Exercise-induced hypoalgesia – interval versus continuous mode
Bibliographic record
Abstract
Aerobic exercise at approximately 70% of maximal aerobic capacity moderately reduces pain sensitivity and attenuates pain, even after a single session. If the analgesic effects depend on exercise intensity, then high-intensity interval exercise at 85% of maximal aerobic capacity should further reduce pain. The aim of this study was to explore the exercise-induced analgesic effects of high-intensity interval aerobic exercise and to compare them with the analgesic effects of moderate continuous aerobic exercise. Twenty-nine young untrained healthy males were randomly assigned to aerobic-continuous (70% heart rate reserve (HRR)) and interval (4 × 4 min at 85% HRR and 2 min at 60% HRR between cycles) exercise modes, each lasting 30 min. Psychophysical pain tests, pressure and heat pain thresholds (HPT), and tonic heat pain (THP) were conducted before and after exercise sessions. Repeated measures ANOVA was used for data analysis. HPT increased (p = 0.056) and THP decreased (p = 0.013) following exercise unrelated to exercise type. However, the main time effect (pre-/postexercise) was a trend of increased HPT (45.6 ± 1.9 °C to 46.2 ± 1.8 °C; p = 0.082) and a significant reduction in THP (from 50.7 ± 25 to 45.9 ± 25.4 numeric pain scale; p = 0.043) following interval exercise. No significant change was found for the pressure pain threshold following either exercise type. In conclusion, interval exercise (85% HRR) has analgesic effects on experimental pain perception. This, in addition to its cardiovascular, muscular, and metabolic advantages may promote its inclusion in pain management programs.
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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 | 0.000 |
| 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) | 0.003 | 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".