Diagnosis and Management of Mild TBI via Eye Tracking

Neurology ◽  
2021 ◽  
Vol 98 (1 Supplement 1) ◽  
pp. S14.2-S14
Author(s):  
Jeannie Lee ◽  
Brandon Wei ◽  
Summre Blakely ◽  
Benedicto C. Baronia

ObjectiveThe purpose of this study is to expose the prevalence of mild traumatic brain injuries among high school football players and to explore the possibility of implementing eye tracking performance as an objective way to assess cases of potential concussion.BackgroundConcussions are one of the most common forms of traumatic brain injury (TBI). Unfortunately, current research suggests that mild TBIs cannot always be accurately diagnosed via routine neurologic examination. Also, most evaluations, such as ImPACT, are survey-style assessments that are time intensive and subjective. Lack of an objective method to rapidly assess concussions on the field raises concern for second-impact syndrome (SIS), which can lead to permanent brain damage or even fatality.Design/MethodsThis multi-part study included a population of 849 high school athletes in from Lubbock, TX. Student athletes filled out a baseline concussion survey, then assessed their eye tracking performance with the EyeGuide Focus, a 10-second test that involves visually tracking a continuous, figure-8 shape. A vector-based system was used to measure the eye-tracking deviation.ResultsForty-two athletes were recorded with a baseline eye-tracking score, and a subsequent eye-tracking score that was labelled as a suspected concussion by a physician. Of those 42, 17 had a follow-up eye-tracking test 2 weeks later. Test scores labelled with suspected concussion had a significantly higher mean raw score than the baseline score. Higher scores indicate greater vector deviation from accurately tracing the figure-8 with the eyes.ConclusionsThe survey results show underdiagnosing of concussions at lower levels of youth sports, which may indicate a lack of resources. As the data shows marked changes between the concussed, baseline, and follow-up scores, eye-tracking promises to be a quick and efficient tool to assess sports-related concussions.

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Jessie R. Oldham ◽  
Christina L. Master ◽  
Gregory A. Walker ◽  
William P. Meehan ◽  
David R. Howell

Author(s):  
Jason Stamm ◽  
Brandon Boatwright

Using a theoretical underpinning of parasocial interaction—BIRGing (basking in reflected glory) and CORFing (cutting off reflected failure)—this study explored fan reactions to high school athletes’ commitments to play football for National Collegiate Athletic Association Division I programs. A thematic analysis of tweets made by fans during the 2020 recruiting period was examined in two stages: (a) tweets directed toward recruits before they committed to a program and (b) tweets directed toward recruits after they committed. Findings show fan frivolity in regard to identification, as well as a desire to become part of the recruiting process of high school football players. In addition, results yield the possibility of a shift in athlete motivations for social media use, fan association with athletics programs, and how fans cope with unexpected loss. Theoretical and practical implications are further discussed.


2019 ◽  
Vol 58 (13) ◽  
pp. 1409-1414
Author(s):  
Joshua N. Berkowitz ◽  
Asheley Cockrell Skinner ◽  
Jacob A. Lohr

This article determines the prevalence of obesity among high school football players nationwide and compares obesity between position groups of football players and across team sports. We calculate body mass index (BMI) for 391 212 males participating in baseball, basketball, football, lacrosse, and soccer, then stratify BMI into commonly accepted categories and subdivide football players by position played, comparing BMI across position groups and sports. A total of 47.4% of high school football players are healthy weight (BMI = 18.5-24.9 kg/m2), 18.0% have obesity (BMI = 30-34.9 kg/m2: 12.4%) or class 2 obesity (BMI >34.9 kg/m2: 5.6%). Among linemen, 14.8% are healthy weight, 14.6% have class 2 obesity, and another 29.3% have obesity. Among non-linemen, the combined prevalence of obesity and class 2 obesity is 2.7%, comparable to other team sports. Obesity is common among high school football players, more so than among other high school athletes. Obesity and class 2 obesity are only common among linemen.


2013 ◽  
Vol 10 (2) ◽  
pp. 160-169 ◽  
Author(s):  
Marcus A. Badgeley ◽  
Natalie M. McIlvain ◽  
Ellen E. Yard ◽  
Sarah K. Fields ◽  
R. Dawn Comstock

Background:With more than 1.1 million high school athletes playing annually during the 2005−06 to 2009−10 academic years, football is the most popular boys’ sport in the United States.Methods:Using an internet-based data collection tool, RIO, certified athletic trainers (ATs) from 100 nationally representative US high schools reported athletic exposure and football injury data during the 2005−06 to 2009−10 academic years.Results:Participating ATs reported 10,100 football injuries corresponding to an estimated 2,739,187 football-related injuries nationally. The injury rate was 4.08 per 1000 athlete-exposures (AEs) overall. Offensive lineman collectively (center, offensive guard, offensive tackle) sustained 18.3% of all injuries. Running backs (16.3%) sustained more injuries than any other position followed by linebackers (14.9%) and wide receivers (11.9%). The leading mechanism of injury was player-player contact (64.0%) followed by player-surface contact (13.4%). More specifically, injury occurred most commonly when players were being tackled (24.4%) and tackling (21.8%).Conclusions:Patterns of football injuries vary by position. Identifying such differences is important to drive development of evidence-based, targeted injury prevention efforts.


1994 ◽  
Vol 22 (6) ◽  
pp. 859-862 ◽  
Author(s):  
Henry N. Williford ◽  
Jane Kirkpatrick ◽  
Michele Scharff-Olson ◽  
Daniel L. Blessing ◽  
Nai Zhen Wang

2011 ◽  
Vol 13 (5) ◽  
pp. 515-535 ◽  
Author(s):  
Joshua D. Pitts ◽  
Jon Paul Rezek

Despite the financial and cultural importance of intercollegiate athletics in the United States, there is a paucity of research into how athletic scholarships are awarded. In this article, the authors empirically examine the factors that universities use in their decision to offer athletic scholarships to high school football players. Using a Zero-Inflated Negative Binomial (ZINB) model, the authors find a player’s weight, height, body mass index (BMI), race, speed, on-the-field performance, and his high school team’s success often have large and significant impacts on the number of scholarship offers he receives. There is also evidence of a negative relationship between academic performance and scholarship offers. In addition, the authors find evidence of a scholarship premium for players from Florida and Texas. The results also show that running backs, wide receivers, and defensive backs appear to generate the most attention from college football coaches, other things equal.


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