Effects of an Injury Prevention Program on Anterior Cruciate Ligament Injury Risk Factors in Adolescent Females at Different Stages of Maturation
Bibliographic record
Abstract
The ideal timing to implement anterior cruciate ligament injury prevention programs with respect to maturation is unclear. The purpose of this study was to investigate the effects of an injury prevention program on knee mechanics in early-, late-, and post-pubertal females. In the study, 178 adolescent female basketball players were assigned to six groups: early-pubertal training, early-pubertal control, late-pubertal training, and late-pubertal control, post-pubertal training, and post-pubertal control. The training groups performed an injury prevention program for six months. Medial knee displacement, knee flexion range of motion, and the probability of high knee abduction moment were assessed before and after the training period. After the six-month training period, medial knee displacement was significantly increased in the early-pubertal control group whereas it was unchanged in the early-pubertal training group. Knee flexion range of motion was significantly decreased in the early-pubertal control group whereas it did not change in the early-pubertal training group. The probability of high knee abduction moment was increased in the early-pubertal control group whereas it was unchanged in the earl-pubertal training group. The probability of high knee abduction moment was also decreased in the post-pubertal training group whereas it did not change in the post-pubertal control group. The program limited the development of high-risk movement patterns associated with maturation in early puberty while improving the knee mechanics in post-pubertal adolescents. Therefore, an injury prevention program should be initiated in early puberty and continue through the post-puberty years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".