The effect of a national body checking policy change on concussion risk in youth ice hockey players
Bibliographic record
Abstract
Objective To determine if the risk of game-related concussion differs for Pee Wee (11–12 years) ice hockey players in the season following a national policy change disallowing body checking (2013/2014) when compared to a season (2011/2012) when body checking was allowed. Design Historical cohort study. Setting Community ice hockey rinks. Participants Pee Wee players were recruited from 59 teams in all divisions of play in Alberta (n=883) in 2011/12 prior to the rule change and from 73 teams in 2013/14 following the rule change (n=617). Assessment of risk factors Pee Wee ice hockey players before and after a national body checking policy change. Outcome measures Suspected concussions were identified by a team therapist/safety designate and referred to a sport medicine physician. Concussions were included if they met the Zurich 2013 Consensus definition of concussion. Main results There were 104 game-related concussions (IR=2.79/1000 game-hours) in Alberta prior to the rule change and 24 concussions (IR=1.08/1000 game-hours) after. Based on a multivariable Poisson regression model adjusting for player size, age, body checking attitudes, previous injury, level of play, and position, accounting for clustering by team, the rate of concussion declined following the policy change [IRR=0.34 (95% CI; 0.21 – 0.56)]. Overall, a physician diagnosed 67.3% and 79.1% of suspected game concussions in 2011/2012 and 2013/2014, respectively. Conclusions Introduction of the national policy change disallowing body checking in Pee Wee resulted in a 66% reduction in the Alberta Pee Wee ice hockey concussion rate. These findings have important implications for youth ice hockey policy. Competing interests None.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".