Importance of Contextual Factors When Measuring Work Outcome in Ankylosing Spondylitis: A Systematic Review by the OMERACT Worker Productivity Group
Bibliographic record
Abstract
OBJECTIVE: To review the literature on contextual factors (CoFas) and their relationship to work outcomes in individuals with ankylosing spondylitis (AS). METHODS: Articles that quantified the relationship between CoFas and employment status, sick leave, or presenteeism in individuals with AS were systematically identified. CoFas were classified into 5 domains for personal factors and 8 domains for environmental factors. We defined criteria for best-evidence synthesis for each CoFa domain based on the number of studies exploring that domain, and the quality of evidence of individual studies based on the risk of bias, adjustment of multivariable analyses for disease activity and physical function, and sample size. RESULTS: Twenty-five studies met our inclusion criteria: 20 addressed employment status, 6 examined sick leave, and 3 presenteeism. For employment, there was strong evidence for the role of age, moderate evidence for related skills/abilities, the absence of work accommodations, the nature of work and absence of workplace support, and poor evidence for the role of marital status. Evidence was insufficient for sex, education, and physical environment. For sick leave and presenteeism there were too few studies to perform a best-evidence synthesis for the role of CoFas. CONCLUSION: Using a newly proposed set of criteria for determining the best-evidence of the association between CoFa domains and work outcome, the following factors emerged: age, related skills/abilities, work accommodations, nature of work, and workplace support. In addition to disease-related variables, these CoFa domains seem important to include when designing and interpreting studies on work 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 | 0.025 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".