Symposia
Criminal Justice / Forensics
Sarah Helseth, Ph.D.
Brown University School of Public Health
Providence, Rhode Island
Grace J. Kim, NA
Undergraduate Student
Brown University School of Public health
Providence, Rhode Island
Dayna Price, BA
Assistant Professor
Brown University School Of Public Health
Providence, Rhode Island
Melissa A Clark, PhD
associate Dean for Education and Professor
Brown University School of Public Health
Providence, Rhode Island
Nancy P Barnett, PhD
Professor
Brown University School of Public health
Providence, Rhode Island
Anthony Spirito, PhD
Professor
Alpert Medical School of Brown University
Providence, RI
Sara J Becker, PhD
Associate Professor
Brown University School of Public health
Providence, Rhode Island
The synergistic, maladaptive relationship between substance use and juvenile justice (JJ) system involvement is well-established. Increasingly, youth who enter the JJ system are screened for substance use at intake, to identify those in need of treatment. Despite being identified as in-need, < 30% of justice involved youth (JIY) receive any kind of treatment (Dennis et al., 2019). Treatment rates are lowest among diverted JIY, or those who are not formally processed through the JJ system, in part because they are referred out rather than treated within the JJ system. Digital interventions would be ideal to treat diverted JIY: they are accessible, customizable, portable, and appealing to youth. Experts have called for the development of mobile health interventions tailored for JIY (Bath et al., 2018), but none exist to date.
This presentation details formative work on TECH (Teen Empowerment through Computerized Health; Authors et al., 2022), the first mobile app designed to help JIY reduce their use of cannabis, the most-used substance among JIY (Dir et al., 2020). Guided by principles of user-centered design (Mohr et al., 2017), app development began with an assessment of JIY’s needs and preferences. Fourteen JIY with past-year cannabis use completed in-depth interviews. Participants were male (57%), Non-Hispanic White (86%), reported lifetime cannabis use >100 times (64%), and averaged 16 years of age (SD=1). The Behavioral Intervention Technology model (BIT; Mohr et al., 2014), which maps theoretical aims (eg, clinical, usage, behavior change) onto technical components (eg, elements, characteristics, and workflow), informed interview guides and data analysis. Interviews assessed youth access to smartphones, online peer interactions, use of behavior change apps, JJ-specific concerns, and planned TECH app features. Interview coding followed a hybrid deductive and inductive approach. Emergent, inductive codes that did not fit within BIT were also captured.
Analysis revealed a strong preference for motivation, behavior change, and social interaction features in the TECH app. Emergent codes included technology in daily life, privacy on mobile apps, and perceived acceptability of behavior change apps. Youth were open to receive the TECH app from JJ staff and connect anonymously to other JIY, so long as the app was secure and not being monitored by JJ staff. In addition to guiding decision-making on the TECH app prototype, the current findings will directly inform any future efforts to build mobile health interventions for JIY in JJ settings.