Helmet Fit Assessment and Concussion Risk in Youth Ice Hockey Players: A Nested Case-Control Study
Bibliographic record
Abstract
CONTEXT: Injury surveillance has shown that concussions are the most common injury in youth ice hockey. Research examining the criteria for ensuring the correct fit of protective equipment and its potential relationship with concussion risk is very limited. OBJECTIVE: To evaluate the association between helmet fit and the odds of experiencing a concussion among youth ice hockey players. DESIGN: Nested case-control within a cohort study. SETTING: Calgary, Alberta, Canada. PATIENTS OR OTHER PARTICIPANTS: Data were collected for 72 concussed, 41 nonconcussion-injured, and 62 uninjured ice hockey players aged 11 to 18 years. MAIN OUTCOME MEASURE(S): Helmet-fit assessments were conducted across players and encompassed helmet specifications, condition, certification, and criteria measuring helmet fit. Using a validated injury-surveillance system, we identified participants as players with suspected concussions or physician-diagnosed concussions or both. One control group comprised players who sustained nonconcussion injuries, and a second control group comprised uninjured players. Helmet-fit criteria (maximum score = 16) were assessed for the concussed players and compared with each of the 2 control groups. The primary outcome was dichotomous (>1 helmet-fit criteria missing versus 0 or 1 criterion missing). Logistic and conditional logistic regression were used to investigate the effect of helmet fit on the odds of concussion. RESULTS: The primary analysis (54 pairs matched for age, sex, and level of play) suggested that inadequate helmet fit (>1 criterion missing) resulted in greater odds of sustaining a concussion when comparing concussed and uninjured players (odds ratio [OR] = 2.67 [95% CI = 1.04, 6.81], P = .040). However, a secondary unmatched analysis involving all participants indicated no significant association between helmet fit and the odds of sustaining a concussion when we compared concussed players with nonconcussion-injured players (OR = 0.98 [0.43, 2.24], P = .961) or uninjured players (OR = 1.66 [0.90, 3.05], P = .103). CONCLUSIONS: Inadequate helmet fit may affect the odds of sustaining a concussion in youth ice hockey players. Future investigators should continue to evaluate this relationship in larger samples to inform helmet-fit recommendations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".