Are There Differences in Workplace Accommodation Needs, Use and Unmet Needs Among Older Workers With Arthritis, Diabetes and No Chronic Conditions? Examining the Role of Health and Work Context
Bibliographic record
Abstract
The aging of workforces combined with the prevalence of age-related chronic diseases has generated interest in whether large numbers of older workers will need workplace accommodations. This research applied work functioning theory to examine accommodation availability, need and use in workers with arthritis, diabetes, or no chronic disabling diseases; factors associated with accommodation needs; and the relationship of accommodation needs met, unmet or exceeded to job outcomes. Participants were aged 50–67 years, employed, and had arthritis (n = 631), diabetes (n = 286), both arthritis/diabetes (n = 111) or no chronic disabling conditions (healthy controls n = 538). They were recruited from a national panel of 80,000 individuals and a cross-sectional survey was administered online or by telephone. Questionnaires assessed demographics, health, work context, workplace accommodations, and job outcomes. Chi-square analyses, analyses of variance, and regression analyses compared groups. Respondents were similar in many demographic and work context factors. As expected, workers with arthritis and/or diabetes often reported poorer health and employment outcomes. Yet, there were few differences across health conditions in need for or use of accommodations with most participants reporting accommodations needs met. In keeping with work functioning theory, unmet accommodation needs were largely related to work context, not health. Workers whose accommodation needs were exceeded reported better job outcomes than those with accommodation needs met. Findings highlight both work context and health in understanding workplace accommodations and suggest that many older workers can meet accommodation needs with existing workplace practices. However, additional research aimed at workplace support and the timing of accommodation use is needed.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".