Physicians’ knowledge, attitudes, and practices regarding fibromyalgia: A systematic review and meta-analysis of cross-sectional studies
Bibliographic record
Abstract
BACKGROUND: The diagnosis, etiology, and optimal management of fibromyalgia remains contentious. This uncertainty may result in variability in clinical management. We conducted a systematic review and meta-analysis of cross-sectional studies examining physicians' knowledge, attitudes, and practices regarding fibromyalgia. METHODS: We searched MEDLINE, Embase, and PubMed from inception to February 2023 for cross-sectional surveys evaluating physicians' attitudes toward, and management of, fibromyalgia. Pairs of independent reviewers conducted article screening, data extraction, and risk of bias assessment in duplicate. We used random-effects meta-analysis to pool proportions for items reported by more than one study and the Grading of Recommendations Assessment, Development, and Evaluation approach to summarize the certainty of evidence. RESULTS: Of 864 citations, 21 studies (8904 participants) were eligible for review. Most physicians endorsed fibromyalgia as a distinct clinical entity (84%; 95% confidence interval [CI], 74-92), and half (51%; 95% CI, 40-62) considered fibromyalgia a psychosocial condition. Knowledge of formal diagnostic criteria for fibromyalgia was more likely among rheumatologists (69%, 95% CI, 45-89) versus general practitioners (38%, 95% CI, 24-54) (P = .04). Symptom relief was endorsed as the primary management goal by most physicians (73%, 95% CI, 52-90). Exercise, physiotherapy, antidepressants, nonsteroidal anti-inflammatory drugs, and non-opioid analgesics were most endorsed for management of fibromyalgia, but with wide variability between surveys. Opioids and most complementary and alternative interventions (e.g., homeopathy, chiropractic, and massage) received limited endorsement. CONCLUSION: There is moderate certainty evidence to suggest that physicians are divided regarding whether fibromyalgia is a biomedical or psychosocial disorder. Physicians typically prioritize symptom relief as the primary goal of management, and often endorse management with exercise, non-opioid analgesics, nonsteroidal anti-inflammatory drugs, antidepressants, and physiotherapy (moderate to high certainty evidence); however, important practice variation exists.
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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 | 0.033 | 0.085 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".