Nonvocational outcomes of vocational rehabilitation: Reduction in health services utilization
Bibliographic record
Abstract
BACKGROUND: Numerous studies have demonstrated the beneficial effects of vocational rehabilitation on vocational outcomes in individuals with a mental illness, yet effects on secondary outcomes remain largely unexplored. This study investigates the impact of vocational rehabilitation on the utilization of emergency, ambulatory care and inpatient services in individuals with a mental illness. METHODS: Using a repeated measures study design, the utilization of health services by individuals with a mental illness (n= 37) was compared before and during their engagement in training and employment at a social enterprise - a form of vocational rehabilitation. RESULTS: Individuals with a mental illness had significantly less emergency department visits (p=0.01), ambulatory care visits (p=0.01) and hospital admissions (p=0.05), but no difference in hospital length of stay (p=0.39), during training/employment, compared to pre-training/employment at a social enterprise. CONCLUSION: The reduction in health services utilization found in this study may reflect symptom and overall health improvement, highlighting the importance of vocational rehabilitation programs for individuals with a mental illness. In addition, results from this study can inform stakeholders and policymakers about the impact of vocational rehabilitation on the healthcare system to help guide decisions regarding program implementation or continuation, and funding allocation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".