Program Evaluation of a Community Organization Offering Supported Employment Services for Adults with Autism
Bibliographic record
Abstract
Background: Individuals with autism spectrum disorder (ASD) have an employment rate well below the general population. One potential solution to address this issue is the implementation of supported employment services. The purpose of our study was to evaluate a Canadian community supported employment program designed for individuals with ASD without an intellectual disability. Method: Thirty-seven individuals with ASD, who were receiving services from a local community agency (Action main-d’oeuvre) providing supported employment services, participated in the study. The research team monitored the characteristics of the participants, the number of hours of services provided, and outcome measures related to employment. We then conducted descriptive analyses, t-tests, and Wilcoxon signed rank tests to compare anxiety about work and self-efficacy before services and after outcomes of the program. Results: Despite high levels of comorbid mental health issues, our results indicated that 62.1% of individuals obtained paid employment within 12 months. Furthermore, participants with post-secondary education found jobs related to their degree or requiring specialized skills. Participants felt less anxious and more self-efficacious towards employment. Maintaining employment was a greater challenge and continuing support may be required. Conclusions: The study suggests that the employment services may have supported the participants in finding a job. However, collaboration is essential to address mental health issues in job seekers with ASD, which appeared to hinder job search and maintenance.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".