Seven weeks of pectoralis muscle stretching does not induce non‐local effects in dorsiflexion ankle range of motion
Bibliographic record
Abstract
Abstract Both an acute bout, as well as chronic static stretching (SS), can increase the joint range of motion (ROM). However, ROM increases of a non‐stretched muscle (non‐local) are reported following an acute SS session, and these effects have not been studied for long‐term SS training. Therefore, this study aimed to investigate the effects of a comprehensive 7‐week SS training program of the pectoralis muscles on ankle dorsiflexion ROM. Thirty‐three healthy, physically active participants (20 male and 13 female) were assigned to either the SS (n = 18) or the control (n = 15) group. The SS group performed a 7‐week SS intervention that comprised three sessions a week, including three exercises of the pectoralis muscles for 5‐min each. Before and after the intervention period, the ankle dorsiflexion ROM was tested with a dynamometer. There was no significant time (p = 0.93, F1,31 = 0.008; η2 = 0.000) or time x group effect (p = 0. 56, F1,31 = 0.342; η2 = 0.011) in ankle dorsiflexion ROM, indicating no changes in ROM in the intervention as well as the control group. Although previous studies on the acute effects of stretching reported non‐local increases in ROM, our study showed no such changes after 7 weeks of SS training. Consequently, if the goal is to chronically increase the ROM of a specific joint, it is recommended to directly stretch the muscles of interest.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".