The effectiveness of a neuromuscular prevention strategy to reduce injuries in youth soccer: a cluster-randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Soccer is a leading sport for participation and injury in youth. OBJECTIVE: To examine the effectiveness of a neuromuscular prevention strategy in reducing injury in youth soccer players. DESIGN: Cluster-randomised controlled trial. SETTING: Calgary soccer clubs (male or female, U13-U18, tier 1-2, indoor soccer). PARTICIPANTS: Eighty-two soccer teams were approached for recruitment. Players from 60 teams completed the study (32 training (n=380), 28 control (n=364)). INTERVENTION: The training programme was a soccer-specific neuromuscular training programme including dynamic stretching, eccentric strength, agility, jumping and balance (including a home-based balance training programme using a wobble board). The control programme was a standardised warm-up (static and dynamic stretching and aerobic components) and a home-based stretching programme. MAIN OUTCOME MEASURES: Previously validated injury surveillance included injury assessment by a study therapist. The injury definition was soccer injury resulting in medical attention and/or removal from a session and/or time loss. RESULTS: The injury rate in the training group was 2.08 injuries/1000 player-hours, and in the control group 3.35 injuries/1000 player-hours. Based on Poisson regression analysis, adjusted for clustering by team and covariates, the incidence rate ratios (IRR) for all injuries and acute onset injury were 0.62 (95% CI 0.39 to 0.99) and 0.57 (95% CI 0.35 to 0.91). Point estimates also suggest protection of lower extremity, ankle and knee sprain injuries (IRR=0.68 (95% CI 0.42 to 1.11), IRR=0.5 (95% CI 0.24 to 1.04) and IRR=0.38 (95% CI 0.08 to 1.75)). CONCLUSIONS: A neuromuscular training programme is protective of all injuries and acute onset injury in youth soccer players.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".