Using Artificial Intelligence to Support Adoption and Adherence to Lifestyle Behaviors
School-based health promotion programs are widely implemented to improve dietary behaviors, physical activity, and other lifestyle-related outcomes of children and adolescents. However, the effectiveness of interventions is often inconsistent, and sustaining long-term behavior change remains a persistent challenge. Limited adoption, engagement, and adherence may stem from the inability of traditional one-size-fits-all approaches to account for differences in participants’ biological, behavioral, environmental, and social contexts. However, hyper-personalized lifestyle medicine, enabled by recent advances in artificial intelligence (AI), offers a promising framework for integrating multidimensional health data to deliver individualized prevention and intervention strategies at scale. In this perspective, we discuss how AI-driven technologies, including predictive analytics, wearable devices, mobile health applications, conversational agents, and virtual assistants, may enhance the personalization, scalability, and sustainability of community-based health promotion programs, including schools. We also discuss practical challenges associated with implementing hyper-personalized approaches in community settings and propose collaborative models involving schools, researchers, healthcare professionals, and participants to support effective adoption.
Authors
- Aliye B. Cepni (ORCID: https://orcid.org/0000-0002-6303-8378)
- C.Y. Yoon
- Craig A. Johnston
Institutions
- University of Houston (US)
- Pusan National University (KR)
Publication Details
- Journal
- American Journal of Lifestyle Medicine
- Published
- 2026-07-18
- DOI
- https://doi.org/10.1177/15598276261466926
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Houston