Does work have to be so painful? A review of the literature examining the effects of fibromyalgia on the working experience from the patient perspective
Bibliographic record
Abstract
BACKGROUND: Chronic pain conditions, such as fibromyalgia, adversely affect individuals' abilities to work. AIM: The aim of this study was to examine, from the perspective of patients, the effects that fibromyalgia symptoms had on their ability to work, the challenges that they encountered in the workplace that did not foster their continued employment, and the types of modifications to their work or workplace that they thought would facilitate their productivity and ability to work. METHODS: A scoping review method, applying techniques of systematic review, was used to conduct a research synthesis of the literature regarding fibromyalgia and work that looked at this issue from the patient perspective. RESULTS: A variety of themes emerged from the analysis and could be broadly categorized into (1) the work experience was a challenging one with which to cope; (2) relationships were strained at work; (3) clinical symptoms had repercussions on subjects' attitudes toward work and the relation to life outside of work; and (4) a variety of possible solutions were considered to help subjects better cope with fibromyalgia and work. CONCLUSIONS: Strategies that potentially could foster continued employment of patients with fibromyalgia include those at the micro, meso, and macro levels. Health care providers can support patients' employment goals by collaborating with patients and their employers, dispelling stigma regarding the illness, and providing practical and specific advice regarding workplace accommodations.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".