Using Re-inforcement Learning to Automatically Adapt a Remote Therapy Intervention (RTI) for Reducing Adolescent Violence Involvement
NCT04850274 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 584
Last updated 2026-05-06
Summary
This study will use a randomized control trial (RCT) design to administer two versions of a multisession remote behavioral intervention for youth seeking Emergency Department care for a violent injury with the goal to reduce their violence involvement and associated negative behaviors and consequences. The study examines two versions of the remote therapy intervention - a standard RTI (S-RTI) and an Artificial Intelligence RTI (AI-RTI). The application of a just-in-time adaptive strategy to address youth violence is an important and novel direction for this research, particularly given the need to understand best practices for delivering behavioral interventions among lower-income populations.
Conditions
- Violence
- Substance Use
- Criminal Behavior
- Violence in Adolescence
Interventions
- BEHAVIORAL
-
Remote Therapy Intervention (RTI)
A single ED session followed by 5 remote therapy sessions
- BEHAVIORAL
-
Artificial Intelligence Remote Therapy Intervention
Optimized by reinforcement learning to step up or down the intensity of treatment between three levels based on patient response to daily assessments.
Sponsors & Collaborators
-
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
collaborator NIH - lead OTHER
Study Design
- Allocation
- RANDOMIZED
- Purpose
- TREATMENT
- Masking
- SINGLE
- Model
- PARALLEL
Eligibility
- Min Age
- 14 Years
- Max Age
- 24 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2021-05-19
- Primary Completion
- 2026-02-13
- Completion
- 2026-02-13
Countries
- United States
Study Locations
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