Patients With Fibromyalgia Reporting Severe Pain but Low Impact of the Syndrome: Clinical and Pain‐Related Cognitive Features
Bibliographic record
Abstract
BACKGROUND: Fibromyalgia (FM) is a prevalent and highly disabling chronic pain syndrome. However, differences among patients regarding how pain impacts on daily life are remarkable. The main aim of this study was to identify clinical and pain-related cognitive variables characterizing patients reporting high adaptability despite experiencing severe chronic pain. METHODS: Two hundred and eighty-three Spanish patients with FM with high levels of pain were classified into 2 groups: (1) those reporting low impact of the syndrome, and (2) those with moderate-to-high impact. Perceived stress, anxiety, and depressive symptoms along with pain catastrophizing, psychological inflexibility, and perceived control over pain were evaluated. Differences in sociodemographics, years with FM, past/current major depressive disorder comorbidity, and health-related economic costs (ie, medications, use of medical services, lost productivity due to sick leave) were also assessed. Stepwise logistic regression analyses predicting group membership from clinical variables and pain-related cognitive processes as predictors were performed. RESULTS: Lower stress, anxiety, and depressive symptoms, along with reduced pain catastrophism, psychological inflexibility, and perceived control over pain, were found in the low-impact group. Significant predictors of group membership (low-impact vs. moderate-to-high impact) in regression analyses were "cognitive fusion" (psychological inflexibility), "helplessness" (pain catastrophizing), and depressive symptomatology, together with pain intensity and other FM symptoms. CONCLUSIONS: The present study provides further evidence on resilience resources in chronic pain by identifying some variables (ie, reduced depressive symptomatology, pain catastrophizing, and psychological inflexibility) differentially characterizing a profile of patients with FM who are especially able to adapt to high levels of pain.
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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 | 0.002 |
| 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".