The Effect of a Novel Movement Strategy in Decreasing ACL Risk Factors in Female Adolescent Soccer Players
Bibliographic record
Abstract
There is a need to investigate the effect of specific movement strategies in reducing biomechanical risk factors for anterior cruciate ligament injury in young female athletes. The purpose of this study was (a) to determine the feasibility of implementing a novel movement strategy (Core-PAC) into a team warm-up before soccer training based on subject compliance and integration of the Core-PAC into the warm-up and (b) to determine whether the Core-PAC would improve peak knee flexion angles and peak abduction moments at the knee during a side cut (SC) and an unanticipated side cut (USC) before kicking a soccer ball, and a side hop (SH) task after immediate instruction and after a 4-week training program. A convenience sample of ten 14- to 16-year-old female soccer players were instructed in the Core-PAC immediately after baseline testing and during a training program consisting of a 20-minute warm-up, 2 times per week. The Core-PAC was understood and accepted by the subjects and incorporated into their warm-up activities with good compliance. After the immediate instruction, there were significant increases in peak knee flexion angles of a mean 6.4° during the SC (p = 0.001), 3.5° during the USC (p = 0.007), and 5.8° during the SH (p < 0.001) tasks. Peak knee abduction moments decreased by a mean of 0.25 N·m·kg(-1) during the SC (p < 0.03), 0.17 N·m·kg(-1) during the USC (p = 0.05), and 0.27 N·m·kg(-1) during the SH (p = 0.04) tasks. After the 4-week training program, some individuals showed improvement. The results of this study suggest that the Core-PAC may be 1 method of modifying high-risk movements for ACL injury such as side cutting and single-leg landing.
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 | 0.003 | 0.000 |
| 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 | 0.001 |
| 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".