Investigation of a Three-Week Neuromuscular Training Intervention on Biomechanical Parameters of the Lower Quarter in Female Collegiate Pivoting Athletes
Bibliographic record
Abstract
Background/Purpose: Mounting evidence has illuminated the efficacy of neuromuscular training (NMT) interventions to improve biomechanics related to anterior cruciate ligament (ACL) injury during dynamic pivoting movements.This investigation examined the strength, dynamic balance, and biomechanics of the lower quarter during select functional movement assessments in female collegiate athletes before and after a three-week NMT intervention with additional investigation of the influence of the training on a power-based motion correlated to sport performance.Study Design: Nonrandomized Controlled Follow-up Study.Methods: 17 Division I NCAA female soccer players aged 18 -21 participated, averaging a height of 167.79 cm and weight of 65.87 kg.Hip strength was measured with hand dynamometry.Single-leg stance modified balance (SLS M ) was measured with eyes closed and in static heel rise conditions.A Noraxon MyoMotion system assessed peak hip and knee excursion during select movement assessments.Vertical jump height was recorded.Six one-hour NMT sessions for lower quarter training were performed over three weeks.Tests were then repeated.Results: Significant improvements on post-intervention were found in hip abduction strength bilaterally (p = 0.000) and hip extension strength in both right (p = 0.002) and left (p = 0.000) lower extremities.Analysis of data also revealed significant improvements in SLS M with eyes-closed for the right lower extremity (p = 0.002) and left (p = 0.000), as well as SLS M with heel rise bilaterally (p = 0.000).Vertical jump height improved significantly (p = 0.000).Hip abduction ROM during single-leg squat (p = 0.001) and knee flexion during single-leg jump tests (p = 0.001) also increased significantly in post-intervention.
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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) | 0.001 | 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) | 0.002 | 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".