Predictors of the Pain Perception and Self-Efficacy for Pain Control in Patients with Fibromyalgia
Bibliographic record
Abstract
OBJECTIVE: This study analyzes the role of a number of cognitive-affective dimensions in the experience and coping of pain in patients with fibromyalgia (FM). Specifically, it was examined whether anxiety, depression, pain catastrophizing and pain-related anxiety predict the pain perception and the self-efficacy expectations in these patients. METHOD: Seventy-four fibromyalgia patients were asked to complete a questionnaire survey including the Chronic Pain Self-Efficacy Scale, the Hospital Anxiety and Depression Scale, the Pain Anxiety Symptoms Scale-20, the Pain Catastrophizing Scale, and the Short-form McGill Pain Questionnaire. RESULTS: Some relevant correlation and predicting patterns were identified. Physiological anxiety was the best predictor of the sensorial dimension of pain. Pain fear was a significant predictor of the pain intensity. Helplessness was the best predictor of the affective dimension of pain, whereas depression was a significant predicting variable of the self-efficacy expectations. CONCLUSIONS: This study shows the relevance of the pain-related anxiety in the pain perception, and of the depression in the self-efficacy expectations in FM patients. Clinical applications of the findings and further research lines in this area are discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".