Reliability, validity, and responsiveness of five at‐work productivity measures in patients with rheumatoid arthritis or osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Arthritis often impacts a worker's ability to be productive while at work. However, the ideal approach to measuring arthritis-attributable at-work productivity loss remains unclear. Our objective was to evaluate the relative strengths and weaknesses of 5 measures aimed at quantifying health-related at-work productivity loss and to determine the best available instrument for this population. METHODS: In a 12-month longitudinal design, the psychometric properties (reliability, validity, and responsiveness) of 5 self-reported measures of at-work productivity were compared in workers with either rheumatoid arthritis (RA) or osteoarthritis (OA). We tested the Workplace Activity Limitations Scale (WALS), 6-item Stanford Presenteeism Scale (SPS-6), Endicott Work Productivity Scale (EWPS), RA Work Instability Scale (WIS), and Work Limitations Questionnaire (WLQ). RESULTS: Across all measures, participants (n = 250, 120 with RA and 130 with OA) consistently reported mild losses of at-work productivity. The Cronbach's alpha of the scales ranged from 0.71 (for SPS-6) to 0.94 (for EWPS), indicating some concerns over the internal consistency of the SPS-6. The RA WIS demonstrated the strongest construct validity (|r| = 0.54-0.74), whereas the WALS was most responsive to perceived changes in work ability. Despite its increasing popularity and potential application for costing analysis, the WLQ did not compare favorably with the other scales, possibly due to psychometric concerns with its physical demands subscale. CONCLUSION: Measures revealed unique conceptualization of at-work disability, but no single scale emerged as clearly superior. However, current results slightly favor the WALS and RA WIS as superior instruments for measuring at-work productivity loss in workers with arthritis.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".