The comparison of the effects of percussive massage therapy, foam rolling and hamstring stretching on flexibility, knee range of motion, and jumping performance in junior athlete: a randomized controlled trial
Bibliographic record
Abstract
Abstract Background Before every sporting event, almost all athletes engage in a routine practice of warming up to prepare the body for peak performance. There has been a surge in popularity within the athletic world around the use of percussive massage therapy (PMT). Objectives The objectives of this study were to see if using percussive massage therapy, foam rolling (FR), and hamstring stretching (HStr) as part of a warm-up routine had any acute effects on flexibility, jumping performance, and range of motion in junior athletes, and if so, whether there was a significant difference in the acute effects of these treatment methods. Methods Thirty-nine junior athletes with at least 3 years of experience, male gender, age range above 17, seated flexion test < 40 cm, and a willingness to participate were all considered for admittance. Participants were randomly divided into three groups. Before and after the treatment, the seated flexion test, vertical jump test, active SLR, and active knee extension were measured. Results The study found significant improvement in all three groups when comparing them within the groups in the sit and reach test (PMT p < 0.001, FR p = 0.002, and HStr p = 0.001), active SLR (PMT p < 0.001, FR p < 0.001, and HStr p = 0.001), active knee extension (PMT p < 0.001, FR p = 0.002, and HStr p = 0.004), and vertical jump test (PMT p < 0.001, FR p = 0.011, and HStr ( p < 0.001). Comparisons between groups showed significant differences among PMT vs. FR ( p = 0.041) in vertical jump height and PMT vs. HStr ( p = 0.034) in active SLR. Conclusion We detected a notable disparity in hamstring flexibility between the PMT and FR groups, as well as in vertical jump height between the PMT and HStr groups. However, there was no apparent alteration in active knee extension in all three groups.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".