Fibromyalgia-related costs and loss of productivity: a substantial societal burden
Bibliographic record
Abstract
BACKGROUND: This study aimed at describing pain-related health care resource use, direct costs, and productivity loss among patients suffering from fibromyalgia syndrome (FMS). METHODS: A cost-of-illness study with a sample of 57 adults having a diagnosis of FMS was conducted in the province of Quebec (Canada). Data regarding FMS-related direct costs and productivity loss from paid and unpaid work over a three-month period were collected using a standardized structured telephone interview protocol. Direct costs were valued in 2009 Canadian dollars using a societal perspective. RESULTS: Results showed that average direct costs over a three-month period added up to $951 per patient (SD: $710), which could be translated in a mean annual cost of $3804. The purchase of prescribed medications led to the highest costs (mean: $329, SD: $321), followed by consultations to health care professionals other than physicians (mean: $129, SD: $222) and physicians consultations (mean: $98, SD: $116). Results further showed a high economic burden for patients themselves, aside from costs covered by public or private insurers. Among the subsample of participants who had a paid job (45.6%), an average of 5.6 days (SD: 13.2) were lost due to pain during the past three months. Among those who were not employed (54.4%), an average of 25.1 days in household productivity (SD: 24.8) were lost. CONCLUSIONS: FMS is associated with a substantial socioeconomic burden. Further research is clearly needed to improve the management of this type of disorder and make better decisions regarding resource allocation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".