Pain exacerbation as a major source of lost productive time in US workers with arthritis
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of arthritis and arthritis pain exacerbations in US workers including impact on functioning and lost productive work time (LPT). METHODS: The research was conducted as a nested case-control study of participants in the Caremark American Productivity Audit, a US national random-digit-dial survey of US workers. The sample included 329 workers ages 40-65 years meeting the First National Health and Nutrition Examination Survey criteria for arthritis, and 91 workers not meeting arthritis inclusion criteria. Participants completed a telephone interview to measure the prevalence of arthritis and pain exacerbations, LPT (in hours and dollars), functional disability using the Western Ontario and McMaster Universities Knee and Hip Osteoarthritis Index (WOMAC) and the Australian/Canadian Osteoarthritis Hand Index, and demographics. RESULTS: The prevalence of arthritis in US workers ages 40-65 years was 14.7% during the 2-week period. Pain exacerbation occurred among 38% of participants with arthritis. Workers with pain exacerbations were significantly more likely to have higher WOMAC scores (38.6 versus 29.6; P = 0.0041) and report arthritis-related LPT (24.4% versus 13.3%; P = 0.0118) than workers without exacerbations. Among those with LPT, average LPT did not differ (4.1 hours per week) between persons with and without exacerbations. The estimated annual LPT cost from arthritis in the US workforce was $7.11 billion, with 65.7% of this cost attributed to the 38% of workers with pain exacerbations. CONCLUSION: Workers with arthritis pain exacerbation account for a disproportionate share of the arthritis-related LPT cost. Stratifying workers for appropriate treatment management based on pain exacerbation status could significantly decrease arthritis-related LPT and offer employees and employers an effective return on health care use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".