Criminal Behavior and Victimization Among Homeless Individuals With Severe Mental Illness: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The objectives of the systematic review were to estimate the prevalence and correlates of criminal behavior, contacts with the criminal justice system, and victimization among homeless adults with severe mental illness. METHODS: MEDLINE, Embase, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, and Web of Science were searched for published empirical investigations of prevalence and correlates of criminal behavior, contacts with the justice system, and episodes of victimization in the target population. RESULTS: The search yielded 21 studies. Fifteen examined prevalence of contacts with the criminal justice system; lifetime arrest rates ranged between 62.9% and 90.0%, lifetime conviction rates ranged between 28.1% and 80.0%, and lifetime incarceration rates ranged between 48.0% and 67.0%. Four studies examined self-reported criminal behavior, with 12-month rates ranging from 17.0% to 32.0%. Six studies examined the prevalence of victimization, with lifetime rates ranging between 73.7% and 87.0%. Significant correlates of criminal behavior and contacts with the justice system included criminal history, high perceived need for medical services, high intensity of mental health service use, young age, male gender, substance use, protracted homelessness, type of homelessness (street or shelter), and history of conduct disorder. Significant correlates of victimization included female gender, history of child abuse, and depression. CONCLUSIONS: Rates of criminal behavior, contacts with the criminal justice system, and victimization among homeless adults with severe mental illness are higher than among housed adults with severe mental illness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".