Community Treatment Order Outcomes in Quebec: A Unique Jurisdiction
Bibliographic record
Abstract
OBJECTIVE: We study compulsory community treatment orders (CTOs) for patients with severe and persistent mental illness (SPMI). Focusing on a unique jurisdiction in Canada that allows for long duration CTOs with strict enforcement procedures, our objectives are to determine whether extended duration CTOs are effective and to determine whether associated hospitalization costs are reduced. METHOD: A mirror image, naturalistic design was employed using patients as their own controls to enhance external validity. No inclusive or exclusive criteria were employed for the 367 SPMI clinic patients who were studied over a 5-year period. Detailed documentation of the dates of all CTOs, long-acting antipsychotic injections (LAIs), emergency visits, hospitalizations, duration of hospitalizations, crimes and/or police involvement were collected. To study the relation between CTO and injection adherence, we use a mixed-effect linear regression model. To study the effect of injection adherence and hospitalization, we use survival analysis via Kaplan-Meier and Cox survival models. RESULTS: < 0.001). The average time the patients spent in the community, that is, outside the hospital, was significantly longer under a CTO, and the duration of hospitalizations was decreased. CONCLUSIONS: LAI adherence and outpatient office visits were enhanced by extended duration CTOs, as was time out of the hospital. The shorter duration of hospital stays implies cost savings. These must be weighed against their undesirable coercive nature.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".