Chronic Effects of Static Stretching Exercises on Muscle Strength and Power in Healthy Individuals Across the Lifespan: A Systematic Review with Multi-level Meta-analysis
Bibliographic record
Abstract
BACKGROUND: The current literature on the chronic effects of static stretching (SS) exercises on muscle strength and power is unclear and controversial. OBJECTIVE: We aimed to examine the chronic effects of SS exercises on muscle strength and power as well as flexibility in healthy individuals across the lifespan. DESIGN: Systematic review with meta-analysis of (randomized) controlled trials. DATA SOURCES: A systematic literature search was conducted in the databases PubMed, Web of Science, Cochrane Library, and SPORTDiscus up to May 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included studies that investigated the chronic effects of SS exercises on at least one muscle strength and power outcome compared to an active/passive control group or the contralateral leg (i.e., using between- or within-study designs, respectively) in healthy individuals, irrespective of age, sex, and training status. RESULTS: The main findings of 41 studies indicated trivial-to-small positive effects of chronic SS exercises on muscle strength (standardized mean difference [SMD] = 0.21, [95% confidence interval 0.10-0.32], p = 0.001) and power (SMD = 0.19, 95% confidence interval 0.12-0.26], p < 0.001). For flexibility, moderate-to-large increases were observed (SMD = 0.96, [95% confidence interval 0.70-1.22], p < 0.001). Subgroup analyses, taking the participants' training status into account, revealed a larger muscle strength improvement for sedentary (SMD = 0.58, p < 0.001) compared with recreationally active participants (SMD = 0.16, p = 0.029). Additionally, larger flexibility gains were observed following passive (SMD = 0.97, p < 0.001) compared with active SS exercises (SMD = 0.59, p = 0.001). The chronic effects of SS on muscle strength were moderated by the proportion of female individuals in the sample (β = 0.004, p = 0.042), with higher proportions experiencing larger gains. Other moderating variables included mean age (β = 0.011, p < 0.001), with older individuals showing larger muscle strength gains, and the number of repetitions per stretching exercise and session (β = 0.023, p = 0.004 and β = 0.013, p = 0.008, respectively), with more repetitions associated with larger muscle strength improvements. Muscle power was also moderated by mean age (β = 0.006, p = 0.007) with larger gains in older individuals. The meta-regression analysis indicated larger flexibility gains with more repetitions per session (β = 0.094, p = 0.016), more time under stretching per session (β = 0.090, p = 0.026), and more total time under stretching (β = 0.078, p = 0.034). CONCLUSIONS: The main findings indicated that chronic SS exercises have the potential to improve muscle strength and power. Such improvements appear to benefit sedentary more than recreationally active participants. Likewise, chronic SS exercises result in a marked enhancement in flexibility with larger effects of passive, as compared with active, SS. The results of the meta-regression analysis for muscle strength indicated larger benefits of chronic SS exercises in samples with higher proportions of female, older participants, and a higher number of repetitions per stretching exercise and session. For muscle power, results suggested larger gains for older participants. Regarding flexibility, findings indicated larger benefits following a higher number of repetitions per exercise and a longer time under stretching per session as well as a longer total time under stretching.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".