Worker Productivity Outcome Measures: OMERACT Filter Evidence and Agenda for Future Research
Bibliographic record
Abstract
The objective of the Outcome Measures in Rheumatology (OMERACT) Worker Productivity working group is to identify worker productivity outcome measures that meet the requirements of the OMERACT filter. At the OMERACT 11 Workshop, we focused on the at-work limitations/productivity component of worker productivity (i.e., presenteeism) - an area with diverse conceptualization and instrumentation approaches. Various approaches to quantify at-work limitations/productivity (e.g., single-item global and multi-item measures) were examined, and available evidence pertaining to OMERACT truth, discrimination, and feasibility were presented to conference participants. Four candidate global measures of presenteeism were put forth for a plenary vote to determine whether current evidence meets the OMERACT filter requirements. Presenteeism globals from the Work Productivity and Activity Impairment Questionnaire (72% support) and Rheumatoid Arthritis-specific Work Productivity Survey (71% support) were endorsed by conference participants; however, neither the presenteeism global item from the Health and Work Performance Questionnaire nor the Quantity and Quality method achieved the level of support required for endorsement at the present time. The plenary was also asked whether the central item from the Work Ability Index should also be considered as a candidate measure for potential endorsement in the future. Of participants at the plenary, 70% supported this presenteeism global measure. Progress was also made in other areas through discussions at individual breakout sessions. Topics examined include the merits of various multi-item measures of at-work limitations/productivity, methodological issues related to interpretability of outcome scores, and approaches to appraise and classify contextual factors of worker productivity. Feedback gathered from conference participants will inform the future research agenda of the working group.
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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 | 0.307 | 0.394 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.025 | 0.014 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".