Effects of dynamic and static stretching within general and activity specific warm-up protocols.
Bibliographic record
Abstract
The purpose of the study was to determine the effects of static and dynamic stretching protocols within general and activity specific warm-ups. Nine male and ten female subjects were tested under four warm-up conditions including a 1) general aerobic warm-up with static stretching, 2) general aerobic warm-up with dynamic stretching, 3) general and specific warm-up with static stretching and 4) general and specific warm-up with dynamic stretching. Following all conditions, subjects were tested for movement time (kicking movement of leg over 0.5 m distance), countermovement jump height, sit and reach flexibility and 6 repetitions of 20 metre sprints. Results indicated that when a sport specific warm-up was included, there was an 0.94% improvement (p = 0.0013) in 20 meter sprint time with both the dynamic and static stretch groups. No such difference in sprint performance between dynamic and static stretch groups existed in the absence of the sport specific warm-up. The static stretch condition increased sit and reach range of motion (ROM) by 2.8% more (p = 0.0083) than the dynamic condition. These results would support the use of static stretching within an activity specific warm-up to ensure maximal ROM along with an enhancement in sprint performance. Key pointsActivity specific warm-up may improve sprint performance.Static stretching was more effective than dynamic stretching for increasing static range of motion.There was no effect of the warm-up protocols on countermovement jump height or movement time.
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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 | 0.000 | 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) | 0.000 | 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".