A School-Based Injury Prevention Program to Reduce Sport Injury Risk and Improve Healthy Outcomes in Youth
Bibliographic record
Abstract
OBJECTIVE: To examine a school-based high-intensity neuromuscular training (NMT) program in reducing sport injury risk and improving fitness in youth. PARTICIPANTS: Students (ages 11-15) (n = 725) in physical education (PE) classes were randomized by school to intervention or control groups. INTERVENTION: A 12-week high-intensity NMT program (including aerobic, strength, balance, and agility components) was designed to reduce sport injury risk and improve measures of fitness. The control program was a standard of practice warm-up (including running and stretching). RESULTS: A Poisson regression model using an intent-to-treat analysis demonstrated a reduced risk of sport injury: incidence rate ratio (IRR)all injury = 0.30 (95% CI, 0.19-0.49), IRRlower extremity injury = 0.31 (95% CI, 0.19-0.51), IRRankle sprain injury = 0.27 (95% CI, 0.15-0.50), and IRRknee sprain injury = 0.36 (95% CI, 0.13-0.98). A change in waist circumference: -0.99 centimeters (95% CI, -1.84 to -0.14) and an increase in indirect measures of aerobic fitness: 1.28 mL·kg·min (95% CI, 0.66-1.90) in the intervention school compared with the control school also occurred. CONCLUSIONS: A NMT program in junior high school PE class was efficacious in reducing sport-related injury and improving measures of adiposity and fitness in the intervention group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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".