Injuries in Canadian high school boys’ collision sports: insights across football, ice hockey, lacrosse, and rugby
Bibliographic record
Abstract
Abstract Background Collision sport participation rates among high school youth in Canada are high. While participation is beneficial for physical and mental well-being, the rates of injury in these sports are high. Aims This study aims to compare injury rates and profiles across four common youth collision sports (ice hockey, tackle football, lacrosse, rugby). Methods Data from a cross-sectional questionnaire of 2029 high school youth were used to identify male collision sport participants to be included in this secondary analysis ( n = 360). Results Of the 2029 students who completed the questionnaire, 360 participated in collision-based sports [Ages: 14 (5%), 15 (41%), 16 (25%), 17 (26%), 18 (3%)]. The rates of injury ranged from 12.7 injuries/100 participants/year (rugby) to 33.1 injuries/100 participants/year (ice hockey). Concussion rates ranged from 12.4 (football) to 15.8 (ice hockey) concussions/100 participants/year. Similarities existed in the profile of injuries between sports, with most injuries occurring due to contact with another player (range 57.0% to 87.5%). Injuries to the head (33.3%), wrist/hand (16.0%), shoulder (12.8%), and knee (12.0%) were the most prevalent injury type. Substantial differences in previous playing experience existed between sports. Discussion The high rate of injury and concussion reported across each of these sports highlights the need for the introduction of primary prevention strategies in these sports aimed to reduce the risk of injury.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".