Faculty Opinions recommendation of Prescribed versus preferred intensity resistance exercise in fibromyalgia pain.
Bibliographic record
Abstract
Exercise is the treatment of choice for fibromyalgia (FM), but little is known about resistance exercise prescription to modulate pain in this condition. This study aimed to compare the effects of different resistance exercise models, comprising self-selected or prescribed intensity, on pain in FM patients. In a cross-over fashion, 32 patients underwent the following sessions: (i) standard prescription (STD; 3 × 10 repetitions at 60% of maximal strength); (ii) self-selected load with fixed number of repetitions (SS); (iii) self-selected load with volume load (i.e., load × sets × repetitions) matched for STD (SS-VM); and (iv) self-selected load with a free number of repetitions until achieving score 7 of rating perceived exertion (SS-RPE). Pain, assessed by Visual Analogic Scale (VAS) and Short-Form McGill Pain Questionnaire (SF-MPQ), was evaluated before and 0, 24, 48, 72, and 96 h after the sessions. Load was significantly lower in SS, SS-VM, SS-RPE than in STD, whereas rating perceived exertion and volume load were comparable between sessions. VAS scores increased immediately after all sessions (p < 0.0001), and reduced after 48, 72, 96 h (p < 0.0001), remaining elevated compared to pre-values. SF-MPQ scores increased immediately after all exercise sessions (p = 0.025), then gradually reduced across time, reaching baseline levels at 24 h. No significant differences between sessions were observed. Both prescribed and preferred intensity resistance exercises failed in reducing pain in FM patients. The recommendation that FM patients should exercise at preferred intensities to avoid exacerbated pain, which appears to be valid for aerobic exercise, does not apply to resistance exercise. PMID: 30158876
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.579 | 0.318 |
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".