Predictors of Disability and Pain Six Months After the End of Treatment for Fibromyalgia
Bibliographic record
Abstract
OBJECTIVES: The goal of this study was to identify factors associated with decreased disability and lower pain scores 6 months after a multimodal treatment program for fibromyalgia (FM). METHODS: Forty-six patients with FM were assessed after having participated in a 3-month outpatient program integrating physiotherapy, occupational therapy, nursing, and cognitive-behavior therapy. A physician examined the patients before treatment and patients who completed a battery of psychosocial questionnaires at baseline, during treatment, at the end of treatment, and 3 and 6 months after the end of treatment. Two separate multivariable linear regression models were built to identify predictors of improvements in disability and pain. RESULTS: Two predictors for improvement in disability were found: an increase in self-efficacy for pain during treatment and better general adherence during treatment. Similarly, one predictor for improvement in pain intensity was found: an increase in self-efficacy for pain during treatment. DISCUSSION: Self-efficacy and adherence are 2 modifiable factors that influence disability and pain intensity in FM. These psychosocial factors need to be addressed in FM treatment programs to assist patients in maintaining posttreatment improvements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".