Efficacy of Cognitive-Behavioral Therapies in Fibromyalgia Syndrome — A Systematic Review and Metaanalysis of Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: We performed the first systematic review with metaanalysis of the efficacy of cognitive-behavioral therapies (CBT) in fibromyalgia syndrome (FM). METHODS: We screened Cochrane Library, Medline, PsychINFO, and Scopus (through June 2009) and the reference sections of original studies and systematic reviews for CBT in FM. Randomized controlled trials (RCT) comparing CBT to controls were analyzed. Primary outcomes were pain, sleep, fatigue, and health-related quality of life (HRQOL). Secondary outcomes were depressed mood, self-efficacy pain, and healthcare-seeking behavior. Effects were summarized using standardized mean differences (SMD). RESULTS: A total of 14 out of 27 RCT with 910 subjects with a median treatment time of 27 hours (range 6-75) over a median of 9 weeks (range 5-15) were included. CBT reduced depressed mood (SMD -0.24, 95% CI -0.40, -0.08; p = 0.004) at posttreatment. Sensitivity analyses showed that the positive effect on depressed mood could not be distinguished from some risks of bias. There was no significant effect on pain, fatigue, sleep, and HRQOL at posttreatment and at followup. There was a significant effect on self-efficacy pain posttreatment (SMD 0.85, 95% CI 0.25, 1.46; p = 0.006) and at followup (SMD 0.90, 95% CI 0.14, 1.66; p = 0.02). Operant behavioral therapy significantly reduced the number of physician visits at followup (SMD -1.57, 95% CI -2.00, -1.14; p < 0.001). CONCLUSION: CBT can be considered to improve coping with pain and to reduce depressed mood and healthcare-seeking behavior in FM.
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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 | 0.041 | 0.085 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.042 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".