Neck Muscle Strength Training In Youth Hockey: Evaluation Of The Research Evidence
Bibliographic record
Abstract
Paediatric concussions in hockey is a major public health concern. Improving the sport readiness of players to safely and effectively participate in ice hockey is one of the essential components to effectively managing the risk for concussion in these athletes. It has been recommended that neck strengthening be included in the general training of these athletes to improve players' capacity to absorb external forces applied to the head and reduce the risk for concussive injury. PURPOSE: To evaluate the merit of this recommendation through a critical appraisal of the existing research evidence regarding the relationship between neck muscle strength and concussion biomechanics, incidence and severity. METHODS: Scoping review of OVID Medline, CINAHL, EBM, SportDiscus and PEDRO databases, 1996 to July, week 3, 2010. Comparative controlled trials and descriptive studies, as well as basic research on concussion mechanics and the developmental biomechanics of the neck were included. RESULTS: Prospective evidence relating neck muscle strength to concussion incidence and severity is not available. There is level 2B and 3B evidence (Oxford Scale) that neck-specific resistance training in healthy adults improves muscles strength and neuromuscular control. Evidence for paediatric athletes is not available. A causal relationship between neck strength and force absorption capacity of the neck is supported by computational studies and expert opinion, but is not supported by cohort studies. There is level 2B evidence regarding the effectiveness of muscle-specific resistance training to enhance short-latency muscle activation and force variables in adults, which could increase the dynamic stability of the neck under external loading conditions. CONCLUSION: Both prospective and high quality experimental studies are needed to fully explore the relevance of strength and neuromuscular training for concussion risk management in youth hockey.
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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 | 0.029 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".