Stretch-induced hypoalgesia: a pilot study
Bibliographic record
Abstract
Objectives Stretching is an intervention often used in various kinds of rehabilitation protocols and the effects on pain sensitivity has sparsely been investigated, especially when addressing potential effects on pain. The objective is to investigate the immediate effects of an axial and peripheral prolonged stretch on pressure pain sensitivity (PPT) and temporal summation (TS) on local and distal sites in healthy subjects. Methods Twenty-two healthy volunteers were recruited to participate in this pilot study. Two prolonged stretching protocols were performed: low back and wrist extensors stretches. PPT and pinprick TS were measured pre- and post-intervention at local and remote sites. Repeated measures analysis of variance (ANOVA) was used to examine the effects and significance of the interventions. Results The low back stretch induced an increase in PPT for both local and remote sites, and the wrist stretch produced a PPT increase only at the local site. TS did not change. Conclusions Low back stretching induced an increase in PPT at both local and remote sites whereas the wrist stretch only increased PPT locally, suggesting hypoalgesia at these sites. Further studies are needed to confirm the effect and mechanisms using randomised, controlled and parallel study design. Considering that pain sensitivity is different than clinical pain, results are difficult to extrapolate to clinical practice. Future studies testing clinical pain are needed to better understand the clinical implication of these results.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".