Abstract
Background:Research into improving player safety of sport-related concussion (SRC) in American football has been an ongoing endeavor. In an attempt to better understand the incidence of SRCs in American football, research has focused on the characteristics of SRC during gameplay. Determining SRC specifics and assessing them quantitatively can help identify high-risk scenarios and predict exposure risk.Purpose:To identify and assess the incidence of SRCs in a National Collegiate Athletic Association football team by comparing field location, player positions, collision partners, and player cues.Study Design:Descriptive epidemiology study.Methods:We used physician sideline reports of diagnosed concussions from a Division I football team from September 2010 to December 2018. Game videos were analyzed to identify the field location where the SRC occurred, collision partner, and player behavior postconcussion. The incidence of in-game SRCs by position was also assessed. We used the “words of estimative probability” model to categorize each concussion as certain, almost certain, probable, or even on the basis of our confidence in identifying them using game film.Results:This study examined 44 SRCs that occurred over 9 seasons. The SRC incidence was significantly higher in the middle defense (5-20 yards from the line of scrimmage) compared with all other field locations (relative risk, 2.46; 95% CI, 1.14-5.29; P < .05). In-game collision partners were most commonly defensive backs. The most common player cue was a hand to helmet/face mask. The positions with the highest SRC incidence by athlete-exposure, game position, and position play belonged to the defensive backs, wide receivers, and running backs.Conclusion:The middle defense had a significantly higher incidence of SRCs than all other field locations. We pose a new method to categorize concussions during video analysis by using words of estimative probability. Knowledge of SRC gameplay characteristics can potentially guide the medical staff and medical observer to better identify them.
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