Forensic and Nonforensic Clients in Assertive Community Treatment: A Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE This study compared rates of arrest and incarceration, psychiatric hospitalization, homelessness, and discharge from assertive community treatment (ACT) programs for forensic and nonforensic clients in New York State and explored associated risk factors. METHODS Data were extracted from the New York State Office of Mental Health's Web-based outcome reporting system. ACT clients admitted between July 1, 2003, and June 30, 2007 (N=4,756), were divided into three groups by their forensic status at enrollment: recent (involvement in the past six months), remote (forensic involvement was more than six months prior), and no history. Client characteristics as of ACT enrollment and outcomes at one, two, and three years were compared over time. RESULTS Clients with forensic histories had a significantly higher ongoing risk of arrest or incarceration, and those with recent criminal justice involvement had a higher risk of homelessness and early discharge from ACT. Psychiatric hospitalization rates did not differ significantly across groups. Rates of all adverse outcomes were highest in the first year for all ACT clients, especially for those with a recent forensic history, and rates of psychiatric hospitalization, homelessness, and discharge declined over time for all clients. For all ACT clients, homelessness and problematic substance abuse at enrollment were significant risk factors for arrest or incarceration and for homelessness on three-year follow-up. CONCLUSIONS Clients with recent forensic histories were vulnerable to an array of adverse outcomes, particularly during their first year of ACT. This finding highlights the need for additional strategies to improve forensic and other outcomes for this high-risk population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".