Flexibility training and the repeated-bout effect: priming interventions prior to eccentric training of the knee flexors
Bibliographic record
Abstract
Both the repeated-bout effect and increased flexibility have been linked to reduced muscle damage, fatigue, and strength loss after intense eccentric exercise. Our purpose was to compare the eccentric-training (ECC) response after first priming the muscles with either static flexibility training or a single intense bout of eccentric exercise. Twenty-five participants were randomly assigned to flexibility training (n = 8; 3×/week; 30 min/day), a single bout of intense eccentric exercise (n = 9), or no intervention (control; n = 8) during a 4-week priming phase, prior to completing a subsequent 4-week period of eccentric training of the knee flexors. Testing was completed prior to the priming phase, before ECC, during acute ECC (0 h, 24 h, and 48 h after bouts 1 and 4), and after ECC. Measures included muscle thickness (MT; via ultrasound); isometric, concentric, and eccentric strength; muscle power (dynamometer); electromyography; range of motion; optimal angle of peak torque; and soreness (visual analog scale). Flexibility training and single-bout groups had 47% less soreness at 48 h after the first bout of ECC compared with control (p < 0.05). The flexibility training group had 10% less soreness at 48 h after the fourth ECC bout compared with both the single-bout and control groups (p < 0.05). Isometric strength loss was attenuated for the flexibility training group (-9%) after the fourth ECC bout compared with control (-19%; p < 0.05). All groups had similar increases in strength, MT, and power after ECC (p < 0.05). Prior flexibility training may be more effective than a single session of eccentric exercise in reducing adverse symptoms during the acute stages of eccentric training; however, these benefits did not translate into greater performance after training.
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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) | 0.001 | 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) | 0.002 | 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".