Physical activity and concussion risk in male youth ice hockey players
Bibliographic record
Abstract
Objective To evaluate the association between self-reported physical activity (PA) and concussion incidence in male youth ice hockey players. Design pooled data from three prospective cohort studies. Setting Community ice hockey rinks and sport medicine clinics. Participants PeeWee (ages 11–12), Bantam (ages 13–14), and Midget (ages 15–17) male youth ice hockey players (n=1208). Assesment of risk factors Participants reported six-week physical education and extra-curricular sport participation history upon study entry. Concussion incidence rate ratios [IRRs (95% CI)] associated with 1). total six-week PA volume, and 2). meeting the Canadian PA recommendations of one hour of daily PA (≥42 hours/six weeks) were calculated using multivariable Poisson regression (covariates: age, competition level, concussion history). Models were adjusted for hockey exposure, and cluster by team, study year and city (α<0.05). Outcome measure Medically-diagnosed concussions during the study period. Main results Total PA volume did not affect concussion incidence in male youth ice hockey players [IRR: 0.996 (95% CI: 0.990–1.003]. Concussion incidence was higher in male ice hockey players who did not meet the PA recommendations versus those who met the PA recommendations amongst PeeWee [IRR: 2.94 (95% CI: 1.29–6.66)] and Bantam [IRR: 2.18 (95% CI: 1.12–3.94)] participants, but not amongst Midget participants [IRR: 1.37 (95% CI: 0.72–2.59)]. There was no evidence of confounding or modification by competition level or concussion history. Conclusions While total PA volume was not associated with concussion risk, PeeWee and Bantam male youth ice hockey players whose six-week PA history was below the PA recommendations were at greater risk of concussion. This research will inform future studies examining the mechanism of this association. 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".