Potential Effects of Dynamic Stretching on Injury Incidence of Athletes: A Narrative Review of Risk Factors
Bibliographic record
Abstract
The use of dynamic stretching as a replacement for static stretching in the warm-up is widespread based on the reports of static stretching-induced performance impairments. While acute and chronic static stretching has been reported to reduce musculotendinous injuries, especially with explosive and change of direction actions, the influence of dynamic stretching on injury incidence lacks a similar volume of literature for acute and chronic responses. It was the objective of this narrative review to examine the acute and training effects of dynamic stretching on injury incidence and possible moderating variables such as dynamic stretching effects on range of motion, strength, balance, proprioception, muscle morphology, and psycho-physiological responses. One study demonstrated no significant difference regarding injury incidence when comparing a dynamic stretching-only group versus a combined dynamic stretching plus static stretching group. The only other study examined functional dynamic stretching training with injured dancers and reported improved ankle joint stability. However, several studies have shown that dynamic activity with some dynamic stretching exercises within a warm-up consistently demonstrates positive effects on injury incidence. Regarding moderating variables, while there is evidence that an acute bout of dynamic stretching can enhance range of motion, the acute and training effects of dynamic stretching on strength, balance, proprioception, and musculotendinous stiffness/compliance are less clear. The acute effects of dynamic stretching on thixotropic effects and psycho-physiological responses could be beneficial for injury reduction. However, the overall conflicting studies and a lack of substantial literature compared with SS effects points to a need for more extensive studies in this area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".