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Evaluation of Concussion Incidence and Modulating Factors in the 2013-2017 Australian Football League.

Ryan Adams | George K Lau | Jennifer B Dai | Adam Y Li | Kevin P Cheung | Syed Haider | Alex Gometz | Alexander F Post | Tanvir F Choudhri
Cureus | 2018

Introduction The increasing awareness and popularization of concussions in the research realm over the last few years have begun to shed more light on the detrimental effects associated with repetitive head trauma. While the majority of the current literature focuses on the National Football League (NFL) and National Hockey League (NHL), several other high-impact sports have been implementing concussion management protocols to protect their players. The Australian Football League (AFL) is a prime example of a major contact sport that has undertaken recent changes to its concussion assessment and management modalities. We recognize the benefit of reporting potential changes in concussion rates over the 2013-2017 AFL seasons. We were interested in some of the factors not yet evaluated before, which may contribute to the overall concussion incidence such as "style-of-play" factors" (home/away, win/loss, points scored, time of season). We hope the results of this analysis shed light on the mechanisms by which concussion rates can be mitigated across major contact sports. Methods Data were obtained from the weekly injury list published by the AFL, a publicly available website. Details of players listed with concussions were collected from regular season games (890 games total) of 18 AFL teams from 2013 to 2017. Weekly injury lists were retrospectively compared using THE AGE, a publicly available newspaper published and owned by Fairfax Media. Data were analyzed utilizing GraphPad Prism 6 (GraphPad Software Inc., CA, US). In addition to descriptive statistics, Fisher's exact tests, Welch's two-tailed t-tests, and correlation tests were used. Alpha level < 0.05 was considered significant for all tests. Results The dataset comprised 236 total concussions between the 2013 and 2017 AFL seasons. We noted a significant increase in the concussion rate (p = 0.0010) between the 2013 and 2017 seasons. This result was complemented by a significant increase in average games missed between the 2014 and 2015 seasons (p = 0.0002); however, this trend was not significant when evaluating the 2013 and 2017 seasons directly (p = 0.0951). Further analysis into the "style of play" factors on concussion incidence, such as average points scored, win/loss, home/away, and time of season, produced non-significant results. Conclusion Our study identified a significant increasing trend in concussion rate and average games missed that correlate to the data analysis in other high-impact sports such as the NFL and NHL. However, further research is necessary to determine if these findings indicate the improvement in concussion management and player safety measures beginning to develop in high-impact sports. We also noted that certain "style of play" factors (points scored, win/loss, home/away, and time of season) have no significant implication on concussion rate during the 2013-2017 AFL seasons. While we consider our data source to be reliable in the reporting of concussions from the AFL, the ideal data set would comprise a medical diagnosis from the team of doctors. It may be possible that our data set is underreporting the total amount of concussions between the 2013 and 2017 AFL seasons. Return-to-play times were not ascertained directly from the team doctor for the clearance date. It may be possible that this data collection modality led to missed cases of head injury or return to play times, which could impact the reliability of our dataset.

Pubmed ID: 30585281

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This is a list of tools and resources that we have found mentioned in this publication.


GraphPad Prism (tool)

RRID:SCR_002798

Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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