A qualitative and observational retrospective analysis of community treatment orders issued in Quebec for the year 2022
Bibliographic record
Abstract
This study provides an observational analysis of community treatment orders (CTOs) in Quebec for 2022, utilizing a qualitative grounded theory approach and descriptive statistics from judgments in the Superior Court of Quebec’s public database, Société québécoise d’information juridique (SOQUIJ), from January to December 2022. Excluding residential placement orders without pharmacological treatment, 209 judgments were analyzed, focusing on sociodemographic traits, court information, clinical data, and treatment details. A significant portion of CTOs proposed by medical teams was granted (202 out of 209, or 97.6%), with 31 receiving partial approval. The study covered 124 male and 85 female patients, aged 19–76 and 14–94, respectively, with average ages of 41 and 53. Roughly a third were diagnosed with psychotic disorders, alongside other conditions like bipolar affective disorders, delusional disorder, neurocognitive disorders, and substance use. The initial CTO duration averaged 2.53 years, with rehospitalization ranging from 7 to 120 days. This analysis highlights Quebec’s use of CTOs, suggesting further research on their efficacy in supporting patient management of illnesses.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 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".