JMIR Publications

ABSTRACT

Understanding and optimizing adolescent-specific engagement with behavior change interventions will open doors for providers to promote healthy changes in an age group that is simultaneously difficult to engage and especially important to affect. For digital interventions, there is untapped potential in combining the vastness of process-level data with the analytical power of artificial intelligence to understand not only how adolescents engage, but also how to enhance intervention efficacy through increased engagement. Rooted in the example of the INSPIRE narrative-centered Digital Health Behavior Change Intervention (DHBCI) for adolescent risky behaviors around alcohol use, we propose a framework for harnessing artificial intelligence to accomplish four goals that are pertinent to healthcare providers and software developers alike: measurement of adolescent engagement, modeling of adolescent engagement, optimization of current interventions, and generation of novel interventions. Operationalization of this framework with youth must be situated in the ethical use of this technology, and we have outlined the potential pitfalls of AI with particular attention to privacy concerns for stealth data collection among adolescents. Given how recently AI advances have opened up these possibilities in this field, the areas for further investigation are plenty.