Availability, Need for, and Use of Work Accommodations and Benefits: Are They Related to Employment Outcomes in People With Arthritis?
Bibliographic record
Abstract
OBJECTIVE: To examine the availability, need, and use of workplace policies for workers with osteoarthritis (OA) and inflammatory arthritis (IA) and their association with employment outcomes. METHODS: Participants (n = 219) were employed, ages ≥25 years, and diagnosed with OA or IA. They were recruited through community advertising and rheumatology clinics in 2 Canadian provinces. Respondents completed a 35-45-minute telephone interview assessing demographics (age, sex), health (diagnosis, pain, activity limitations), work context (job control), employment outcomes (workplace activity limitations, absenteeism, productivity losses, reduced hours), benefits (extended health, short-term leaves), and accommodations (flexible hours, modified schedules, special equipment/adaptations, work-at-home arrangements). Regression analyses examined differences in benefit/accommodation need and use. RESULTS: Many participants reported that arthritis impacted their work. But with the exception of extended health benefits, ∼50-65% of participants reported not needing each individual benefit/accommodation, although only 7.3% of respondents reported needing no benefits or accommodations at all. Greater job control and education were associated with greater perceived need and use of benefits/accommodations. Need was also associated with greater activity limitations, and disclosure of arthritis was related to use of benefits/accommodations. Participants needing but not using workplace policies often had significantly poorer employment outcomes compared to those using benefits/accommodations. CONCLUSION: Findings are relevant to workers with arthritis and to employers. Results suggest that individuals with arthritis are unlikely to be a drain on workplace resources. Many individuals do not use benefits/accommodations until needed, and among those using them, there were generally positive relationships with diverse employment 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".