Using data and machine learning to improve suicide prevention for youth in the juvenile justice system
Epidemiologic and Machine Learning Approaches to Frame Suicide Prevention Strategies Among Juvenile Justice Youth - 2021
['FUNDING_CAREER'] · RESEARCH INST NATIONWIDE CHILDREN'S HOSP · NIH-11085984
This study is looking at why young people in the juvenile justice system are at a higher risk for suicide, especially when they return to their communities, and it aims to create helpful strategies to prevent this by understanding their unique needs and experiences.
Quick facts
| Phase | ['FUNDING_CAREER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | RESEARCH INST NATIONWIDE CHILDREN'S HOSP (nih funded) |
| Locations | 1 site (COLUMBUS, UNITED STATES) |
| Trial ID | NIH-11085984 on ClinicalTrials.gov |
What this research studies
This research investigates the high rates of suicidal behavior among youth in the juvenile justice system, particularly focusing on those reintegrating into the community after incarceration. It employs advanced machine learning techniques to analyze various youth characteristics and contextual factors that contribute to suicide risk. By developing a risk prediction model, the research aims to identify effective suicide prevention strategies tailored for this vulnerable population. The ultimate goal is to integrate these evidence-based strategies into routine reentry services for youth released from confinement.
Who could benefit from this research
Good fit: Ideal candidates for this research are youth aged 10-24 who have been incarcerated in the juvenile justice system and are facing challenges reintegrating into their communities.
Not a fit: Patients who are not involved in the juvenile justice system or who do not have a history of suicidal behavior may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved suicide prevention strategies that significantly reduce the risk of suicidal behavior among youth transitioning out of the juvenile justice system.
How similar studies have performed: Previous research has shown success in using machine learning approaches to predict mental health outcomes, indicating potential for this novel application in suicide prevention.
Where this research is happening
COLUMBUS, UNITED STATES
- RESEARCH INST NATIONWIDE CHILDREN'S HOSP — COLUMBUS, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: RUCH, DONNA — RESEARCH INST NATIONWIDE CHILDREN'S HOSP
- Study coordinator: RUCH, DONNA
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.