HELMET FIT IN YOUTH ICE HOCKEY
Bibliographic record
Abstract
Background Appropriate helmet fit is thought to contribute to the protective effect of helmets in reducing the risk of concussion in sports. Only one previous study has evaluated helmet fit in youth ice hockey; however, inter-rater reliability was not assessed. Objective To evaluate helmet fit in youth ice hockey players and assess inter-rater reliability of helmet fit criteria. Design Self-report and observational evaluations. Setting 2016 Hockey Calgary Summer Day Camps. Participants Canadian youth (11–18 years) ice hockey players. Methods Helmet fit criteria were developed from previously published ice hockey, skiing, snowboarding and motorcycle helmet fit criteria. A total of 60 players underwent self-report and observational helmet fit evaluations by two independent assessors. Inter-rater reliability was assessed using descriptive statistics and Cohen's kappa coefficient. Results Most players rated helmet fit (90%) and comfort (87%) as ‘excellent’ or ‘good’. Most helmets (93%) and cages (84%) displayed the Canadian Standards Association (CSA) sticker or stamp. Only 23% of players satisfied all helmet fit criteria for both assessors; however, 70% of players failed three or fewer criteria across the evaluations of both assessors. The most commonly failed helmet fit criterion was ‘crown of helmet is 1–2 fingers above eyebrows’, which was failed by 22% of players. For inter-rater reliability, the most commonly disputed helmet fit criterion was ‘helmet does not cover eyes when pressing down’, which was disagreed upon by the assessors for 33% of players; however, all other criteria were agreed upon for over 80% of players. Substantial agreement (K>0.8) was found for 19% of helmet fit criteria, whereas 50% of criteria had little agreement beyond chance (K<0.2). Conclusions The majority of youth ice hockey players did not satisfy all helmet fit criteria for both assessors. The association between helmet fit and concussion needs to be investigated.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".