Higher Emotion-Related Distress in Patients with Fibromyalgia versus Chronic Neuropathic Pain and Healthy Controls: Is It a Primary Affective Disorder?
Bibliographic record
Abstract
Fibromyalgia is central sensitization pain disorder with various psychological symptoms. Our aim is to compare trait paranoia, self-esteem and impulsivity between fibromyalgia patients (FM), chronic neuropathic pain sufferers (CNP) and healthy control. We administrated the Mini International Neuropsychologic Interview to 30 FM, 27 CNP and 22 HC. All participants completed the Paranoia, Rosenberg Self-Esteem and Short UPPS-P Impulsivity Behavior Scales, Beck Depression and State-Trait Anxiety inventories. Patients provided pain ratings and completed the French version of the McGill Pain Questionnaire and Pain Catastrophizing Scale. An analysis of variance compared the three groups, with adjustment for psychological distress, pain severity and education level. Anxiety-related psychiatric comorbidities were more prevalent in FM. Depression and state anxiety were higher in both CNP and FM, while trait anxiety was higher in FM compared to two other groups. Paranoia scores were significantly higher among FM than among HC, with intermediate scores in CNP. These group differences remained after adjustment for psychological distress, pain severity and education level. Lower self-esteem and higher negative urgency in patients with FM disappeared when results were adjusted for psychological distress. FM described sensory and affective aspects of pain as more severe and displayed higher pain catastrophizing than CNP group. These results suggest that emotion-related distress is higher in FM than in CNP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".