An Updated Meta-Analysis of Randomized Controlled Evidence for the Effectiveness of Community Treatment Orders
Bibliographic record
Abstract
OBJECTIVES: It is unclear whether community treatment orders (CTOs) for people with severe mental illnesses can reduce health service use, or improve clinical and social outcomes. Randomized controlled trials of CTOs are rare because of ethical and logistical concerns. This meta-analysis updates available evidence. METHOD: A systematic literature search was performed of the Cochrane Schizophrenia Group Register, Science Citation Index, PubMed, MEDLINE, and Embase to November 2013. Inclusion criteria were studies comparing CTOs with standard care including those where control subjects received voluntary care, for most of the trial. RESULTS: Three studies provided 749 subjects for the meta-analysis. Two compared compulsory treatment with entirely voluntary care, while the third had control subjects receiving voluntary treatment for the bulk of the time. Compared with control subjects, CTOs did not reduce readmissions (risk ratio 0.98, 95% CI 0.82 to 1.16) or bed days (mean difference [MD] -16.36; 95% CI -40.8 to 8.05) in the subsequent 12 months (n = 749). Moreover, there were no significant differences in psychiatric symptoms (standardized MD -0.03; 95% CI -0.25 to 0.19; n = 331) or the Global Assessment of Functioning (MD -1.36; 95% CI -4.07 to 1.35; n = 335). Only including the 2 studies that compared compulsory treatment with entirely voluntary care made no difference to the results. CONCLUSIONS: CTOs may not lead to significant differences in readmission, social functioning, or symptomatology, compared with standard care. Their use should be kept under review.
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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 | 0.037 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".