Effects of Stretching on Injury Risk Reduction and Balance
Bibliographic record
Abstract
ABSTRACT Evidence for the effectiveness of acute and chronic stretching for improving range of motion is extensive. Improved flexibility can positively impact performances in activities of daily living and both physical and mental health. However, less is known about the effects of stretching on other aspects of health such as injury incidence and balance. The objective of this review is to examine the existing literature in these areas. The review highlights that both pre-exercise and chronic stretching can reduce musculotendinous injury incidence, particularly in running-based sports, which may be related to the increased force available at longer muscle lengths (altered force-length relationship) or reduced active musculotendinous stiffness, among other factors. Evidence regarding the acute effects of stretching on balance is equivocal. Longer-term stretch training can improve balance, which may contribute to a decreased incidence of falls and associated injuries and may thus be recommended as an important exercise modality in those with balance deficits. Hence, both acute and chronic stretching seem to have positive effects on injury incidence and balance, but optimum training plans are yet to be defined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".