The contribution of IPS to recovery from serious mental illness: A case study
Bibliographic record
Abstract
BACKGROUND: Individual Placement and Support (IPS) is an effective, evidence-based intervention to support transition to paid work for individuals who have a serious mental illness. Currently, there is a lack of qualitative reporting from the people receiving IPS and their support networks. APPROACH: A case study of a 42-year-old-man who has schizophrenia and who attends a community mental health team in a Canadian urban centre is presented. His experience and that of his mother, employer, and clinical supports are shared through semi-structured interviews. The authors of this paper include a peer researcher who has been a participant in an IPS program. FINDINGS: The enduring and individual support of IPS is credited with being central to the study subject's successful acquisition and maintenance of paid employment. His involvement in paid work is also associated with improved health outcomes, including a significant reduction in the frequency of medical appointments to monitor his mental health. Improved social skills and self-efficacy are also reported. CONCLUSION: Provision of IPS services within a multidisciplinary mental health team can promote the acquisition of durable employment for individuals in recovery from serious mental illness. Clinicians are reminded to check their assumptions regarding which individuals could benefit from IPS, and are encouraged to take their lead from clients in determining whether to commence or continue employment services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".