 I now want to introduce you to Alison Kyo and we've worked together for a long time. Alison studied physiotherapy in UCD and then did a master's in sports and exercise medicine in Trinity. She then came back to do a PhD in UCD and then afterwards started working in the Insight Centre. She worked on a lot of different projects and insights over a number of years related to digital tools and their use in innovation and healthcare pathways and also in promotion of activity and she's also very interested and you'll see from some of the work and Alison was involved in some of the previous work that we spoke about that a lot of her work is involved in the exploration of strategies around marathon running and she was involved in the paceman project. Alison has just recently started a new role as a lecturer in healthcare innovation in Trinity so unfortunately we would be losing her and although she's not involved in running and as a sport Alison is an international hockey umpire so some of you may already be familiar with her and thank you very much for doing this today because you're dashing to the airport immediately for a hockey engagement so over to you thank you. Thank you thanks everyone for being here today it's always a challenge to to follow off on Barry and his great work but I'm going to do my best and go through some of the evidence that we have from existing literature within the area of marathon training um if anyone can't hear me as we go through just raise your hand shout at me as we go um today I'm just going to go briefly into the the evidence that we have um in existence already some of the challenges that face marathon runners when it comes to training we'll then go and look at what the evidence and the published literature says what type of studies exist in this area some of the characteristics of them before looking at what the results of some of them are so one of the studies that have taken place that have tried to predict or alter marathon training times or marathon times based on training and then finally very briefly look at some of the practical things that we can consider at the moment based on the evidence that we have in existence so we all know the kind of the fable of marathon running um has come back from Greek times when the messenger arrived having run 40 kilometers and then drops dead on arrival but marathon running has obviously um come leaps and bounds since then and we all know it in its most recent format um since the 1896 Olympics but really it has exploded in the last couple of decades particularly since the 70s where we now have over 5000 marathons happening a year with over two million participants happening globally and this is big business now we have an awful lot of people that want to do their very best that don't want to get injured and that want to cross that finish line on time so how do they train to make sure that all their time and effort and money and commitment pays them dividends a cursory glance at the internet will show the abundance of information that exists out there and it can be really confusing particularly for people who are just starting off with marathon running or their first marathon running um where do they go youtube instagram scientific literatures experts books the the the amount of possibilities there is endless um and you know you don't even have to look at the likes of Strava or Garmin or anything at the moment to see that we also have like experts who have decades worth of experience that can claim that they know how you should best run your marathon so where does someone start um you know how do they know which strategy is going to work best for them and where do they even begin on picking all of this information because it's absolutely almost kind of like a a paradox of choice happening here and unfortunately the result at the moment is a lot of people are facing this jigsaw puzzle that they just don't know how to get the pieces together that fit them best and and this I suppose is where the science comes in because what science does is has it has a hypothesis we have um a plan or something that we think is going to happen and so we can then manipulate different variables to test whether our idea is true or not if we look at experts they have decades of um I suppose you know free living experience under their belt and they have knowledge around period periodization around physiology but the two things can't be compared one isn't necessarily better than the other but we can definitively state that expert opinion is the same as what a scientific um evidence and hypothesis can show us so and that's where I suppose we were looking at the science because there's lots of different studies that exist out there where people have tried to change different pieces of people's training and then have come up with a result as to how effective that was or not but as a single study we don't learn an awful lot but when we collectively put them together and pool them we can learn an awful lot more and so that's what we were looking to do with a study that we um uh completed a couple of years ago by 2019 now at this stage so we did what's called a systematic review and a systematic review is where we systematically look at all the published scientific research that exists um we extract the information that is relevant to us so for us it's looking at people who have run a marathon who are over the age of 18 and who have reported something to do with their training strategies in the run up to that marathon and then what we did was we pooled them together to say what can we learn from this literature as a collective more than we'll learn from looking at them as individual studies and so what we did was we well we did our systematic review when we found that we had 85 articles that fit our um criteria so that's an immediate flag that despite the popularity of marathons um we actually don't have an awful lot of research in the area of training that has been published most of the research that has taken place has taken place with male runners over 75 percent most of it has taken place with recreational runners and most of it has taken place within the US so again that's a little bit of a flag that we have a biased sample here that the evidence that we have around marathon training sways us towards this cohort of people in particular so as we're going through just kind of keep that in mind in terms of the studies that exist um most of the studies interestingly only really looked at tweaking one or two variables whereas we know from our own kind of um training practices there's so many different things that we can look at when we um go to train for a marathon so the fact that they're only looking at one piece again is a little bit of a limitation but what was also interesting is this this research spans across five decades but over 40 percent of it has actually taken place since 2010 but despite the relative newness of this uh research only five percent of the marathon training research at the moment lists GPS as one of its methods so the majority of research is completely basing its opinions and its recommendations of self-report data okay somebody saying what they did and how they did it but what we did was we took out all the information that existed because we needed to understand well what is in existence at the moment and to pool it together and to make a um reasonably accurate estimate of effectiveness we had to include or only include training variables that had been reported in 10 studies or more so effectively if they're not within 10 studies we can't really um accurately say how much of a role that they have to play um in training so even though there was an awful lot of variables we actually were only able to look at seven and say what influence have these seven had on marathon performance subsequently also when we kind of look at it we ideally would have liked to have pooled them together so say if we take uh average weekly training distance plus longest um training run and say what's the difference between focusing on them versus just looking at uh the longest training run we weren't able to do that and the reason we weren't able to do that is because of that self-report data when there's a lot of differences in how people report something it becomes very tricky for us to definitively state this is what happened okay so there is again a little bit of a limitation there with this but these are the seven training parameters um that were listed in 10 or more studies and interestingly all of them are are influential to marathon performance so we can see there in the brackets at the end there's the range of what was reported but that or squared number is the one that's kind of most important for us to look at the closer that is to one the more predictive it is subsequently of um marathon training so effectively for all of these we have significant um changes in essence if you increase or improve your performance in each of these seven variables you will subsequently decrease your marathon performance um or finish time okay so but we can see um the or squared up at uh no point eight there is maximum training distance of one week average training uh weekly training distance is point seven they are more predictive than something like um our number of sessions a week when it comes to training but what does this mean for us practically we were able to kind of work backwards a little bit and particularly focusing on those who want to do will say a four hour marathon time we were able to turn around and say that there are certain parameters that they should look at in terms of their training volumes so if you're a for a person that's looking to to finish in four hours um your average weekly training distance should be about 44 kilometers you should do about four and a half hours of training a week and you should not go over 63 kilometers in one week in your training block your pace should be about 97 percent of your planned marathon um pacing strategy and the longest training run interestingly should only be about 27 kilometers now this is just for people who are looking to run four hour marathons there's a lot of people that think the 32 kilometers is what we should look at but the evidence that is in existence at the moment for four hours would suggest that you don't need to do that that a 27 kilometer run is the longest thing that you need to do now again the evidence and the kind of the the availability of the numbers wasn't there for us to be able to extrapolate this into two hours two and a half uh we were only able to confidently look at this for four hours but it's still a kind of an indication of the types of thresholds that we could look at if this research develops further but probably the biggest thing for us from this um literature review that we did is the limitations that are in existence at the moment despite the popularity of marathon running we can see that there's not a lot of evidence in existence out there at the moment that has been published and so this is in a way exciting because there's an awful lot more for us to learn and there's an awful lot that we can't necessarily be confident in that work like what Barry is doing can can help and that we can look at further so big cautious point of the day is if someone turns around and tells you I can definitively give you a training program that will guarantee you a three hour training or a finished time they can't based on the evidence that we have at the moment and that's not to dismiss expert opinion but it is to give a little bit of I suppose a warning signal that we don't actually definitively know an awful lot about this as a topic yet similarly some of our limitations again as I've kind of already highlighted are that you know we still need to know an awful lot more about people outside of the US and about women runners in particular I can skip over that one we've kind of covered that so the big takeaway from this study is linked to what Barry is doing and also what you'll hear from Kira is the potential for high volumes of data for us to get meaningful insights as to a what people are doing but then to learn from what people are doing and plan as to how we can change that in the future so if we know that the majority of runners are doing x number of kilometers in their training runs and we want to know the influence of changing that by 10% or whatever we need to know what they're doing and then we can start planning it and then start tweaking it further and some of our studies that we can look to do in the future may be able to benefit from people interacting with the likes of Strava or Runkeeper or potentially in the future even pairing with them to start doing studies like this but at the moment this is very much an area that is growing and that is potentially very exciting for us to look at so that was a very quick whistle stop tour for me I hope I've given you a little bit more time back but a takeaway from this is that really at the moment the evidence suggests that there's really only seven key training behaviors that have been shown to be effective in terms of marathon finishing time at the moment so if you tweak those seven variables and you improve your performance in them you will improve your marathon finish time but this is absolutely still a growing area use the likes of Strava more that gives us the data to use and that we can learn more of this from and be very cautious if someone promises you a definitive finishing time thank you