910 A supervisor training program for work disability prevention: preliminary results from a cluster randomised controlled trial
Bibliographic record
Abstract
Introduction Providing supervisors with tools to improve their response to workplace injuries or illnesses may improve disability outcomes. The objective of this study was to examine the effectiveness of the Supervisor/Manager Accommodation Recognition and Training (SMART) Program on reducing the total duration of workers’ lost-time claims. Here, we provide preliminary results from two Canadian (located in Ontario and British Columbia) and one American employer. Methods Within each organisation, work units were randomly selected to have their supervisors receive the training program. Work units not assigned to the program served as the control group for the study. Work disability outcome data were one-year prior to and one-year post training for comparison purposes. Web based surveys were used to collect information on supervisors’ knowledge and responses to workplace injuries at baseline, 3- and 6 months post training. Results For the Ontario-based employer, the SMART program did not impact the total duration of workers’ lost-time claims when compared to the controls. For the British Columbia-based employer, trained work sites had a reduction in both the number of days off per injury incident (−6.2) and the number of short-term disability claims per 100 workers (−10.5). Across the American-based employer, the work sites that received the SMART training had a significant reduction in the number of days off per workers’ compensation claim (−4.9), a small decrease in the average number of days per short-term disability claim (−2.7) and the number of Workers’ Compensation claims were reduced to half the rate post-training (8.3 claims per 100 employees per year down to 4.4). Survey results will also be discussed. Conclusion The mixed results of the preliminary data highlight the importance of context when studying complex organisations. Employee culture, policies and practices of management, type of industry, and other organisational factors have a strong influence on work disability 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".