Mechanisms of Team-Sport-Related Brain Injuries in Children 5 to 19 Years Old: Opportunities for Prevention
Bibliographic record
Abstract
BACKGROUND: There is a gap in knowledge about the mechanisms of sports-related brain injuries. The objective of this study was to determine the mechanisms of brain injuries among children and youth participating in team sports. METHODS: We conducted a retrospective case series of brain injuries suffered by children participating in team sports. The Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) database was searched for brain injury cases among 5-19 year-olds playing ice hockey, soccer, American football (football), basketball, baseball, or rugby between 1990 and 2009. Mechanisms of injury were classified as "struck by player," "struck by object," "struck by sport implement," "struck surface," and "other." A descriptive analysis was performed. RESULTS: There were 12,799 brain injuries related to six team sports (16.2% of all brain injuries registered in CHIRPP). Males represented 81% of injuries and the mean age was 13.2 years. Ice hockey accounted for the greatest number of brain injuries (44.3%), followed by soccer (19.0%) and football (12.9%). In ice hockey, rugby, and basketball, striking another player was the most common injury mechanism. Football, basketball, and soccer also demonstrated high proportions of injuries due to contact with an object (e.g., post) among younger players. In baseball, a common mechanism in the 5-9 year-old group was being hit with a bat as a result of standing too close to the batter (26.1% males, 28.3% females). INTERPRETATION: Many sports-related brain injury mechanisms are preventable. The results suggest that further efforts aimed at universal rule changes, safer playing environments, and the education of coaches, players, and parents should be targeted in maximizing prevention of sport-related brain injury using a multifaceted approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".