The Effect of a 4-Week TRX Suspension Training on Lower Extremity Alignment and Muscle Strength in Male Basketball Players
Bibliographic record
Abstract
Background: This study investigated the effectiveness of a 4-week TRX suspension training program on knee and hip alignment as well as hip muscle strength in male basketball players with dynamic knee valgus. Methods: The present study was Quasi-experimental, and its statistical population consisted of basketball players (18-25 years old) from Mashhad, Iran. Thirty-two athletes diagnosed with dynamic knee valgus were randomly selected as samples and randomly assigned to experimental (n=16) and control (n=16) groups. Data measurement tools included Kinovea software (Kinovea Robotics, Canada, 2006) and an isokinetic dynamometer (JTECH MedicalTM Commander instruments). To measure kinematic angles, athletes performed standardized tasks such as squats and lunges, which were selected to elicit dynamic knee valgus and accurately assess knee and hip alignment. A 4-week TRX suspension training program (3 sessions/week, 30-45 minutes/session) was implemented for the exercise group. Statistical analyses (paired t-tests, ANCOVA) were conducted using SPSS software (p < 0.05). Results: Paired-sample t-tests revealed significant improvements in knee and hip alignment (reduced knee valgus (p=0.003) and hip drop angles (p=0.013)) in the exercise group post-training compared to pre-training. The exercise group's dominant leg also observed significant increases in hip abductor, extensor, and external rotator strength (p=0.0001). Analysis of covariance (ANCOVA) controlling for pre-test scores demonstrated significant between-group differences in all outcome measures, indicating the TRX program's effectiveness in the dynamic knee valgus group compared to the control. Conclusion: This study suggests that a 4-week TRX suspension training program can effectively improve knee and hip alignment and strengthen hip musculature in male basketball players with dynamic knee valgus.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".