Self–Myofascial Release: No Improvement of Functional Outcomes in “Tight” Hamstrings
Bibliographic record
Abstract
PURPOSE: Self-myofascial release (SMR) is a common exercise and therapeutic modality shown to induce acute improvements in joint range of motion (ROM) and recovery; however, no long-term studies have been conducted. Static stretching (SS) is the most common method used to increase joint ROM and decrease muscle stiffness. It was hypothesized that SMR paired with SS (SMR+SS) compared with SS alone over a 4-wk intervention would yield greater improvement in knee-extension ROM and hamstring stiffness. METHODS: 19 men (22 ± 3 y) with bilateral reduced hamstring ROM had each of their legs randomly assigned to either an SMR+SS or an SS-only group. The intervention consisted of 4 repetitions of SS each for 45 s or the identical amount of SS preceded by 4 repetitions of SMR each for 60 s and was performed on the respective leg twice daily for 4 wk. Passive ROM, hamstring stiffness, rate of torque development (RTD), and maximum voluntary contraction (MVC) were assessed pre- and postintervention. RESULTS: Passive ROM (P < .001), RTD, and MVC (P < .05) all increased after the intervention. Hamstring stiffness toward end-ROM was reduced postintervention (P = .02). There were no differences between the intervention groups for any variable. CONCLUSION: The addition of SMR to SS did not enhance the efficacy of SS alone. SS increases joint ROM through a combination of decreased muscle stiffness and increased stretch tolerance.
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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 | 0.001 | 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) | 0.006 | 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".