The Role of Sex, Gender, Health Factors, and Job Context in Workplace Accommodation Use Among Men and Women with Arthritis
Bibliographic record
Abstract
Background: With the aging of populations in many countries, workers are expected to remain employed longer but may struggle with the onset of common, chronic conditions like arthritis. To date, few studies have examined workplace policies and practices that could help accommodate individuals with arthritis, and fewer still have used a sex and gender-based approach to explore similarities and differences between women and men. Objectives: This study compared the health and work contexts of workers aged ≥50 years to better understand similarities and differences between women and men in accommodation availability, need, use, and unmet needs. Methods: A cross-sectional survey of men and women with osteoarthritis (OA), inflammatory arthritis (IA), or both OA and IA was administered online or by telephone and assessed demographics (e.g. age, education), health (e.g. pain, fatigue, workplace activity limitations), work context factors (e.g. job sector, full/part-time work, job control), and workplace accommodations (e.g. health benefits, flexible hours, special equipment/adaptations, modified duties). Sex and gender-based analyses examined similarities and differences between men and women and included descriptive statistics, multivariable multinomial analyses, and nested regression analyses. Results: There was a 58.9% response rate and final sample of 463 participants (women, n = 266; men, n = 197; OA = 59.0%; IA/both IA and OA = 23.7%; unsure = 17.3%). Women and men were significantly different in a number of health (e.g. fatigue, health variability, workplace activity limitations) and work context factors (e.g. job sector, part-time work, job stress). However, in other respects, they were similar (e.g. pain, job involving physical demands, size of organization, shift work, union membership, job control). There were no differences between men and women in the availability or use of workplace accommodations. However, women reported significantly more accommodation needs and had greater unmet needs. Multivariable multinomial analyses found male/female as a binary variable did not explain differences in accommodation need, use, and unmet need. Nested analyses highlighted that differences in health variables explained male/female differences in accommodation need, while work context differences explained male/female differences in whether needs were met. Conclusions: The findings highlight that women and men draw on a range of existing accommodation policies and practices to help manage their arthritis and that most have their accommodation needs met. Decomposing the context within which men and women with arthritis work suggests that women may face health and work context challenges that differ from men and that are related to greater accommodation needs and unmet need. This highlights potential vulnerabilities in the work of women that need to be addressed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".