Factors associated with absenteeism, presenteeism and activity impairment in patients in the first years of RA
Bibliographic record
Abstract
OBJECTIVES: To understand the impact of the early years of RA on all aspects of work productivity, and determine how this is related to clinical markers. Previous research on work productivity has examined predominantly early retirement and absenteeism. The impact of reduced work performance (presenteeism) and activity impairment is less well understood in early RA populations. METHODS: Working patients enrolled in an RA inception cohort were recruited into a nested study. A questionnaire incorporating the Work Productivity and Activity Impairment (WPAI) instrument was administered with a number of clinical outcomes, including the Multidimensional Health Assessment Questionnaire (MD-HAQ) and scales for pain, fatigue and patient assessment of disease patient global assessment (PtGA). RESULTS: Analysis included 150 RA patients, with the mean age at onset being 48 years (s.d. 10 years) and disease duration from symptom onset being 49 months. Patients had relatively mild disease: MD-HAQ (0.6), pain (3.6), PtGA (3.6) and fatigue (4.6). Of the 92% patients working for pay, 19% reported missing work (absenteeism) in the past week due to their health, accounting for 46% of their working time. Even while at work, ∼25% of actual hours was lost due to poor health, while outside work 33% of patients' regular daily activities were prevented. In multivariate analyses, disease severity was associated with the presence of absenteeism, presenteeism and activity impairment. Patients able to self-schedule their work had lower presenteeism and activity impairment. CONCLUSIONS: Productivity loss is common in patients in the first years of RA who are in paid work and was associated with work characteristics and adverse clinical outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".