694 Efficiency of vocational rehabilitation programs for workers with schizophrenia: a systematic literature review according to the prisma guidelines
Bibliographic record
Abstract
Introduction Unemployment is common among people with schizophrenia and contributes most to the economic cost of the condition. This study was aimed at (1) reviewing the available tools to facilitate the vocational rehabilitation of workers with schizophrenia and (2) describing their specific opportunities. Methods A search of PubMed for original, peer-reviewed articles published from 2006 until January 31, 2016, yielded 643 citations. Exclusion criteria were patients less than 18 years or older than 65 years of age, patients with additional diagnoses, studies conducted in developing countries, lack of an adequate study design, systematic reviews or case studies, no work related studies, and other major analytic inadequacies. The remaining 24 articles were assessed in qualitative synthesis using the Scottish Intercollegiate Guidelines Network (score ≥2+), Critical Appraisal Skills Program or Prediction Model Risk of Bias Assessment Tool checklists. Results Only seven quantitative and one qualitative study could be included. The number of study participants with schizophrenia varied substantially (n=7 in the qualitative study, n=100 in the largest quantitative study). Most studies were conducted in the United States (n=5), as well as two in Canada and one in Japan. Cognitive remediation programs (Neurocognitive Enhancement Therapy) combined with supported employment were significantly more effective (p<0.005) than supported employment by itself. Next, Individual Placement and Support (the manual version of supported employment) and cognitive behavioural therapy (Indianapolis Vocational Intervention Program) were, by themselves, more effective than conventional vocational rehabilitation, regardless of whether it was for competitive employment. Discussion Combining cognitive remediation programs with supported employment programs significantly improved the vocational outcomes of workers with schizophrenia, especially for those with lower community functioning. Participation in competitive employment was also promoted by shorter initial working hours, higher education and disclosure of disabilities. Future prospective, longitudinal research with larger samples, in stratified baseline conditions, 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 | 0.104 | 0.165 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.030 | 0.023 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".