The Association Between Prior Mental Health Service Utilization and Risk of Recidivism among Incarcerated Ontario Residents
Bibliographic record
Abstract
BackgroundThere is mixed evidence on the link between mental health and addiction (MHA) history and recidivism. Few studies have examined post-release MHA care. Our objective was to examine the association between prior (pre-incarceration) MHA service use and post-release recidivism and service use.MethodsWe conducted a population-based cohort study linking individuals held in provincial correctional institutions in 2010 to health administrative databases. Prior MHA service use was assigned hierarchically in order of hospitalization, emergency department visit and outpatient visit. We followed up individuals post-release for up to 5 years for the first occurrence of recidivism and MHA hospitalization, emergency department visit and outpatient visit. We use Cox-proportional hazards models to examine the association between prior MHA service use and each outcome adjusting for prior correctional involvement and demographic characteristics.ResultsAmong a sample consisting of 45,890 individuals, we found that prior MHA service use was moderately associated with recidivism (hazard ratio (HR): 1.20–1.50, all P < 0.001), with secondary analyses finding larger associations for addiction service use (HR range: 1.34–1.54, all P < 0.001) than for mental health service use (HR range: 1.09–1.18, all P < 0.001). We found high levels of post-release MHA hospitalization and low levels of outpatient MHA care relative to need even among individuals with prior MHA hospitalization.DiscussionDespite a high risk of recidivism and acute MHA utilization post-release, we found low access to MHA outpatient care, highlighting the necessity for greater efforts to facilitate access to care and care integration for individuals with mental health needs in correctional facilities.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".