Influence of 8-weeks of supervised static stretching or resistance training of pectoral major muscles on maximal strength, muscle thickness and range of motion
Bibliographic record
Abstract
Abstract Objectives Current research suggests static stretch-induced maximal strength increases and muscle hypertrophy with potential to substitute resistance-training routines. However, most studies investigated the plantar flexors. This study explored the effects of a static stretching program on maximal strength, hypertrophy and flexibility of the pectoralis major and compared the effects with those of traditional resistance training. Methods Eighty-one (81) active participants were allocated to either a static stretching, strength-training or control group. Pectoralis stretching was applied 15 min/day, 4 days per week for 8 weeks, while resistance training trained 3 days per week, 5 × 12 repetitions. Results There was an increase in all parameters (strength: p < 0.001, ƞ 2 = 0.313, muscle thickness: p < 0.001, ƞ 2 = 0.157–0.264, flexibility: p < 0.001, ƞ 2 = 0.316) and a time*group interaction (strength: p = 0.001, ƞ 2 = 0.154, muscle thickness: p = 0.008–0.001, ƞ 2 = 0.117–0.173, flexibility: p < 0.001, ƞ 2 = 0.267). Post-hoc testing showed no difference between both intervention groups regarding maximal strength and muscle thickness ( p = 0.905–0.983, d = 0.036–0.087), while flexibility increased in the stretching group ( p = 0.001, d = 0.789). Conclusion Stretching showed increases in maximal strength and hypertrophy, which were comparable with commonly used resistance training. Based on current literature, the influence of mechanical tension as the underlying mechanism is discussed. Furthermore, as equipment and comparatively long stretching durations are requested to induce meaningful strength increases in recreationally active participants, practical application seems limited to special circumstances.
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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) | 0.003 | 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".