Best Practice in Occupational Therapy: Program Characteristics that Influence Vocational Outcomes for People with Serious Mental Illnesses
Bibliographic record
Abstract
BACKGROUND: Despite the known benefits of work for people with mental illnesses, vocational outcomes of this group remain poor. Attempts at comparing the efficacy of various models of service delivery have met with limited success due to variations across studies. PURPOSE: The purpose of this paper is to provide information about key characteristics related to outcomes in the field of vocational rehabilitation for people with serious mental illnesses. METHOD: A comprehensive review of literature published between 1990 and 2003 was conducted, resulting in 39 articles for analysis. RESULTS: A set of twelve characteristics was identified that appear to influence vocational outcomes across models. These characteristics relate to the types of services offered, the manner in which services are delivered, and the work environment. PRACTICE IMPLICATIONS: The authors suggest these characteristics can be incorporated across models and practice settings. The findings are discussed in terms of implications for best practice in occupational therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".