Body checking in non-elite adolescent ice hockey leagues: it is never too late for policy change aiming to protect the health of adolescents
Bibliographic record
Abstract
OBJECTIVES: The objective of this study is to evaluate the effect of policy change disallowing body checking in adolescent ice hockey leagues (ages 15-17) on reducing rates of injury and concussion. METHODS: This is a prospective cohort study. Players 15-17 years-old were recruited from teams in non-elite divisions of play (lower 40%-70% by division of play depending on year and city of play in leagues where policy permits or prohibit body checking in Alberta and British Columbia, Canada (2015-18). A validated injury surveillance methodology supported baseline, exposure-hours and injury data collection. Any player with a suspected concussion was referred to a study physician. Primary outcomes include game-related injuries, game-related injuries (>7 days time loss), game-related concussions and game-related concussions (>10 days time loss). RESULTS: 44 teams (453 player-seasons) from non-body checking and 52 teams (674 player-seasons) from body checking leagues participated. In body checking leagues there were 213 injuries (69 concussions) and in non-body checking leagues 40 injuries (18 concussions) during games. Based on multiple multilevel mixed-effects Poisson regression analyses, policy prohibiting body checking was associated with a lower rate of injury (incidence rate ratio (IRR): 0.38 (95% CI 0.24 to 0.6)) and concussion (IRR: 0.49; 95% CI 0.26 to 0.89). This translates to an absolute rate reduction of 7.82 injuries/1000 game-hours (95% CI 2.74 to 12.9) and the prevention of 7326 injuries (95% CI 2570 to 12083) in Canada annually. CONCLUSIONS: The rate of injury was 62% lower (concussion 51% lower) in leagues not permitting body checking in non-elite 15-17 years old leagues highlighting the potential public health impact of policy prohibiting body checking in older adolescent ice hockey players.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".