Youth Ice Hockey Related Injury and Concussion: Informing Prevention Through Modifiable Risk Factors
Bibliographic record
Abstract
Ice hockey is a popular sport in Canada, yet is considered a high-risk sport for injury. To prevent these injuries, potential risk factors must be identified to inform injury prevention strategies. Further, injury prevention strategies that have been implemented should be evaluated to ensure no unintended injury consequences have occurred. In this dissertation, the potential risk factors for injury and prevention strategies in youth ice hockey are reviewed and limitations of the literature are discussed to help inform the next steps for injury prevention. The association between on-ice skill performance and injury is also examined. This will help provide a better understanding of the potentially modifiable risk factors for injury in youth ice hockey and will further aid in the development of targeted interventions. Additionally, the rates of injury and concussion among under-15 (ages 13-14) ice hockey players playing in leagues allowing body checking, but who have varying years of body checking experience is explored. Finally, the association of body checking experience and rates of injury and concussion in under-18 players (ages 15-17) are assessed. These evaluations will provide important evidence for recent and potentially future body checking policy changes in youth ice hockey. Policy permitting body checking continues to be the most relevant modifiable risk factor in youth ice hockey. A faster time on the transition agility (suggesting higher skill) was associated with a higher rate of injury among 11-17-year-olds. Among 13-14-year-olds participating in a body checking league, there were no significant differences in the rates of injury or concussion among players that had no body checking experience and those that had either 1 year or 2+ years of experience. Among 15-17-year-olds, the adjusted rates of injury and concussion were higher among those with more body checking experience (3 years) than those with less experience (2 years). These studies provide further evidence in support of disallowing body checking in younger age groups in youth ice hockey to reduce injury and concussion rates, with no adverse consequences related to less body checking experience when engaged in leagues allowing body checking in older age groups (ages 13-17).
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".