Susceptibility to movement-evoked pain following resistance exercise
Bibliographic record
Abstract
OBJECTIVE: To investigate the: (1) role of basic muscle pain sensitivity and psychological factors in the prediction of movement-evoked pain (MEP) following delayed onset muscle soreness (DOMS), and (2) association of MEP with changes in systemic muscle pain sensitivity following DOMS induction. METHODS: Fifty-one participants were assigned to either eccentric resistance exercise or control groups. They completed questionnaires evaluating psychological distress and underwent muscle pain sensitivity evaluation by the pressure pain threshold (PPT) test at the exercised and remote muscles, before and 24 hours following the intervention. MEP intensity was determined in response to lifting a 3kg canister using a visual analogue scale (VAS). RESULTS: The exercise group demonstrated MEP intensity of 5/10 on VAS and reduced PPTs at the main exercised muscle (p<0.001). A regression tree analyses revealed that the level of anxiety trait predicted a higher MEP intensity. A secondary analysis showed that 53% participants who were DOMS responders (MEP > mild intensity; ≥ 3/10 VAS) exhibited decreased PPTs in the exercised (p<0.001) and remote (p = 0.027) muscles following eccentric exercise. Characterization of DOMS responders revealed that, at baseline, they had lower PPTs in the exercised (p = 0.004) and remote (p = 0.001) muscles and reported higher psychological distress i.e., anxiety trait and depression symptoms (p<0.05), compared to non-responders. A regression analysis revealed that lower PPT or high levels of anxiety trait increased the probability to become a responder (p = 0.001). CONCLUSIONS: Susceptibility to MEP following DOMS is determined by muscle pain hypersensitivity and high levels of anxiety trait. MEP at the early stage of DOMS is linked with an increase in systemic muscle pain sensitivity suggestive of central mechanisms. This knowledge is valuable in translating science into clinical musculoskeletal pain management.
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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 | 0.002 |
| 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) | 0.002 | 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".