Concussion and strength performance in youth ice hockey players
Bibliographic record
Abstract
Objective To explore the influence of concussion on strength performance within youth ice hockey players. Design Athletes were assessed prospectively before and after a sport-related concussion and longitudinally across a 3-year period. Setting University research laboratory. Participants 178 unique male and female youth ice hockey players (ages 8–14 years). Nineteen of the 178 participants sustained a concussion while enrolled in the study, where three participants sustained repeated concussions for a total of 23 concussive events. Intervention Participants completed a pre-season/baseline assessment of strength performance annually for up to 3 years. If a concussion was sustained, follow-up assessment on the same measures was. Outcome Measures Lower body and upper body strength performance (leg maximal voluntary contraction, squat jump height, counter movement jump height and hand grip). Results Using a linear mixed-effects model, when accounting for severity of post-concussive symptoms, significant average effects were found for jump height (squat jump: Estimate=−0.05; SE=0.02; t=−2.51; P=0.0186; countermovement jump: Estimate=−0.03; SE=0.02; t=−2.20; P=0.0371) during the symptomatic stage post-concussion and for leg maximal voluntary contraction (Estimate=−1.05; SE=0.47; t=−2.27; P=0.0421) during the asymptomatic stage post-concussion, indicating decreased strength performance following concussion. Conclusions This study acts as an initial step towards better understanding concussion-related strength performance deficits that may limit the on and off ice performance of the youth ice hockey player population. Acknowledgements Ontario Neurotrauma Foundation (ONF). 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".