Community treatment orders and the experiences of ethnic minority individuals diagnosed with serious mental illness in the Canadian mental health system
Bibliographic record
Abstract
INTRODUCTION: The prevalence of Community Treatment Orders (CTOs) in the Western world has generated considerable discussion regarding best practices in the outpatient treatment of the seriously mentally ill. Although problems encountered by ethnic minority communities in the various health care systems have been studied to some degree, there is an acute dearth of information on the effects of CTOs on minority individuals. This paper presents findings from research on the lived experiences of individuals from ethnic minority backgrounds who have been the subjects of CTOs in Toronto, Canada, and their perceptions of its impact on their lives. METHODS: Using a qualitative phenomenological approach, in-depth semi-structured interviews were conducted with individuals who have experienced CTOs. Purposive sampling was used to recruit participants (n = 24) from ethnic minority background in Toronto, Canada. RESULTS: Participants perceived both positive and negative impacts of CTOs. The positives included affirmation of experiences with the mental health system; improved rapport with the case management and clinical team, increased medication compliance and feelings of empowerment. The negative feedback included feelings of being coerced and the stigma associated with it. CONCLUSIONS: The findings of this study suggest that although CTOs are not a panacea for every mental health problem, they can be effective with a specific group who choose to follow through with the expectations of the treatment. The author, however argues that for these individuals to be on a CTO before getting better treatment, brings to the fore a number of issues with the mental health system. This is particularly concerning as it pertains to individuals of ethnic minority background.
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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 | 0.008 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".