It's estimated to affect about 32.5 million adults in the United States, which is almost 10% of the population. We know that osteoarthritis is a disease of the articular cartilage, as well as the synovium. What's a little bit less commonly known, however, is that 40% of adults with osteoarthritis go on to develop a comorbid depression. The reason this is significant is with osteoarthritis, you get an upregulation of inflammatory cytokines. And these activate an enzyme known as indolamine dioxygenase. The reason this is important is that this enzyme preferentially shunts tryptophan metabolism towards kynuronine, as opposed to serotonin. As we all know, serotonin is one of the major neurotransmitters implicated in the pathophysiology of depression, that is, decreased serotonin levels lead to depression. Furthermore, it's independently been shown that elevated kynuronine levels also drive the pathophysiology of depression. So a very basic brief overview of our study and the methods is that we collected, discarded intact synovium and cartilage from 20 patients undergoing total knee arthroplasty. These samples were rinsed with PBS and divided using a scalpel. And then we assessed the culture media with high-performance liquid chromatography with tandem mass spectrometry. The results of our study showed that synovial kynuronine production was roughly three times higher than in cartilage, as evidenced here. So we found that the synovium and not the cartilage was the main producer of kynuronine. Furthermore, we also found that a compound known as 1-methyltryptophan was able to inhibit synovial kynuronine production. The reason these results are important is because synovectomy, which is the removal of synovium during primary arthroplasty procedures, is not routinely performed. But based on the findings of our study, this creates a future avenue to further investigate the role of synovectomy and potentially attenuating the post-operative depression and pain symptoms that patients with knee osteoarthritis experience. Furthermore, our results show that 1-methyltryptophan is a potential treatment option for patients with debilitating knee osteoarthritis. Typically, patients that have really bad knee OA, the stepwise progression of treatment is conservative. So patients do PT, take oral anti-inflammatories. And if that doesn't work, sometimes they resort to steroid injections or hyaluronic acid injections. And those have varying efficacies. And so we're proposing that 1-methyltryptophan could potentially be a future treatment option for patients with knee osteoarthritis and serve as a potential bridge between conservative treatment as well as surgery. And yeah, with that, I'm happy to take any questions. Thank you. No questions. I have a question. Yes, sir. So are you recommending complete synovectomy with PTA? I am not. I am recommending that future studies look at that. What's the downside of synovectomy? You're removing a large portion of this. So it's basically extending the post-operative recovery time and also it's not been shown to decrease, or it's been shown to make it more difficult to gain range of motion after surgery. Yes, sir. Yeah, yeah. Yeah, yeah, no, I definitely agree. I think the one methyl tryptophan is a really promising avenue within the field, and I think future studies need to address that or look at that into more detail. I think the synovectomy portion of it is to kind of confirm what we already know. Yeah. Yeah, no, I agree. Thank you, appreciate it. Any other questions? Okay, cool. Thank you guys. Thank you, Kian. Next we have Derek Day. Derek Day. So Derek will be talking about diagnosing hamstring strains using shear wave elastography. Thank you. So yeah, I'm Derek Day, I'm a PGY-4, I'm at Georgetown MedStar National Rehabilitation Hospital. I'm grateful to have this chance to share some of our early results in a study that I have been working on with my mentor, Dr. Alter, who's here, as well as with an excellent team again at the NIH. So we are looking at the utility of shear wave elastography in the diagnosis and monitoring of hamstring injuries specifically. So again, we know that hamstring injury, hamstring strain is typically clinically diagnosed based on history, exam, clinical assumptions, and can be diagnosed fairly reliably that way. The gold standard for imaging would be MRI, but then there are trickier things when it comes to return to play, return to activity, it can be a very nagging injury that can recur. So having a useful and kind of easily, readily available objective tool, both for the confirmation of the diagnosis and then to follow up these injuries would be very helpful in the clinic. And having something that is, again, you have it at the bedside, less expensive than MRI to follow up these injuries, multiple MRIs is not typically something we're doing for a hamstring injury. So we want to have more objective tools, and so that's what we're looking at. And our hypothesis is that you can detect a difference in the elastography values or in stiffness at the site of injury, and that that then would return to normal with recovery. And just as for kind of a simple and brief overview for any who may not be familiar, shear wave elastography with ultrasound, you're using the same transducer with a machine that has that capability. And what it does is there's a high energy, so acoustic pulse of energy is sent from the transducer and creates these transverse waves in a perpendicular direction from the transducer, and those are the shear waves. So I like to think of it like strumming a guitar string. So that pulse is like strumming down on the tissue, and then the velocity of those shear waves is proportional to the stiffness of the tissue. So that's how we then can detect or measure the stiffness of tissue with shear wave elastography. So our study is a cross-sectional study. We are comparing healthy controls to patients who've had injury, and enrollment is open, so we are still early. We're still enrolling healthy controls and symptomatic patients. To this point, the data that I'll be presenting today that we've analyzed is in five healthy female controls. We've scanned both limbs in them, so 10 limbs, and then one symptomatic patient, and we scanned her symptomatic side and the asymptomatic side. All of these, the controls and the patient, had shear wave elastography with the Samsung RS85, and all underwent MRI. So in our healthy controls, we were able to confirm that there was no underlying hamstring injury. So we are looking at the elastography values. So what we do is, in long axis on the muscle, we turn on shear wave, and you can then sample different sites. So we're using two millimeter diameter samples, six samples within one image, and we get the average elastography value of that, and then can compare those averages among the healthy controls and the symptomatic patient. For our patient, we scanned her at one week after injury, and then we were able to scan her again seven months after injury. At that point, she had had several months where she had been asymptomatic, had been able to return to activity. And we had standardized sites that we are scanning these muscles, and then including with the symptomatic patient at the point of maximal tenderness. So we did see at the time of injury, if I can get my cursor to work here, there we go. At the time of injury, we are seeing that there was greater stiffness or greater elastography values at the point of maximal tenderness in our symptomatic patient on her symptomatic side, the left side. In the image you can see here, this is from the initial scan. So again, one week after injury. Qualitatively, you can see there's a heat map for the stiffness. Things that are deeper red indicate higher elastography values versus the deep blue lower. So you can even just kind of looking qualitatively at it tell that between our symptomatic side and the right unaffected side, there was greater stiffness at the point of maximal tenderness. And then we have our scans. These are the images from seven months post-injury below. So the data showed on the quantitative side, our symptomatic limb at the point of maximal tenderness in our patient had more than two, her elastography values were more than two standard deviations above the average of our healthy controls. And it was above her asymptomatic side as well. And then at seven months, so post-injury, her left symptomatic side at that same site returned to within the normal values. So it was almost exactly the same actually as the average of our healthy controls and within one standard deviation of her asymptomatic side. So this, again, this is a clinically significant result, not statistically significant with a single patient. But being able to pick up that signal was exciting to us, that this is something that could be useful. And perhaps most significantly or most meaningfully, being able to see that change over time on the symptomatic side. So seeing that she returned to normal when she was asymptomatic and had recovered from her injury, as this may be a useful tool for that, for kind of tracking recovery. And so the implication then would be, can we use this to guide return to play? Can we use this to figure out rates or risk of re-injury? So we're excited to continue this to get more data to where we can have more statistically significant outcomes. And of course, standardization is key here. So that's one thing that's a struggle with ShearWave in general, because between different machines, and we've seen even different transducers on the same machine, you can get different values, different users, you can get different values. So we are using a very standardized protocol and going forward, that would need to be done in studies in general. And there are other studies that actually are suggesting that you should have lower stiffness at the site of injury. Some of that may be because of edema right there. So our efforts are really to standardize and to be measuring muscle tissue rather than any sites of edema or of defect, so that we're really seeing what's happening in the muscle tissue. But again, excited to see where this goes going forward, and I am happy. So, as I mentioned at the beginning, these can be really nagging injuries that recur or that people feel like they're asymptomatic, they can go back and then becoming injured again. So, if we can confirm on imaging that they have returned to normal values and then extending that to with normal values or based on your trend with elastography, can we predict whether or not you're going to re-injury or have a recurrence of this, that would be the real clinical utility to guide that return to play. So interesting, interesting study. So the five controls, average age 30.6, 4, something like that? Yeah. Yeah, 30.4. And your person who got hurt, 57. So it's interesting that the qualitative number that comes up there for the normal side is about the same, even though the age discrepancy is so great, as somebody who's older than 57 now and tore his hamstring running track at 20 in college. How many days out is the affected scan that you showed? Seven days. So that's a week out already. And a 57-year-old, eh. It's interesting. And again, yeah, so clinically is different than bench. So this is bench. So I don't know if you could call it clinically significant. It's interesting that the number changes, but it's seven months later. What was her sport? How'd she get hurt? It was running, if I remember right, yeah, runner. So I wonder if, I mean, it's interesting start and follow some track teams around town, get the kids in and see what happens with that. Absolutely. Yeah. But I'd be more impressed to see what happens, if you could look at treatment differences. We're all running to ultrasound, deep tissue massage, cross friction massage, PNF stretching, all those things and find out the one or two that really makes a difference. And then if you can correlate that with hamstring strength versus quad strength or the ratios in between all the things they did to us when we were in college and all the things we've done in the last 30 something years to our patients. But it's another interesting tool. Yeah, absolutely. Looking at treatment effect on elastography would be excellent questions for future study as well. Anyone else? All right. Thank you. Thank you. Next we have Paige Dirk. That's your last name, right? Dyrick. Dyrick, yes. She's going to present on female athlete tried and risk of non-bone stress overuse, musculoskeletal injuries in our college athletes. Yes, I can get rid of this. All right, so good afternoon, everyone. My name is Paige Dyrick. I'm one of the current sports medicine fellows at Spalding. And I'll be presenting on the female athlete triad and risk of non-bone stress overuse musculoskeletal injuries in collegiate athletes. I have no relevant financial disclosures. So we know that female athletes have twice the rate of overuse musculoskeletal injuries compared to male athletes. But we don't entirely understand why. When we examine the female athlete triad, which is going to include low energy availability, with or without disordered eating, low bone mineral density, and menstrual dysfunction, we know that there is an association between female athlete triad and bone stress injuries. What we don't entirely know yet is if there's any association between the female athlete triad and non-bone stress overuse musculoskeletal injuries. So this study aimed to elucidate that relationship between the female athlete triad and overuse musculoskeletal injuries in female athletes. So this is a retrospective cohort study that included female athletes that participated in any NCAA Division I sport at a single academic institution. Our main outcome measure was non-bone stress overuse musculoskeletal injuries. And what I mean by that is basically tendinopathies, plantar fasciitis, bursitis, injuries of that nature. And so what we ended up doing is we obtained general health information, and then we screened athletes for female athlete triad components at their pre-participation physical examination, which is required by NCAA before any of the athletes can compete. So that's where we obtained the information from. And then we also evaluated athletes who chose to have their bone mineral density measured as part of a separate study that was looking at bone mineral density, kind of normative values of bone mineral density in an athletic population. So all of these athletes ended up having complete PPE data, so pre-participation physical examination data, and they all ended up having DEXA scans as well. All athletes were assigned a triad cumulative risk score based off PPE and DEXA scan data. So ultimately, we ended up using this risk stratification point system, which was basically proposed by this 2014 female athlete triad consensus coalition statement on treatment and return to play. And it was really looking at this point system, really evaluated evidence-based risk factors for developing the female athlete triad. So these are just some of the risk factors, whether there are any dietary restrictions, what their BMI is, when their age of menarche was, how many menses they get in 12 months, what their z-score was on the DEXA scan, and whether or not an athlete had a history of stress reactions or fractures. Each of these criteria would be assigned a particular point. And then the cumulative triad risk was the addition of these different risk criteria. So for example, if an athlete said they had a current eating disorder, that would give them two points. If they said their age of menarche was somewhere between 15 to 16 years old, that would give them an additional point. So then when we summed all of these together, what was really what we ended up looking at was a high risk criteria would be a score of six or greater. That would be considered high risk for an athlete. A summed score that was between two and five was considered moderate risk. And then a summed score between zero and one was considered low risk. So then once we kind of calculated the summed risk for each of the athletes, we looked to see what type of musculoskeletal injuries they obtained over their collegiate participation. So this is kind of table one, which looks at which athletes had overuse injuries and which ones didn't. And so out of the 239 athletes, 103 of them, or 43%, ended up sustaining an overuse injury, which included a bone stress injury at some point during their athletic career. And follow up time was two and a half years. And so what we look at for just general demographics, the athletes who sustained an overuse injury, which included a bone stress injury, were younger, about six months on average, than those who didn't have an overuse injury during their career. They had a lower BMI, a lower percent body fat, and they had a higher triad risk score. Those are all in bold. And then we also separated the athletes based off of what sports they participated in. So we categorized athletes as if they were in lean advantage sports. Lean advantage sports being those that subjective appearance or weight is really important, those that are gymnasts or synchronized swimmers or in weight class sports like sailing. Those were going to be lean advantage sports. We then looked at athletes that were in non-lean sports. And those were more ball sports. They were going to be soccer, volleyball, basketball. They had a low risk of low energy availability. And then finally, we also separated into distance runners and then other endurance sports, which is going to be any sport that required any sustained aerobic effort. And that was going to be crew, rowing, swimming, other track and field distances as well. And so what we found is those that were distance runners or those that were involved in lean advantage sports were more likely to obtain an overuse injury during their career than other sports. And then finally, with the other data, and this is really the crux of what this whole project was about, was do athletes have a higher female athlete triad cumulative risk score? Are they at a higher risk of sustaining non-bone stress overuse musculoskeletal injuries? And this table is basically saying, when you actually account for the triad risk score, you can see that it's statistically significant and related to increasing the risk for bone stress injuries. But a higher female athlete triad risk score does not necessarily increase their risk of sustaining other non-bone stress overuse musculoskeletal injuries. So that's really the crux conclusion of this research and something that was actually very opposite of what my hypothesis was. And then just based off of just other data and breaking it down into the different sports, as I kind of mentioned before, it's not really all that surprising. But distance runners were more likely to sustain both non-bone stress overuse injuries and bone stress injuries. And those that were in lean advantage sports were more likely to sustain non-bone stress overuse injuries. So in conclusion, main thing that I really wanted to get across was that the female athlete triad cumulative risk score is associated with an increased risk of sustaining bone stress injuries, which we know, but not other types of overuse musculoskeletal injuries like tendinopathies, like plantar fasciitis, bursitis, or any other overuse musculoskeletal injuries. When we're controlling for the triad score, participants in lean advantage sports had an increased risk of non-bone stress overuse injuries. And then distance runners had an increased risk of both non-bone stress and bone stress injuries compared to those in non-lean sports. So main thing that we can kind of take away from this research is that addressing low energy availability may have more impact on reducing bone stress injury, but it may not be the right approach to treating those that are getting recurrent non-bone stress overuse musculoskeletal injuries. And then I just included citations and level of evidence for these as well. Thank you. And if not, that's totally fine Hope you found the research interesting. Thank you If you go back to the table, you know you the 145 189 Is that done so that is that an end the number of patients or the number of injuries? No, these are gonna be number of injuries. So one person could have more than One injury. Yes. Uh-huh. Yeah Okay It was just over it was our follow-up time was two and a half years and so it was just sort of Close. Mm-hmm. Yep Did you see did you try to kind of do it by athlete like treating an athlete just as one injury? Sorry, can you can you repeat the question clear if you go back to the previous table? Oh I see. Yeah, so we at least we included we separated The overuse injury here. The N is the number of athletes, but then in this table The number of injury is going to be 189 for a number of all overuse injuries With 44 of them being bone stress and then 145 being non bone stress So, why did you kind of have that approach and what I'm just trying to get at if you know You didn't see an effect here And if that's kind of if it's kind of confounded by the fact that you have number of injuries versus number of patients Yeah, I mean, I think I Mean ultimately, yeah, I think it was more I don't know if I have the right answer to why we ended up just choosing multiple injuries for for one athlete But when we were ending when we were doing the chart review We were going through each kind of season and how many musculoskeletal injuries that they sustained during their career Um, there were some that were more frequent than others, yes, uh-huh. And I think that's typical in any community. Yes, mm-hmm. In the country, how do we take care of it? It's pretty small. Right. Yeah, and I honestly would have thought that it would have been, that FEMA athlete triad risk score would be associated also with non. Yeah. So I think if we're looking for bone stress injuries, prevention is number one to make sure that we're not having athletes go down the route of where they're getting osteoporosis or they're getting functional hypothalamic amenorrhea. So it's a lot of identifying those factors early on for what the female athlete triad components are, and then addressing those and seeing if these athletes need to be involved with nutrition counseling, if they need to see a psychologist. There's a multidisciplinary approach, at least at the institution where the study was conducted and at others as well. That's a multidisciplinary approach, especially when it comes to addressing athletes that might be at risk for the female athlete triad, particularly those that are going to be runners and those that are going to be in these lean advantage sports. When it comes to the overuse non-bone stress injuries, it's something to keep in mind that it's important, obviously, to eat well and get enough nutrition and energy in order to compete. But there's more that goes to it. I think a lot of it has to do with cross-training. It's very often that we're seeing runners that are coming in that just run hundreds of miles a week and not necessarily doing too much else. And that's just going to put them at risk for sustaining these overuse injuries. So it's really endorsing, should we get them into the pool and do cross-training that way, get them on the bike, get them off of just concrete running, where that's going to really increase just that repetitive load that they're getting. So I would just say, at least for especially those that are getting these recurrent tendinopathies, it's going to be a lot about managing strength management, load management, teaching them the right exercises that they should be doing, and then cross-training as well, just to keep them off of just recurrent running injuries that we're most commonly seeing. Thank you. Thank you, Paige. Thank you. Next, we have David Ibrahim. Is David here? Yes. And he's presenting on early sports specialization as associated with an increased risk of lower extremity injuries in NCAA athletes. Bye-bye. All right, so hi everyone, I'm David Ibrahim, I'm a fourth year medical student at Michigan State University, College of Osteopathic Medicine, and I'm here today to talk about the association of early sport specialization and its increased risk of lower extremity injuries. So my team and I have been working with NCAA institutions to investigate the long-term effects of early sport specialization, and the reason for that is there was a previous survey that looked at recruitment coordinators, and they actually stated that they tended to look at whether or not high school athletes were multi-sport or single-sport athletes during that time when they would consider a scholarship. And so their reasoning for that was that the students who were single-sport athletes tended to get injured more often during college, and that being said, there had never been a study to date on that to see whether or not it's true. And so with, you know, the U.S. reaching all-time high, record high of NCAA athletes at 520,000, there's cause for concern. And so MSU created a task force to research this, and this involved three divisions, institutions, so D1, D2, and D3, and then we had a total of 211 participants who were able to answer the survey, and this was a retrospective cohort study. We ended up having a total of 95 students classified as highly specialized. We had 69 that were moderate and 40 that were low specialized, and then in addition, we also had, of the high, we had seven who were classified as extremely specialized. And the way that we stratified these students was by asking a previously established four-point question, four-question study, and then each question, if they answered yes to, would add one point to their total. And so if they answered yes to, did you choose a main sport before college, or did you quit other sports to focus on one before graduating high school, or did you train for one sport for more than eight months out of the year prior to college, or did you quit all other sports before the age 12? And so if they answered yes to zero or one of them, they were classified as low specialized. If they answered yes to two, they were moderate. Three would make them high. And then those who answered yes to all four were classified as extremely specialized. Moving on to figure two, you actually see a pretty similar percentage as far as the low specialized athletes. So these are the multi-sport ones. Blue is the percentage who had injuries, whether it's lower or upper extremity, and then orange is the percentage who did not have any injuries. And not only is it similar, but it's actually higher for those who didn't have any injuries. But as you move up in terms of specialization, that flips, and then the gap widens more and more until you get to the extremely specialized athletes who've only been playing one sport since they were, before they were 12 years old, all of them had injuries during college. Moving on to table two, when we looked at just moderately specialized athletes and compared them to the low specialized, we had about a three times higher odds of having any injury as well as almost three for lower extremity injuries. But that was non-significant when looking at upper extremity and whether or not surgery was required to repair that. And then moving up from moderate to high specialization, all four of these categories we looked at were significant. And it's worth noting that it was about a five times higher odds of having any injury compared to those who were multi-sport athletes. And then we also looked at the time commitment across all of the specializations, the time that they spent per week practicing, training, and competing in their respective sports. And we found no difference between all four with an average of about 22 hours per week. And then in summary, on average the return to play was shorter for the low specialized athletes at just 85 days as opposed to 112 for the highly specialized athletes. And then those who were moderately and highly specialized were more likely than those who were low specialized to report an injury. And so those who are involved in NCAA athletics, from the students to parents, coaches, sports administrators, team physicians, should recognize this association between early sports specialization and the increased risk of injuries. If not, thank you for your time. Okay. That's fine. So, I know that as far as that, I think we do have data on that that I don't have off the top of my head, but I can get to you afterwards, but as far as the highly specialized ones, they had like a three and a half times greater odds of having to have a surgical repair compared to those who are moderately specialized or low. Yeah, so the return to play wasn't that part. I'm sure there were studies on it in the past. The only thing that I was saying that we there wasn't studied up to this point was early sport specialization and the risk of injury. And you're presenting on the same topic, which is the epidemiology of injuries. So she's presenting on epidemiology of injuries in the United States. High school track and field throwing events from 2008 to 2019. Hi everyone, I'm Toka PPM, current PGY3 at Spalding. This was prepared as an e-poster, so I'm so sorry if the details are not clear to anyone. If anyone wants a closer look at the tables or the figures, please come by after and I'll show them to you, hopefully with a better definition. So our research focused on epidemiology of injuries in the U.S. track and, high school track and field throwing events. Specifically, we looked at shot put, discus, hammer events, and we wanted to know that compared to the previous research that has been done on throwing events, they've usually aggregated data, didn't stratify it by events, so it did miss a couple of details about the injury rates between that. And given that each one of these specific throwing events poses unique challenges and has different mechanisms, we wanted to know the impact of studying each event separately on the injury rates and patterns. So we did a descriptive epidemiology design. We looked at the athlete exposures. We counted each athlete exposure as an athlete participating in one particular event, whether it be practice or competition. And any reportable injury was an injury that basically affected the athlete. Limited participation in the sport for at least a day or resulted in a specific type of injury. We used rate ratios to compare the rate of injuries between competition and practice, and we used the injury proportion ratio to compare relative proportions of the categorical variables themselves. So from these results, just to sort of summarize the main points, in terms of injury patterns, we looked at the body parts that were affected. We did notice that the shoulder was the most affected body part. May not come as a surprise given it's a throwing event, but surprisingly, previous research did show that the most common injuries were in lower extremities during throwing events. And this research did show that it was shoulder followed by ankle and then by knee. This gave us an idea that if you do stratify by event type, it might give you different data. So it's an important part of epidemiology studies to focus on that. So that gave us an idea about if there's any future research to not aggregate just all of the events and focus on event types as well. Another area that we did notice was that muscle strains were the most common injury type. We did notice that stress fractures were not as frequent. So this tells us that the athletes did not suffer from extremely disabling injuries and were able to return to play. The second main point was when it came to competition versus practice, there was reported more injuries during practice than competition. And it was more in girls versus boys. However, when we did stratify the data by events, there was no sex differences based on chronicity of injuries, which is also different from what previous studies have shown that there were higher injury rates and higher chronic injuries in girls than in boys when it came to high school track and field throwing events. The other main point that we noticed is we don't frequently think of head injuries and concussions when it comes to throwing events just because of the mechanism of it. However, there was a reported 3% of athletes that had concussions. So if you are suspecting one, not a bad idea to pursue it with your athlete. And our study did have some limitations, one of them being that because we use the Rio database and what the athletic trainers reported in it, it might underestimate the actual number of injuries that were reported. And we did have a limited sample. So even though there were over 5 million athlete exposure events, there were only 267 track and field injuries total within throwing events specifically. All right. Any questions? So the 12 year study. Yeah. It's supposedly every high school in the United States. So five point something million of them. Good point. Not every high school in the US. They did randomly select high schools based on geographical regions. So it wasn't all of the high schools. There were only 267 adverse. Injuries per 5 million, 400,000. There were only 267 times in 12 years. Yeah. So within the high school events, within competition and practice. Yeah. But again, that's one of the limitations of studies that we think there might be underreporting of. Spine injuries, because you see that a lot. We wanted to discuss that. We did have reported lower back lumbar spine injuries. Those were 7.9%. Yeah. Chest and thoracic spine was a lot less. It was like 1.9%. Yeah, we have some diagnoses that were reported. Muscle strains were the most common. I don't know how comprehensive they were, but we were limited in the data that was collected within the Rio database. Yeah, very good idea. Any other questions? Okay, thank you. Thank you. Okay, our last presenter of the day is Edward Runquist. Thank you. Edward? Yes, go ahead. Gotcha. You have a, you have a flash drive? Okay. And Edward's presenting on prevalence, correlates and consequences of interpersonal violence in currently competing NCAA athletes. Thank you. Okay, I guess I'll just have to scroll a little bit, but my name is Edward Runquist, I'm a third year at Drexel College of Medicine in Philadelphia. I'm presenting on prevalence, correlates, and consequences of interpersonal violence in currently competing NCAA athletes. So we're diving more into the psychology realm. Presenting on behalf of my team at the Sports Equity Lab, founded by Dr. Jetsa Twockley out of Yale University School of Medicine. A little background about this study. So interpersonal violence in sport is of growing concern, yet its implications remain poorly understood, particularly among U.S. college athletes. It's been studied a lot in Europe, but not as much as in the U.S. So IV is a broadly inclusive term, rising to prominence in both the developmental health and sports medicine literature as a comprehensive means of reflecting the range of abusive behaviors experienced by college athletes, and that encompasses interrelated domains that include neglect, abandonment, physical, financial, sexual, psychological, and emotional abuse. So given the need to better understand the driving factors and consequences of experiencing IV, we partnered with the NCAA to document the self-reported prevalence of IV in U.S. NCAA athletes, to identify associated independent risk factors, and to examine potential consequences related to interpersonal violence in terms of athletes' psychosocial well-being, emotional connection to their sport, and reported willingness to seek help. And as a secondary objective, we further looked at how reported experiences of IV varied among athletes based on self-reported variations in race, ethnicity, gender, sexual orientation, and disability status. We saw in previous papers that they kind of just look at IV as a whole and not really dig into who is getting, who is affected most by interpersonal violence. So we used a retrospective self-reported study called the NCAA My Playbook, which is an annual survey sent out to collegiate athletes across the U.S. This particular survey included 123 universities across NCAA levels, so NCAA Division I, II, and III schools. So our results, overall, we had a total of over 4,000 athletes who we had data to look at on. And with that, we found that 9.8% of the athletes that we surveyed experienced interpersonal violence throughout their collegiate career. And this disproportionately affected athletes who were female, non-heterosexual, and disabled when compared to their male, heterosexual, and non-disabled counterparts, with most of the interpersonal violence being from the psychological, emotional abuse, and neglect or abandonment realms. And we saw that this carried through in the multivariable analysis, where female athletes, non-heterosexual, and as well as athletes who were older and at additional years of NCAA eligibility were more prone to experience IV than their colleagues. And then looking at the outcomes and reported experiences of IV, this was on four different scales, one that looked at perceived performance, one with team cohesion, and then emotional connection to their sport and willingness to seek help. So athletes who experienced IV throughout their collegiate career were more likely to be less satisfied with their performance, felt less like they contributed to their team's success. And also, they felt lack of team cohesion and association with their group. And ultimately, this led to higher rates of burnout, feeling uninterested in their sport, and more willingness to quit when compared to their colleagues who have not experienced interpersonal violence. Reassuringly, though, it wasn't associated with an athlete's willingness to seek help. So ultimately, in this paper, in the discussion, we talked a lot about preventative ways the NCAA can implement into protecting these athletes on the primary, secondary, and tertiary levels, whether that being through bystander training with coaches and teammates, because those are the largest perpetrators of this abuse, also implementing more mental health resources through the providers that see these athletes on a daily basis, as well as bringing in maybe sports psychologists, and then also calling on the NCAA to put in more rules and regulations on perpetrators of this abuse in order to stop it from continuing in these teams. And that's kind of what we're seeing in the media as coaches being called out on their years of abuse. So kind of putting in surveillance systems and reporting systems early on that we can catch these perpetrators and be able to stop interpersonal violence from continuing in NCAA athletics. So ultimately, we hope these results give a foundation for evidence and future studies to dive deeper into interpersonal violence on the demographic factors. Because this was like a prevalence estimate study, we didn't—our questionnaires were kind of broad and didn't really target all of the different types of abuse just because we didn't want to re-traumatize our athletes. So hopefully going forward, we can continue to look at the data from my playbook each and every year, and hopefully our recommendations make a difference. Thank you. Yeah? I don't know if you know the answer to this or if other people do, but what's the reporting process? Yeah. So I think it depends on each school, and that's kind of the problem because this is like a yearly survey, right? So people may be doing this at the end of their school year and not really going to their school coaches or administrators to report this abuse. And it's obviously de-identified when we collect the information, so we don't know who these athletes are. So that's why in the paper we've written is kind of calling on the NCAA to have a blanket surveillance system that they can use to target those athletes and those teams. It's all types. So, the questionnaire that we implemented, this was the first time it was implemented into this survey. It was intentionally vague. It just said, have you experienced financial abuse in your collegiate career in the past six weeks? It gave a couple of examples, but it wasn't specific and it gave you everything that financial abuse could be. Was that different across the spectrum between your Division III athlete, Division I athlete, so you didn't get the NIL money to be able to do that? No. So, that's something that we are looking to do going forward. I think this was just like a foundational study. In terms of diving into each of the different types, we couldn't do that all in one paper. So, but it is interesting, especially with that. You could, but it's a long paper. Yeah. This one's already long as it is. Any other question? Do you have access to the long-form contractual? Hm? Do you have access to the long-form contractual? I know the sports medicine providers, yeah. Thank you. Thank you all for coming. I think that was our last presentation of the day. Thank you, presenters. Thank you to the audience.

prevalence

correlates

consequences

interpersonal violence

NCAA athletes

female athletes

non-heterosexual athletes

disabled athletes

satisfaction with performance

team connection