Economic impact study: neuromuscular training reduces the burden of injuries and costs compared to standard warm-up in youth soccer
Bibliographic record
Abstract
BACKGROUND: There is randomised controlled trial (RCT) evidence that neuromuscular training (NMT) programmes can reduce the risk of injury in youth soccer. We evaluated the cost-effectiveness of such an NMT prevention strategy compared to a standard of practice warm-up. METHODS: A cost-effectiveness analysis was conducted alongside a cluster RCT. Injury incidence rates were adjusted for cluster using Poisson regression analyses. Direct healthcare costs and injury incidence proportions were adjusted for cluster using bootstrapping. The joint uncertainty surrounding the cost and injury rate and proportion differences was estimated using bootstrapping with 10 000 replicates. RESULTS: Along with a 38% reduction in injury risk (rate difference=-1.27/1000 player hours (95% CI -0.33 to -2.2)), healthcare costs were reduced by 43% in the NMT group (-$689/1000 player hours (95% CI -$1741 to $234)) compared with the control group. 90% of the bootstrapped ratios were in the south-west quadrant of the cost-effectiveness plane, showing that the NMT programme was dominant (more effective and less costly) over standard warm-up. Projecting results onto 58 100 Alberta youth soccer players, an estimated 4965 injuries and over $2.7 million in healthcare costs would be conservatively avoided in one season with implementation of a neuromuscular training prevention programme. CONCLUSIONS: Implementation of an NMT prevention programme in youth soccer is effective in reducing the burden of injury and leads to considerable reduction in costs. These findings inform practice and policy supporting the implementation of NMT prevention strategies in youth soccer nationally and internationally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".