Investigation of an Eight-Week Neuromuscular Training Intervention on Biomechanical Parameters of the Lower Quarter in Adolescent Female Soccer Players
Bibliographic record
Abstract
Purpose: Mounting evidence supports the implementation of neuromuscular training (NMT) interventions to improve biomechanical profiles for prevention of musculoskeletal injury in dynamic pivoting athletes.Research has demonstrated there is a clear link between functional movement behavior and vulnerability to injury.However, there is limited research examining the capacity of NMT to positively influence pathomechanical movement behavior.This investigation assessed the strength, balance, and functional biomechanics of uninjured adolescent female athletes following an eight-week NMT intervention, which was conducted in order to expand upon research aimed at injury prevention in the lower quarter.Methods: 37 female soccer players ages 10 -15 participated.Hip strength was measured with hand dynamometry, and single-leg stance modified balance (SLS M ) was measured in multiple conditions.A 3-Dimensional Dynamic Movement Assessment (3D-DMA) system assessed lower quarter joint excursion during select functional loading tasks.Participants completed an 8-week, 16-session NMT intervention followed by repeated measurements.Results: Following the intervention, significant improvements were found in: hip abduction strength bilaterally (p = 0.000), hip extension strength bilaterally (p = 0.000), SLS M in eyes-closed condition bilaterally (p = 0.000), and DMA functional outcomes in the Full Squat Test (p = 0.019), Step-Up Test (p = 0.007), Single-Leg Squat Test (p = 0.000), and Single-Leg Hop Test (p = 0.000).Conclusions: These data indicate an 8-week NMT intervention is sufficient to elicit positive neuromuscular adaptations in the lower quarter associated with pathomechanical loading patterns.Such adaptations support improved function across a diversity of complex sport-related movements.More research is needed to further devel-
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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".