Canadian Studies on the Effectiveness of Community Treatment Orders: An Updated Systematic Review of Quantitative Data: Études canadiennes sur l’efficacité des ordonnances de traitement en milieu communautaire : mise à jour d’un examen systématique des données quantitatives
Bibliographic record
Abstract
ObjectivesCommunity treatment orders (CTOs) for people with severe mental illnesses are used across most of Canada. Our previous systematic review of 10 years ago found that the evidence-base was limited to small studies, with only one including controls. This review updates the evidence using studies conducted in Canada over the last decade.MethodsA systematic search of PubMed/Medline, Embase, CINAHL, and PsycINFO for any Canadian study of outcomes following CTO placement from March 2015 to January 2025.ResultsWe identified four articles from three studies. Adding these studies to the previous search gave a total of nine articles from seven studies. None could be included in a meta-analysis. There were reductions in readmission rates and bed-days following CTO placement, while psychiatric symptom, outpatient attendance, treatment adherence participation in psychiatric services and housing all improved. In one study, perceived coercion was no greater in the CTO cases than the controls and being on an order preferable to being in hospital. However, many of the studies were small and only two included controls, of which solely one adjusted for potential confounders using either matching or adjusted analyses. The certainty of evidence was therefore rated as very low.ConclusionsThe evidence-base for the use of CTOs in Canada remains limited. This research gap contrasts with other countries that have conducted large studies using randomized or matched controls and adjusted analyses. There is a need for larger studies with more standardized reporting methods to allow for the pooling of results.Protocol Registration NumberProspectively registered with PROSPERO registration number CRD42024615480.
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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 | 0.066 | 0.242 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.020 | 0.029 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".