Emotional, physical, and sexual abuse in fibromyalgia syndrome: A systematic review with meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To systematically assess the potential association of fibromyalgia syndrome (FMS) with emotional, physical, and sexual abuse. METHODS: The databases EMBase, Google Scholar, Medline, and PsycINFO (through April 2010) and the reference sections of original studies were searched for eligible studies. Eligible studies were cohort or case--control studies that assessed at least one type of emotional, physical, or sexual abuse in childhood or adulthood in patients with FMS and in controls. Two authors independently extracted descriptive, quality, and outcome data from included studies. Methodologic quality was assessed by the Newcastle-Ottawa Quality Assessment Scale. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were pooled across studies by using the random-effects model. Heterogeneity was assessed by I(2) statistics. RESULTS: The search identified 18 eligible case-control studies with 13,095 subjects. There were significant associations between FMS and self-reported physical abuse in childhood (OR 2.49 [95% CI 1.81-3.42], I(2) = 0%; 9 studies) and adulthood (OR 3.07 [95% CI 1.01-9.39], I(2) = 79%; 3 studies), and sexual abuse in childhood (OR 1.94 [95% CI 1.36-2.75], I(2) = 20%; 10 studies) and adulthood (OR 2.24 [95% CI 1.07-4.70], I(2) = 64%; 4 studies). Study quality was mostly poor. Low study quality was associated with higher effect sizes for sexual abuse in childhood, but not with other effect sizes. CONCLUSION: The association of FMS with physical and sexual abuse could be confirmed, but is confounded by study quality.
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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 | 0.020 | 0.055 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.039 |
| Bibliometrics | 0.009 | 0.010 |
| 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) | 0.004 | 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".