Effect of a Novel Movement Strategy in Decreasing ACL Risk Factors in Female Adolescent Soccer Players
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of a novel movement strategy incorporated within a soccer warm-up on biomechanical risk factors for anterior cruciate ligament injury during 3 sport-specific movement tasks. DESIGN: Single-blind, randomized controlled clinical trial. SETTING: Laboratory setting. PARTICIPANTS: Twenty top-tier female teenage soccer players. INTERVENTIONS: Subjects were randomized to the Core Position and Control movement strategy (Core-PAC) warm-up or standard warm-up, which took place before their regular soccer practice over a 6-week period. The Core-PAC focuses on getting the centre of mass closer to the plant foot or base of support. MAIN OUTCOME MEASURES: Peak knee flexion angle and abduction moments during a side-hop (SH), side-cut, and unanticipated side-cut task after the 6 weeks with (intervention group only) and without a reminder to use the Core-PAC strategy. RESULTS: The Core-PAC group increased peak flexion angles during the SH task [mean difference = 6.2 degrees; 95% confidence interval (CI), 1.9-10.5 degrees; effect size = 1.01; P = 0.034] after the 6-week warm-up program without a reminder. In addition, the Core-PAC group demonstrated increased knee flexion angles for the side-cut (mean difference = 8.5 degrees; 95% CI, 4.8-12.2 degrees; ES = 2.02; P = 0.001) and SH (mean difference = 10.0 degrees; 95% CI, 5.7-14.3 degrees; ES = 1.66; P = 0.001) task after a reminder. No changes in abduction moments were found. CONCLUSIONS: The results of this study suggest that the Core-PAC may be one method of modifying high-risk soccer-specific movements and can be implemented within a practical, team-based soccer warm-up. The results should be interpreted with caution because of the small sample size.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".