Matching services to adults with serious mental illness involved in the justice system
What works, for whom? Applying novel precision medicine methods to people with mental illness in the justice system.
This project uses new data methods to match justice-involved adults with serious mental illness to the services most likely to help them avoid re-offending.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project ID | NIH-11138765 on NIH RePORTER |
What this research studies
You would be part of work that uses modern data tools like causal inference and machine learning to find which supports—such as psychiatric care or cognitive behavioral therapy—help different people with serious mental illness who have been involved with the criminal justice system. The team will analyze records and real-world program experiences to identify subgroups who benefit from particular interventions instead of assuming one approach fits everyone. The project includes close mentorship and field experience to make sure methods reflect the needs of justice-involved people with SMI. The overall aim is to create better ways to match people to services that reduce future criminal justice involvement.
Who could benefit from this research
Good fit: Ideal candidates are adults (21+) with serious mental illness who have current or past involvement in the criminal justice system and who interact with mental health or reentry services.
Not a fit: People without a serious mental illness, without justice-system involvement, or under age 21 are unlikely to be helped by this specific project.
Why it matters
Potential benefit: If successful, this work could lead to more personalized treatment plans that lower the chance of re-offending for justice-involved people with serious mental illness.
How similar studies have performed: Previous work has shown that psychiatric services and cognitive behavioral programs can reduce recidivism on average, but using precision medicine and machine learning to match individuals to the right intervention is relatively new.
Where this research is happening
Chapel Hill, United States
- Univ of North Carolina Chapel Hill — Chapel Hill, United States (Active)
Researchers
- Principal investigator: Montoya, Lina — Univ of North Carolina Chapel Hill
- Study coordinator: Montoya, Lina
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.