Dual diagnosis of mental illness and substance use disorder and injury in adults recently released from prison: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: People with mental illness and substance use disorder are over-represented in prisons. Injury-related mortality is elevated in people released from prison, and both mental illness and substance use disorder are risk factors for injury. Effective care coordination during the transition between criminal justice and community service providers improves health outcomes for people released from prison. However, the health outcomes and support needs of people with dual diagnosis (co-occurring mental illness and substance use disorder) released from prison are poorly understood. Here we aim to examine the association between dual diagnosis and non-fatal injury in adults released from prison. METHODS: Pre-release interview data collected between Aug 1, 2008, and July 31, 2010, from a representative sample of sentenced adults (≥18 years) in Queensland, Australia, were linked, retrospectively and prospectively, to person-level, state-wide emergency department and hospital records. We identified dual diagnoses from inpatient, emergency department, and prison medical records. We modelled the association between mental health status and all injury resulting in hospital contact by fitting a multivariate Cox regression, adjusting for sociodemographic, health, and criminogenic covariates, and replacing missing covariate data by multiple imputation. FINDINGS: In 1307 adults released from prison, there were 2056 person-years of follow-up (median 495 days, IQR 163-958). The crude injury rates were 996 (95% CI 893-1112) per 1000 person-years for the dual diagnosis group, 538 (441-657) per 1000 person-years for the mental illness only group, 413 (354-482) per 1000 person-years for the substance use disorder only group, and 275 (247-307) per 1000 person-years for the no mental disorder group. After adjusting for model covariates, the dual diagnosis (adjusted hazard rate ratio 3·27, 95% CI 2·30-4·64; p<0·0001) and mental illness only (1·87, 1·19-2·95; p=0·0071) groups were at increased risk of injury after release from prison compared with the group with no mental health disorders. INTERPRETATION: People released from prison experience high rates of injury compared with the general population. Among people released from prison, dual diagnosis is associated with an increased risk of injury. Contact with the criminal justice system is a key opportunity to prevent subsequent injury morbidity in people with co-occurring mental health disorders. Engagement with integrated psychiatric and addiction treatment delivered without interruption during the transition from prison into the community might prevent the injury-related disparities experienced by this vulnerable group. The development of targeted injury prevention strategies for people with dual diagnosis released from prison is warranted. FUNDING: National Health and Medical Research Council.
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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 | 0.001 | 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 | 0.001 | 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".