Living with the unexplained: coping, distress, and depression among women with chronic fatigue syndrome and/or fibromyalgia compared to an autoimmune disorder
Bibliographic record
Abstract
Chronic fatigue syndrome (CFS) and fibromyalgia are disabling conditions without objective diagnostic tests, clear-cut treatments, or established etiologies. Those with the disorders are viewed suspiciously, and claims of malingering are common, thus promoting further distress. It was hypothesized in the current study that levels of unsupportive social interactions and the coping styles used among those with CFS/fibromyalgia would be associated with perceived distress and depressive symptoms. Women with CFS/fibromyalgia (n=39), in fact, reported higher depression scores, greater perceived distress and more frequent unsupportive relationships than healthy women (n=55), whereas those with a chronic, but medically accepted illness comprising an autoimmune disorder (lupus erythematosus, multiple sclerosis, rheumatoid arthritis; n=28), displayed intermediate scores. High problem-focused coping was associated with low levels of depression and perceived distress in those with an autoimmune condition. In contrast, although CFS/fibromyalgia was also accompanied by higher depression scores and higher perceived distress, this occurred irrespective of problem-focused coping. It is suggested that because the veracity of ambiguous illnesses is often questioned, this might represent a potent stressor in women with such illnesses, and even coping methods typically thought to be useful in other conditions, are not associated with diminished distress among those with CFS/fibromyalgia.
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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 | 0.000 | 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) | 0.001 | 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".