Measuring the Impact of Arthritis on Worker Productivity: Perspectives, Methodologic Issues, and Contextual Factors
Bibliographic record
Abstract
Leading up to the Outcome Measures in Rheumatology (OMERACT) 10 meeting, the goal of the Worker Productivity Special Interest Group (WP-SIG) was to make progress on 3 key issues that relate to the application and interpretation of worker productivity outcomes in arthritis: (1) to review existing conceptual frameworks to help consolidate our intended target and scope of measurement; (2) to examine the methodologic issues associated with our goal of combining multiple indicators of worker productivity loss (e.g., absenteeism <-> presenteeism) into a single comprehensive outcome; and (3) to examine the relevant contextual factors of work and potential implications for the interpretation of scores derived from existing outcome measures. Progress was made on all 3 issues at OMERACT 10. We identified 3 theoretical frameworks that offered unique but converging perspectives on worker productivity loss and/or work disability to provide guidance with classification, selection, and future recommendation of outcomes. Several measurement and analytic approaches to combine absenteeism and presenteeism outcomes were proposed, and the need for further validation of such approaches was also recognized. Finally, participants at the WP-SIG were engaged to brainstorm and provide preliminary endorsements to support key contextual factors of worker productivity through an anonymous "dot voting" exercise. A total of 24 specific factors were identified, with 16 receiving ≥ 1 vote among members, reflecting highly diverse views on specific factors that were considered most important. Moving forward, further progress on these issues remains a priority to help inform the best application of worker productivity outcomes in arthritis research.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".