Developing a Least Restrictive Program for Re-Entering Transition Age Youth Pursuing Higher Education: A Pre-Implementation Evaluation

The following project is one of five funded Collaboration projects:

PI: Johanna Folk (UCSF)

Co-Investigators: Cynthia Valencia (UCSF), Michael Massa (OYCR), Jocelyn Meza (UCLA)

Institutions/Organizations: UCSF, UCLA, OYCR, Cre8Innovations

Abstract: Youth incarceration is incredibly costly, associated with a range of adverse health outcomes, and ineffective at preventing future legal system contact. Conversely, higher educational attainment is associated with reduced recidivism risk and positive life outcomes, including overall health and well-being. With the recent Department of Juvenile Justice facility closures in California, Least Restrictive Programs (LRP) have emerged as promising alternative placements for youth interested in pursuing higher education. These community-based placements are more developmentally oriented and cost-effective than incarceration and have the potential to support young people in navigating socialization challenges associated with re-entry while pursuing higher education. A community-based organization (Cre8Innovations), led by formerly incarcerated young adults and working in partnership with the Office of Youth and Community Restoration, is actively developing a LRP for transition age youth stepping down from Secure Youth Treatment Facilities and pursuing higher education in the San Francisco Bay Area. Grounded in pre-implementation science frameworks, the proposed study aims to assess and document barriers and facilitators to developing this LRP while honoring lived expertise, leveraging the expertise of an interdisciplinary team, and utilizing community participatory research methods. Mixed methods will be used to assess the needs of the population and identify evidence-informed interventions to integrate into the LRP curriculum, mentorship programming, and supervision practices. Findings will inform the implementation and evaluation of the LRP and serve as a blueprint for future LRP scalability.

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