O-005 HOW CAN WORK ACCOMMODATIONS CONTRIBUTE TO SUSTAINABLE RETURN TO WORK OF OLDER WORKERS AFTER SICK LEAVE?
Bibliographic record
Abstract
Abstract Introduction In Quebec (Canada), older workers aged 45 or over have a longer average absence compared to other types of workers, with higher annual costs per injury. Based on the disability at work paradigm, this study aimed to identify how work accommodations can contribute to sustainable return to work (S-RTW) of older workers having experienced occupational physical or psychological impairments. Methods Following a mixed design study, the ACC45+ questionnaire was developed and validated in Canada to list the work accommodations implemented during the RTW of the target population. Results The tool (37 items under 8 subscales) measures feasible accommodations about the work context and content, and the interpersonal relations at work. The accommodations reported as frequently implemented (≥70%) during the RTW process were: RTW plan and follow-up, and Work schedule and the workplace. T-tests showed that some accommodations (e.g., Co-worker support) are less prevalent among older workers having experienced a psychological impairment. Finally, multivariate analyses showed that two work accommodations (Work schedule and workplace, and Occupational health) were significantly correlated with Fear of relapse and the Ergonomics of the workplace which, in turn, positively influenced S-RTW. Discussion and conclusion Results confirmed that working in an organization that is attentive to occupational and safety issues is effective in promoting older workers’ job maintenance after the RTW. The ACC45+ is the first questionnaire that can be used by stakeholders (e.g., immediate supervisors, union representatives, psychologists, physiotherapists) in interventions for implementing work accommodations in order to prevent older workers’ relapses and to promote their S-RTW.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".