Training champions: University of Delaware experts prepares students Olympic success
University of Delaware students, alumni and experts are very involved with this year's Olympics. The following are available for interview.
Alumni Attending Olympic Games Shannon Colleton is a 2022 graduate of UD's Physical Therapy Sports Residency Program heading to the Winter Olympics with the U.S. Ski and Snowboard Team. She's specifically working as a PT for the women's speed skiing team (Super G and the downhill competitions).
Students Covering Olympics Cris Granada, a senior communication major and member of UD's soccer team, has parlayed a summer internship with NBC Sports into a position as a production assistant with the network at the Winter Olympics.
Professors with Olympic Expertise Matthew Robinson, professor of sport management in Lerner, is an all-around Olympics expert. He can talk about the host city, Milan, and the IOC's evolving model of hosting games in multiple locations. He can also talk about the idea of sport as a unifier despite what's going on in the world around us. Matt can also talk about the burden the NHL faces, having to pause its season so players can compete on the world stage. While it's an honor to have an athlete represent their country on the world stage, it's also a risk to the professional team if they get hurt. The NBA feels similarly about the Summer Games. Soccer also pauses for the World Cup.
Jeffrey Schneider, clinical instructor of kinesiology and applied physiology, has worked with Olympic figure skaters in the past and can speak as an expert on this sport.
Thomas Buckley, professor of kinesiology and applied physiology, is an expert in ice hockey and bobsledding. He can talk about common injuries, risks/benefits. He noted that bobsledding has a surprisingly high rate of concussion and repetitive head trauma due to the speed of the sport.
To contact Robinson and Buckley directly, visit their profile pages and click the "contact" button. Interviews for all the experts featured here can also be arranged by contacting mediarelations@udel.edu.
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Biography
Dr. Buckley is a Professor in the Department of Kinesiology and Applied Physiology as well as the Biomechanics and Movement Science (BIOMS) program at the University of Delaware. Prior to arriving at UD, Dr. Buckley was an Associate Professor in the Department of Health and Kinesiology at Georgia Southern (2007-2014). Previously, Dr. Buckley was an Assistant Professor in the CAAHEP/CAATE accredited Athletic Training program at Dominican College (2001 – 2007) in Orangeburg NY and had served as an Adjunct Instructor in the Physical Education program at the City University of New York – Hunter College (1997 – 2001). Dr. Buckley his doctorate in Applied Physiology from Columbia University’s Teachers College (2007), is master’s degree in Athletic Training from Indiana State University (1997), and his bachelor’s degree in Athletic Training from Springfield College (1995). Dr. Buckley’s primary research interests are in the medium- and long-term neurological effects of collision sports participation and their associated repetitive head impacts as well as elucidating the relationship between concussion and subsequent musculoskeletal injury. Additionally, Dr. Buckley works closely with the University of Delaware Athletic Department and Athletic Training staff on concussion management of the student-athletes. Dr. Buckley has over 215 peer-reviewed publications and has been awarded nearly $3 million dollars in research funding from National Institute of Health/Neurological Disorders and Stroke, the Office of Naval Research, the NCAA/DoD CARE project, the Delaware Economic Development Office, the Army Research Office, and research contacts with industry partners.
Areas of Expertise
Long Term effects of Concussion
Concussion Research
Media Appearances
UD using AI for injury research
WDEL online
2025-05-14
Thomas Buckley, professor of kinesiology and applied physiology at UD, worked with colleagues in the UD College of Engineering, and said they've developed an AI model that goes through the data produced by 150 variables to find a pattern, which can then predict an athlete's propensity for a musculoskeletal injury following a concussion.
Mild, moderate physical activity may reduce time to symptom-free status after concussion
Orthopedics Today online
2022-02-17
Athletes diagnosed with a sports-related concussion had an association between mild to moderate physical activity acutely after concussion with reduced time to symptom-free status and return to participation, according to published results.
Youth football participation doesn't impact concussion recovery later
United Press International online
2020-09-20
Starting tackle football at a younger age may not affect a player's ability to recover from a concussion as they age, a study published Wednesday by the journal Neurology found.
CARE Consortium: Estimated age at first exposure to football and neurocognitive performance
National Collegiate Athletic Asssociation online
2019-04-24
Previous studies have found that repetitive head impacts to athletes during adolescence can have potentially detrimental effects much later in life. But what short-term effects might that early-life exposure have? To find out, Jaclyn Caccese, a postdoctoral research fellow at Delaware, and a team of researchers delved into data from the ongoing NCAA-Department of Defense Concussion Assessment, Research and Education Consortium study, examining whether the age at which athletes first played football had any effect on neurocognitive performance or concussion symptom severity when they reached college. Their results were published in Sports Medicine, a medical journal.
VIDEO | Concerned about concussion? Here's what to look for
WDEL online
2018-08-14
"You need the athlete to self-report. Most concussions are not obvious," UD Associate Professor Dr. Thomas Buckley said. "The athlete has to acknowledge that they don't feel right."
Long-Sought NCAA Football Practice Legislation Finally Within Sight
Huffington Post online
2015-08-10
Thomas Buckley, an assistant professor in the department of kinesiology and applied physiology at the University of Delaware, is heading up his school's part of the mammoth NCAA-DOD research initiative. He told HuffPost he believes that Hainline is doing the best job he can to "change the culture" within the “slow-moving” NCAA. “I [just] do not think he has succeeded entirely yet," he said.
Collision Sports and Neurodegenerative Disease: Inclusion of Moderating Risk Factors
Exercise and Sports Science Reviews
Buckley TA, Caccese JB, Jeka JJ.
2025-07-01
Collision sport participation with repetitive head impacts has been associated with increased risk of neurodegenerative diseases, but also have lower mortality rates for many individual conditions. The role of modifiable risk factors in later life development of neurodegenerative diseases in athletes is a clear knowledge gap and a potential opportunity for interventions to improve health related quality of life.
A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes
Sports Medicine
Claros CC, Anderson MN, Qian W, Brockmeier AJ, Buckley TA
2025-03-27
Background Emerging evidence indicates an elevated risk of post-concussion musculoskeletal injuries in collegiate athletes; however, identifying athletes at highest risk remains to be elucidated. Objective The purpose of this study was to model post-concussion musculoskeletal injury risk in collegiate athletes by integrating a comprehensive set of variables by machine learning. Methods A risk model was developed and tested on a dataset of 194 athletes (155 in the training set and 39 in the test set) with 135 variables entered into the analysis, which included participant’s heath and athletic history, concussion injury and recovery-specific criteria, and outcomes from a diverse array of concussion assessments. The machine learning approach involved transforming variables by the weight of evidence method, variable selection using L1-penalized logistic regression, model selection via the Akaike Information Criterion, and a final L2-regularized logistic regression fit. Results A model with 48 predictive variables yielded significant predictive performance of subsequent musculoskeletal injury with an area under the curve of 0.82. Top predictors included cognitive, balance, and reaction at baseline and acute timepoints. At a specified false-positive rate of 6.67%, the model achieves a true-positive rate (sensitivity) of 79% and a precision (positive predictive value) of 95% for identifying at-risk athletes via a well-calibrated composite risk score. Conclusions These results support the development of a sensitive and specific injury risk model using standard data combined with a novel methodological approach that may allow clinicians to target high injury risk student athletes. The development and refinement of predictive models, incorporating machine learning and utilizing comprehensive datasets, could lead to improved identification of high-risk athletes and allow for the implementation of targeted injury risk reduction strategies by identifying student athletes most at risk for post-concussion musculoskeletal injury.
Collegiate Participation in Repetitive Head Impact Sports does not Adversely Affect Gait Dual Task Cost
Journal of Head Trauma Rehabilitation
Buckley TA, Williams K, Oldham JR, Hunzinger KJ, Passalugo S, Anderson MN, Bodt B, Gallo CA, Bryk KN, Munkasy BA
2025-09-03
Objectives: The purpose of this study was to assess gait related dual task cost (DTC) changes over the course of a collegiate athletic career in both repetitive head impact (RHI) exposed and non-RHI exposed athletes. Participants: We recruited 47 NCAA intercollegiate athletes and grouped by RHI exposed (N = 27) and non-RHI (N = 20) sports. Design: Participants completed 5 trials of single task (ST) and 5 trials of dual task (DT) gait with a working memory cognitive challenge both prior to their collegiate athletic careers (pre) and then again after they completed their collegiate athletic careers (post) (mean 1173 ± 341 days between tests) in this prospective longitudinal design. To assess for changes over the course of a career, separate 2 (group: RHI, non-RHI) × 2 (time: pre, post) mixed design ANOVA were performed for each dependent variable of interest (DTC gait velocity and DTC step length) and the model was adjusted for concussion history at the time of test and sex. Main Measures: Gait velocity and step length DTC. Results: There were no significant group by time interactions for DTC gait velocity (F = 0.517, P = .476, η2 = 0.012) or DTC step length ((F = 0.206, P = .652, η2 = 0.005). Conclusions: The primary finding of this study indicated no difference between RHI exposed and non-RHI exposed athletes gait DTC performance between the beginning and conclusion of their collegiate athletic careers. While the long-term effects of RHI remain to be fully determined, these results suggest that RHI may not adversely affect ST or DT gait performance when the individual is young.
Multifaceted concussion assessment battery: sensitivity at the expense of specificity?
The Physician and Sportsmedicine
Slocum C, Langdon JL, Munkasy BA, Brewer B, Oldham JR, Graham V, Buckley TA
2024-12-23
A multifaceted assessment battery is recommended for testing suspected concussed athletes; however, the individual tests have limitations and potentially may lead to false positive outcomes. Therefore, the purpose of this study was to psychometrically evaluate concussion assessment tools used for intercollegiate student-athletes, with a focus on the time interval between baseline and subsequent assessments. Methods: Ninety-two collegiate student-athletes matched between concussion (N = 46. F32/M14) and non-concussion (N = 46, 32F/14 M) completed the standard assessment of concussion, balance error scoring system, symptom questionnaire, and computerized neurocognitive tests at baseline and acutely (
Concussion Recovery: Dual Task Performance and Prioritization
Physician and Sports Medicine
Munkasy BA, Bockelman K, Jangdon JL, Buckley TA.
2025-12-01
Objectives: The objective of this study was to assess a clinically feasible DT protocol consisting of the Balance Error Scoring System (BESS) and Standard Assessment of Concussion (SAC) administered simultaneously during and beyond clinically determined concussion recovery. Method: We recruited 28 collegiate student-athletes (14 post-concussion, 14 control) who performed a DT BESS and SAC assessment at three timepoints: 1) clinical recovery, 2) return to play (RTP) day, and 3) 30 days post-concussion. Scores on each component were assessed with a linear mixed model ANOVA with repeated measures and task prioritization was assessed with a Chi-Square. Results: There was not a significant group by time interaction for the BESS (F: 0.48, p = 0.625, ή2 = 0.018) or SAC (F: 1.927, p = 0.156, ή2 = 0.069), but there was a significant difference in task prioritization at RTP (χ2: 13.4, p = 0.010). Conclusion: While group performance did not differ over time, the concussion participants had a range of task prioritizations at RTP, including mutual interference, which could help identify athletes with incomplete neurological recovery.
Integrative Data Analysis to Identify Persistent Post-Concussion Deficits and Subsequent Musculoskeletal Injury Risk.
National Institute of Health
In the year following a concussion, there is an increased risk of musculoskeletal injuries such as sprains and strains. While the cause of these injuries isn't clear, the goal of this project was to use sophisticated statistical analyses to identify which athletes are at highest risk for these injuries. The results of these studies may be used to reduce injury risk in athletes who have had a concussion.
This program pairs Veterans with current Collegiate Athletes for a 12-week long exercise program to improve the Veteran's Health Related Quality of Life.
Gamified Concussion Assessment
State Space Labs
2021-2022
Service Academy Longitudinal mTBI Outcomes Study (SALTOS)
Henry M. Jackson Foundation for the Advancement of Military Medicine
