Examining the Relationships between Cumulative Childhood Adversity and the Risk of Criminal Justice Involvement and Victimization among Homeless Adults with Mental Illnesses after Receiving Housing First Intervention
Bibliographic record
Abstract
OBJECTIVES: Exposure to adverse childhood experiences (ACEs) is associated with increased risk of criminal justice involvement and repeated victimization among homeless individuals. This study aimed to (1) examine whether the relationship between cumulative ACE score and odds of experiencing criminal justice involvement and victimization remains significant over time after receiving the Housing First (HF) intervention and (2) investigate the moderating effect of cumulative ACE score on the effectiveness of the HF intervention on the likelihood of experiencing these outcomes among homeless individuals with mental illnesses. METHODS: demonstration project that provided HF versus treatment as usual (TAU) to homeless adults with mental illness in five Canadian cities (N = 1,888). RESULTS: In all 4 follow-up time points, the relationship between cumulative ACE score and both outcomes remained significant, regardless of study arm (HF vs. TAU) and other confounding factors. However, cumulative ACE score did not moderate intervention effects on odds of experiencing either outcome, suggesting that the effectiveness of HF versus TAU, with regard to the odds of being victimized or criminal justice involvement, did not differ by cumulative ACE scores over the course of study. CONCLUSIONS: Findings suggest that providing services for homeless individuals with mental illness should be trauma informed and include specialized treatment strategies targeting the experience of ACEs and trauma to improve their treatment outcomes. An intensive approach is required to directly address the problem of criminal justice involvement and victimization in these individuals.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".