Occupation-based Interventions in Patients With Severe Mental Disorders: A Review Study
Bibliographic record
Abstract
Background and Aims The importance of participatory health governance has been acknowledged by the World Health Organization. Studies have shown the positive effects of participation in occupation-based intervention in patients with severe mental disorders, including schizophrenia, in outpatient and inpatient wards. The purpose of this article is to review the studies on occupation-based interventions in patients with severe mental disorders. Methods This is a narrative review study. A search for related articles was conducted in PubMed, Google Scholar, Cochrane, ScienceDirect, Scopus, OTseeker, PsycInfo databases using the keywords “severe mental disorder”, “serious mental illness”, “schizophrenia”, “Major depression disorder”, “Bipolar disorder”, “Occupational therapy”, Occupation”, and “Occupation-based intervention” without the time limitation. Titles and abstracts of 480 yielded articles were examined. Results Twelve articles were reviewed; Two were related to occupation-based interventions in psychiatric inpatients, five were related to occupation-based interventions in outpatients, and five were related to occupation-based interventions in both inpatients and outpatients. Among these articles, one studied the challenges of using occupation-based interventions. Conclusion It seems that occupation-based interventions in inpatients and outpatients with mental illness have been used more to reduce symptoms, and less attention has been paid to the effectiveness of these interventions in maintaining and or improving occupational performance in these patients. The Canadian model of occupational performance and the recovery framework have been used in the design of these interventions. To achieve better results in psychosocial rehabilitation where occupation-based interventions lead to an increase in quality of life, the challenges in this area should be solved.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".