Work factors are associated with workplace activity limitations in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to examine the extent of workplace activity limitations among persons with lupus and to identify factors associated with activity limitations among those employed. METHODS: We conducted a cross-sectional study using a mailed survey and clinical data of persons with lupus who attended a large lupus outpatient clinic. Data were collected on demographics, health, work factors and psychosocial measures. The workplace activity limitations scale (WALS) was used to measure difficulty related to different activities at work. Multivariable analysis examined the association of health, work context, psychosocial and demographic variables with workplace activity limitations. RESULTS: We received 362 responses from 604 (60%) mailed surveys. Among those not employed, 52% reported not working because of lupus. A range of physical and mental tasks were reported as difficult. Each of the physical, cognitive and energy work activities was cited as difficult by more than one-third of participants. Among employed participants, 40% had medium to high WALS difficulty scores. In the multivariable analysis, factors significantly associated with workplace activity limitations were older age, greater disease activity, fatigue, poorer health status measured by the 36-item Short Form Health Survey, lower job control, greater job strain and working more than 40 h/week. CONCLUSION: People with lupus experience limitations and difficulty at work. Determinants of workplace activity limitations are mainly those related to workplace and health factors.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".