, so I'm not surprised. They wouldn't have been on my list, but they're in there because so many people talk with great confidence that they do lead to injury, so we thought we'd have a look. So yeah, the very long-winded answer to a question is. For me, if I'd have guessed it would have been either how much running someone's doing and how they're actually running. Excellent. And obviously, like you said, we interpret these results with a little bit of caution because it is a smaller sample size and just a feasibility study. But what did, what conclusions did you come to? First of all, with the feasibility of it all, and then with the results in relation to injury. Yeah, so the feasibility stuff, we satisfied fairly comfortably, which was really pleasing. We recruited, we got 149 participants in 47 days. It really wasn't difficult to get people to participate in this study. All we really did was put it out there through our various social media networks and lots of... lots of pain-free recreational runners sort of jumped on board, which was great. So we recruited people really fast. So, you know, if we think about needing to get to my back of a napkin sample size calculation of over a thousand, we should hopefully be able to get there within 12 months, which is a sort of feasible timeframe to run this at scale. Pretty much everyone was happy to sign up for a Dash LX account. We got 89% acceptance. Adherence was slightly lower, 70%, so of the 133 that came into the study, we ended up retaining, where's my flow diagram? We retained 93 of them, so we lost 40 to follow up. That was primarily people just not engaging with our. weekly injury surveillance email. So once you enrolled in the study, you completed your first week of surveillance. We then sent you an email with a personalized link to a Qualtrics questionnaire that asked the question, are you running with any pain or not? And then depending on how you answered that question, we asked some further questions to determine, now I think you have developed a running injury or no, actually you appear to be a bit sore, but don't get me our definition for injury. Some people just didn't engage in that at all. Whether that's emails going into spam accounts or people thinking actually this is a bit more arduous than what I thought, that was the main reason we lost people. We lost a few people because they didn't respond for a few weeks and then said, hey, I'm injured. So we excluded those participants because if you've ignored us in week one, week two, week three, and then say you've developed an injury, is that a valid account? Have you been injured for that entire time and just haven't responded? So we were quite... stringent with that side of stuff, but 70% is still an acceptable number. And then we had really low data loss. So every participant completed their PROMs. We lost no PROM data whatsoever, and we lost 13% of our IMU GPS data. So all the feasibility outcomes were satisfied. The next thing to say would be that our incidence rate, so the number of runners that developed an injury was actually pretty low. So of the 86 participants, 21 developed an injury. These people were doing a lot of running to give you some figures. The male participants, so 55 of the participants were male. The average weekly distance was 47K. And the female participant's slightly lower, but still pretty high, 36K. So they're doing a lot of running week to week. So whilst 21 of them developed an injury, that equates to 0.46 injuries per thousand kilometres of running. So our incidence rate was a bit lower than what we would have expected and certainly compared to some other studies. Fairly standard breakdown of injury sites, as you would expect. The most common site of injury was the foot and ankle, followed by the hip and the knee. But there didn't appear to be a huge amount of patella femoral pain, interestingly. Whilst we obviously didn't diagnose these patients, the questionnaire did ask some sort of sites of pain and onset and that sort of thing But it would appear very few of these participants develop PFP. So given that we nicknamed it runners knee And I think I think we can explain that slightly by the by the cohort which we can we can get on to but yeah relatively low injury rate and then of all those variables the variable that demonstrated an indication of significance, a variable that may be associated with why runners get injured, is acute load by effort. So the way that's calculated, I would suspect most of your audience are familiar with the acute chronic workload ratio, where we take the average of the previous four weeks and divide that by the sum of the previous week to give us that ratio. we broke that up a little bit and we had chronic load and acute load. And we also did that by distance and effort. So hopefully acute and chronic load by distance is relatively straightforward. It's purely to do with how many kilometers you've run in either the previous week or the four weeks preceding that. We also had the same variables, but by effort. And that was calculated. So it's a proprietary variable that Dash have developed. So it's a unitless variable which makes it slightly difficult to interpret. But ultimately it's relative to something called critical power, which is effectively, and please remember I'm not an exercise physiologist, so if I give a bastardized example of what critical power is, I'm happy for any physiologist to call me out, but it's effectively a bit like your lactate threshold. So it's relative to... how much power you produce every second of a single run workout taken as an average. And that's fed into this acute load by effort calculation. So it's critical power divided by total power, which gives us a threshold. In really simple terms, it's a metric of how hard you're working. And acute load by effort was significantly higher in the injured group than than the uninjured group. Now, when we say significantly, remember we're basing that purely on a mean difference between the groups and the confidence intervals around that difference, so the variance of the difference. When confidence intervals don't cross zero, so when both confidence intervals are either positive or negative, depending on the directionality, that gives us an indication of significance. So we're not saying this variable is why runners get injured. but it's the start of a journey that would make us think this appears to be strongly associated with why runners develop an injury. Let's keep digging at it basically. So how hard runners push themselves in the previous week was the only variable that seemed to track with injury development, which I think is super interesting, because we have these. We have these kind of rudimentary rules in clinical practice, don't we, around the rule of 10% and don't progress by more than 10% each week. And I suspect most people are thinking really heavily about distance when it comes to that sort of thing. But actually, increasing distance, if you're keeping your effort low, doesn't appear to be a big problem based on what we've found. Whereas if you suddenly push your effort and how best to measure that effort is the kind of next. challenging question, that's the bit that runners should be careful with. But all the other stuff, like how well you sleep, your mental wellbeing stay, your intrinsic motivation to run, your step rate, your contact time, all these things that you know, you hear about none of them showed any indication that they were associated with why a runner became injured or not. Good, um, way to boil it down to something that's quiet. easy to understand. And I think most runners can, um, at least, you know, extrapolate some practical takeaways from that saying that, all right, I've been tracking my distance. Um, you know, most runners track their distance, their weekly mileage, and then that accumulates and most training plans have, um, this is how far you run, this is how much you accumulate per week and, you know, follow that metric. But, um, some, not all of runners would probably track their effort or power or those sort of measurements that indicate effort to then, you know, be careful around those metrics to be safe. If someone had, I know you say that they used a pretty complex system to calculate this critical power and those sort of ratios. Can you maybe highlight some key takeaways or metrics for people to follow if you can talk about that? If they don't have some fancy, fancy... data that have like maybe just their watch or their GPS and something to follow. Yeah, I can try for sure. And I think it can be quite simple, you know, so as you say, most runners I think are pretty good at tracking distance. And you look at something like Strava, it tells you very clearly how much you ran last week and previous weeks and stuff, all relative to distance. So I think a good takeaway for the average runner is to start paying attention to effort. And there's a number of simple ways you can do that, right? You can look at your heart rate in simple terms, whilst your heart rate is affected by a variety of things. If your average heart rate on a run is higher this week than it was last week, and you've run broadly a similar distance, then your effort's higher, accepting the challenges of measuring heart rate well with a wrist-mounted sensor, right? So I would be careful. with people doing that using a wrist-mounted heart rate monitor like this thing, as opposed to a chest strap. Chest straps are much better than wrist-mounted monitors. So if you've got a chest strap, looking at your heart rate is a pretty good place to start. If you don't have one of those, that's not to say you can't use your heart rate coming from your wrist, but it gets affected by a huge amount of things in simple terms when we run our thorax. does what it does and it doesn't really move that much. So we can be pretty happy that we're getting an accurate trace, your wrist does all sorts of stuff, right? You cross the road, you dodge a dog, all these sorts of things. So the validity of stuff coming from the wrist is always a bit poorer. You could look at something really straightforward like rate of perceived exertion, right? We've got the Borg scale of perceived exertion which is really complicated going from six to 20. Why not make it one to 10, right? One is easiest run you've ever done. 10 is fall down, vomit, don't get up for a few hours. It's worth tracking that in all the different runs that you do. And again, if you did a 10K last week that you would class as being a four out of 10, and then you do the same 10K next week and it's an eight out of 10, then your effort has jumped significantly. That's something you should be careful with, right? So rate of perceived exertion is another good way. Whilst we've said distance, didn't appear to track. If you significantly increase your distance, you will increase your effort, right? Distance and effort are intertwined and we've separated them for research purposes, but the reality is they're gonna influence one another. So ways I've done it in the past, thinking back to clinical practice, which wasn't that long ago. I would do some simple rudimentary calculations. So, okay, you're gonna run 10K on a Monday, you're gonna do 5K on a Thursday, and then you're gonna run 15K at the weekend. I want you to multiply your distance by your rate of perceived exertion. So your 10K, which is easy, multiplied by three is 30. Your 5K, which is a threshold round, is gonna be multiplied by seven, so that's 35. And then your long run at the weekend is gonna be a two, which is really straightforward. So 15 by two is 30, 35. You've got a 95 score that week. Do that every week. And then you're broadly getting a perspective of your distance and your effort that you can measure. And it's not to say that number can't increase, right? Cause ultimately the harder you train, the fitter you're gonna get, the better you're gonna perform. But if you suddenly go from here to here, that's when the risk may come. the limitation is we don't know how much is too much before the risk really starts to realize itself. And that rings true if you look at some of Rasmus Nielsen's work, the group from Norway that have done some similar things. They did a very nice study a few years ago looking at distance where under 10% seemed to be super safe and over 30% progression week to week seemed to be... have a high risk of injury, but you've got that huge unknown area in the middle where you may be able to progress safely, but for some people, but not for others. So the next holy grail in this sort of work is how much is too much. We've used baseline data to say broadly this variable is different between these two groups, that the next bit is... how much is too much, that kind of Goldilocks effect, what's too hot, what's too cold, et cetera. We're looking at that now, so we're doing a secondary analysis of these data. The big advantage of wearable technology, right, is if I did this as a lab-based study, you come in to the lab, we collect data, we send you on your way, we follow you, but we never see you again. Whereas with wearable tech, every run you do, I can get that, right? So we can do a prospective, but then longitudinal analysis. And that's what we're doing right now. So we've got every single workout for all of these runners over that 12 week period. So we're now doing a causal network analysis that is hopefully going to allow us to say, not only is that variable the one that links to injury, here's the sort of ceiling and floor that appears to be safe and risky. And again, it's, it's a, it's an exploratory analysis. It's designed to feed. the big studies that we want to run in the not too distant future, but it will hopefully give some inference as this one does as to how much is too much. Yeah. Great takeaways there. That's great. Uh, I wanted to talk about that, um, metric you sort of follow without any wearable technology and having your RPE multiplied by your distance, the kilometers, um, to come up with that score. Um, in the past, when I've been training, I like to use. RPE multiplied by minutes, minutes per session to come up with like the, you know, just your exercise units. Um, would that be a similar process to follow or are there limitations to that one? No, no, absolutely. I think they're, I think they're, they're one and the same, but at the same time, they're different, right? And that's, that's another, another way we could have approached our injury incidents. Right. So there's a, there's a thought process that we should. report injuries per thousand minutes of running, about a thousand minutes rather than kilometers because an elite runner, and I'm looking at you, suspect you run significantly better than I do. You're probably gonna hit a thousand Ks faster than me, but the time that you're gonna do that is also gonna be different. So time is relative to the person, whereas a kilometer for you is a kilometer for me, right? But... the time it takes us to run a kilometer is gonna be very different. So that's another way of tracking that exposure. And I think it works as well as the alternative. And I think at the moment, because we don't know which one would be better, you'd go with the one that works best for the runner. I've got fairly strong OCD tendencies and... I like to run 5k or 10k or 12k, I can't run for an hour and then have 10.7k or something that would really upset my brain, but I run to not be fat and be able to drink a few beers and stuff as opposed to caring about how well I run. So whereas good runners would be able to separate that and their training session is an hour and how long they run in that session is going to be relative to the effort they want and all those sorts of things. So I think you can use either. Yeah. Maybe that you do both, right? You could feed, you could feed distance time and, and RPE into that single calculation and, and see where you go with it. Yeah. Good tip. The, um, I guess wiggle room in terms of how far you can push yourself increasing week by week is an interesting topic as well. And like you say, there have been studies done where less than 10% can probably be in the safe, maybe conservative. progression, if that there's ever a term, but the 30% seems like it is, you know, well within the red zone or your heightened risk of injury and where the middle ground might be for you vary. So I guess anywhere between that 10% and 30% is where most people gravitate towards anyway. Um, would it be fair to say that test out somewhere in that gray zone and just listen to your body? And, you know, just massage those numbers week by week pending how the body feels. So like to say, as an example, if someone wants to increase by 15% for the, for, like per week, see how your body feels, see how you're recovering and bouncing back, and then maybe try another 15% and see how your body feels. And if it's getting a bit sore or you're getting a bit fatigued and not feeling like you're recovering as well, then maybe have a down week or maybe increase by 5% or 10% just sort of massage around that gray zone while. paying attention to those internal cues? Yeah, I think that's good advice. And, you know, for me, it's where injury and performance really heavily clash, right? Because the more you can overreach, generally the better you'll perform. And the runners, it doesn't matter what the sport is, right, whether it's running, swimming, baseball, whatever, the better you can recover, generally the better you'll perform, right? So it's... My take for, and I've always said this to my patients, right? And it might be relative to the demographic I work with. I don't work with, or never used to at least, work with elite high performing runners, or very rarely did I. I'm working with someone that comes in and says, I'm doing my first marathon and I really wanna get under four hours. And I always say, well, why? Why don't you just wanna finish the damn thing? Because running a marathon is really difficult, right? And as a result, I'm always very open and honest that I don't care how fast you run this thing. My job is to either help you recover from the injury you've got or get you over the finish line without breaking down. And whether you do that in three hours or seven hours, I've always been very honest that I just don't care less because it's not my job, right? But as a result, when it comes to progression, my analogy is often, it's a bit like buying a house. If you make a low offer, the vendor says, no, you go up. Whereas if you make a high offer, they'll go, oh yeah, that sounds good. And you could have gone lower, right? So I don't think being conservative, listening to your body and going, okay, I've handled that, let's push a bit harder. I think that's a really sensible approach for the average recreational runner who is doing stuff for the reasons that we've been speaking about. I get that it clashes with. what a sub elite or elite one runner wants to do because they want to push themselves as hard as they're capable of in order to try and perform. So I think it does depend a little bit of who you're working with, but, but for your typical recreational runner, starting conservative and pushing a bit harder if, if a training block is successful, I think he's super sensible. Yeah. And I guess there would never really be a number to say like, okay, you know, like the 10% rule is the 10% rule because it's. Scottish limitations is quite vague, but it's like on the conservative side. So it might as well be conservative, but the idea around, well, how much can I push? How much? I don't think there's going to be a one number to fit all because everyone has different recovery strategies. People like respond differently. People get better asleep than others, nutrition, hydration, all those sorts of things. And so, um, I guess gathering, you know, guidelines to say you can push for 15% increase week over week. 20%, 25% week over week would never be really be that feasible. Cause not only do people have different recovery strategies, but people's recovery strategies change week by week. You know, um, like, like we said, before we started recording, I've got a seven month old daughter that's, you know, my sleep has definitely fluctuated over the past couple of weeks and couple of months and, uh, my opportunities to push myself and train hard as like, is just not, not the way to go in those. stages of life. And so I think trying to gather some data based on where you find yourself, how well you're recovering, how well all those other things are clicking into place. And then you might want to take on the risks to see how much you can push yourself and see if that is successful. And then, you know, it's all about the risk versus reward. Like you say, with, when it comes to performance, it's all about pushing your capabilities. I was always wondering, looking at elite athletes and you know, the, the top tier and how there were so many injuries. And I thought from a physio perspective, like, why is there so many injuries? Because surely they have the best recovery. Surely they have the best medical team, the best physios to really dial in all these training loads and like really have it down to a T, but they're just pushing themselves, they're redlining themselves just to get their best performance and sort of, um, you know, they've got this real thin line of what's safe and I suppose that's why they're breaking down. but I just rambled a little bit, but anything to add to that? No, no. And, you know, it's, uh, it's that some of the people, some of the time saying, right. And they also, the limitation of this approach and what we're going to try and do with this secondary analysis that I mentioned is ultimately what we're trying to do here is boil down something really complicated, like running injury to a singular variable, which is probably going to be a real challenge, right? It's the interaction between these variables that's likely to hold more weight. And that's why we're running these multivariate models to try and find out how they may interact. So my sort of simple analogy for that would be we're gonna take all this stuff, stick it in a colander and see what falls out the bottom for different phenotypes of people. And that's where it may be the... Distance may be a particular trigger if you have a particularly high contact time. And if not, then this is a very theoretical example. So no one grabbed hold of it and think it's the Holy grail. But whereas effort may be more of a problem if you have a particularly long stride length, you know, or something along those lines. So that interaction of how you're running, how much you're running, all the other stuff, you know, is, is going to be interesting to try and unpick and hopefully then. that will give us something we can feed into a prevention strategy. So this is designed to try and complete what we call the Van Mechelen model of injury prevention. So we know the scale, we know how many runners get injured, we know the incidence rate, we've now looked to see what variables are associated, let's latch onto acute load by effort. Let's now design an intervention that could allow runners to control their acute load by effort and test it in a trial against people just running however the heck they want, and then run the cohort study again to see if the incidence rates lower. And that will show us whether the prevention strategy is successful. But just saying don't push yourself as hard, I don't think that's ever likely to lead to a significant reduction in incidence. I suspect the prevention strategy will need more pieces. And if you make it too big, then people probably won't do it and it will fall apart. So that's, I know this, I know the feasibility study itself is, um, like just being released. It's fairly recent. Um, is there talk about doing this, um, up in the ante and actually doing this as a fully fleshed out, um, larger scale model, um, is that underway? It's not underway. We need to write a grant and we need to convince someone to, we need to convince someone to fund it basically. So we were very fortunate with this study. We initially, the guys at Dash were doing this just because they're interested as well, you know? So all of Dash's kind of engineers and stuff, the data pipeline we had going from them to us and stuff. Dash covered the cost of all of that. I then managed to get some funding from our... our quality research impact fund at the University of Essex. So I was then able to reimburse Dash for some of their time. And so that small grant has covered the cost of this manuscript and the subsequent work we're doing now. We're lucky that we've got good institutional relationships with certain publishers, and that's why the manuscript is open access. But to run this at scale, to do it in over a thousand people with the infrastructure that will allow us to set to follow more people over that prolonged period, we're gonna need a sizeable grant. So that's kind of next on my to-do list. And I think we'd need, we, I think our adherence rate is very high, particularly as we got that just by sending a weekly email. We didn't have a research assistant sitting there going, hey, you haven't responded to this email, I'm gonna send it again or. that you haven't responded to now, so I'm gonna pick up the phone and try and contact you or give you a Zoom call or something. So with a bit more infrastructure around it, I think we can get that adherence rate up. We'd also like to be able to provide people with devices. So one of the other semi-interesting things from here, depending on how much you think about this stuff, is Garmin still dominate this market significantly. I think something like 80% of the participants had a... had a Garmin device. So we're gonna try and have a behind the scenes look at what devices give the cleanest data or results in the least amount of data loss. And then to run this at scale, we'd need to provide everyone with the same device. So that's partly where the cost would come from. But again, hopefully that will facilitate adherence. If you finish this thing, then you get to keep the couple of hundred bucks watch that we've given you to join in. So. We're definitely going to aim to do it. It's just a question of how quickly we can convince someone somewhere to, to give us a very large sum of money to do it. If you do get the grant, um, when it comes to the recruitment phase, will you be doing similar things to what you've done in this study, like in terms of just, um, reaching out to groups of runners and then seeing if they'll take part? Yeah, I think that's a, that's a successful strategy, you know, and I think that's the advantage of having colleagues. in the UK, in the US, in Canada, I think we could do with a European collaborator as well, and then possibly one in Asia, and then we've got great coverage across the world. I do think we'd need to try and do more, and that's where possibly things like Parkrun and some of these other groups could be approached to see if people are willing to participate. Like I said, we had pretty stringent inclusion criteria. If we go back to the list, we wanted people to self-identify as a recreational runner. We wanted people between 18 and 45, 18 for ethics reasons, 45 for osteoarthritis reasons. And we had a few people on social media have a bit of a crack at us for cutting the age ceiling at 45, a few people weren't happy with that, but. that there's reasons behind it. We wanted people that were running for more than 12 months, at least three times a week, exceeding 60 minutes total, that the uninjured bit, no more than two additional forms of exercise, they had to currently run with a device. So we had pretty stringent criteria. I think one of my reflections going forwards is we could relax that and hopefully be more inclusive. Because again, if we look at our demographics, You know, the mean mass of the male participants was 72 kilos, the female 60 kilos. The mean BMI of the male participants is 22, the women 21. You know, that's not your average recreational runner. You know, I'm an average recreational runner and my BMI is not 22. I promise you. So, uh, I think we, we did end up with possibly a, a slightly more, not elite, but, but a cohort of people that are kind of genuine. recreational runners that race and running is their big thing, whereas the cohort of runners that are more likely to get injured are big blokes like me running around a couple of times a week to avoid dying of a heart attack. So I do think we need to be a bit more relaxed with some of those criteria. Not so relaxed that you end up massively diluting your sample and struggling to then have external validity relative to a group. I do think we could be a little bit more relaxed on that to make our recruitment easier. Yeah. Well, reach out when it gets to that stage, cause I'm sure the listeners of this podcast and I've got Facebook groups of thousands of people, thousands of runners that love this sort of stuff. And so, um, reach out when it gets to that recruitment stage, I'll be, um, happy to help out and I'm sure the listeners would be as well. Oh, that'd be appreciated. And I think, you know, that one of the other real advantages of of doing this type of study is runners are generally a pretty altruistic group, right? They run because they love to run and as a result, they're generally quite motivated to try and help other runners by participating in a study. You know, and it is pretty light touch having to participate in this, you know, you go through our consent process, you give us access to your watch, you fill in a couple of, a couple of, a couple of prompts and then all you've got to do is click a link in an email once a week, you know, it's pretty, it's pretty, pretty light touch. participating in it, but yeah, we just do what you love. You just go, you just keep running for a couple of times a week. And we, we didn't say you can only run this many times or this distance or whatever we said, you know, run, run as you run, you know, it may be in time that we do run subsequent studies where we do look to control how much people are doing and I get that that's a barrier because runners love to run, right. And that was one of my, one of my sort of thought processes around doing some running retraining studies in my PhD. runners like to run and runners that are told they can't run generally don't respond very well. And so an intervention where you can say, hey, look, you can keep running, but I want you to do a bit of this generally goes down quite nicely. So anything that keeps runners running is a good thing, but that clashes so heavily, like that I'm just looking at the, so I'm off to Copenhagen very early Thursday morning to present these data at sports Congress and my sort of couple of cherry pick statistics that that I've got the benefit of running 40% reduction in all-cause mortality, even when we adjust for a fairly significant set of confounders, that's the why running is good for you a bit. And then the risk of injury, a third of novice runners cease to start to run program within six months and over half of them do so because they get hurt. You can find an injury incidence as high as 90% for recreational runners if you wanna pick that particular cherry. So we know it's good for you, but we know. There's a fairly significant chance you're going to break down with something hurting at some point. So anything we can do to facilitate the former and avoid the latter is, is where we're trying to go with it for sure. Yeah. And hence why a lot of these runners gravitating to podcasts like this to try and help them reduce their risk of injury and increase their running performance safely and chatting to you is all helping them gather some pieces to the puzzle and help them with some practical takeaways to Make that happen. I know a lot of runners listen to this, but also a lot of like health professionals, physios and osteos and those sorts of things. And so I know you help health professionals out with information and particularly around patellofemoral pain and those sorts of things. If people are interested to learn more about your work, is there anywhere that can go any sort of resources that you can guide them towards that you're a part of? Yeah, there are a few places. So kind of the more old school social media accounts, I would say. I'm DrBradNeil on Twitter, although I probably use Twitter significantly less since a certain Mr. Musk decided to set it on fire. I'm TimPFP on Instagram and then website the same. So timpfp.com, which is very patellofemoral pain focused. They're probably the three main places. But I'm never shy to receiving a message or an email or something. If you stick my name into Google, you'll find the University of Essex profile with my email and stuff. People can always reach out. I'm always happy to chat to people. And I say this to students all the time. If you're struggling to get access to a paper, just email the author. The average researcher is over the moon to have someone drop into their inbox and ask to read something you've just spent the last... couple of years on, you know, we want people to read this stuff, you know, we're not going to ignore you, we'll, we'll generally send a, send a copy on or at least, you know, everyone I work with regularly is happy to do that. So yeah, don't never be shy to, to reach out and make contact. This is a perfect example. Because I read that paper, and then I reached out to you to have a chat about it. And here we are on this podcast. And so I think it's like, yeah, it's a massive, I guess. restriction for recreational runners because we want the right information. It's just so hard to get. And so, um, getting these opportunities to have a chat with you and other running researchers to discuss their papers, which like for the recreational runner, like they'll never see it. Most papers hardly see the light of day with so much effort and that, and funding and all that sort of stuff that goes into it. Um, it's awesome that we can have people like you agree to come onto these podcasts and share all these, these insights and very much looking forward to. Um, the scale up version of, uh, this promising feasible study and then whatever, um, comes your way. I know we've had a chat about, uh, potentially coming back on to talk about patellofemoral pain, cause it is, uh, very, um, common occurrence in recreational runners. And I know there's a lot of misconceptions around that injury as well. So I'd love to have you back on to chat about that and maybe answer some questions from some listeners, but, um, right now I just want to thank you very much for your time. amazing job on the paper. Thanks for all the hard effort you've put in to release it. And yeah, thanks for coming on sharing these awesome tips. Pleasure, mate. Thanks for the invite and staying up and navigating the time zones. It's a pleasure. You're very welcome. If you are struggling to overcome an injury, you can jump on a free 20 minute injury chat with me, which you can book through my calendar in the show notes. While you're in the show notes. elevate your running IQ by jumping onto my free email list so you can receive material to help rehab your injury, lower your injury risk and increase your performance. If emails aren't for you, consider my Facebook group, Instagram and YouTube channels. And remember, each insight you get from these resources brings you one step closer to your next running breakthrough.