Generative Artificial Intelligence Use and Adolescent Mental Health

Abstract

To synthesize recent literature on the relationships between generative artificial intelligence (GenAI) use and adolescents’ mental health, with particular attention to problematic use and psychiatric vulnerabilities. Emerging evidence suggests associations between GenAI use and a range of adolescent mental health outcomes, including depression, anxiety, psychosis-related experiences, externalizing behaviors, eating disorder risk, and suicidality. Problematic patterns of use, including dependency and emotional reliance, may be particularly relevant among adolescents with preexisting psychiatric vulnerabilities. Current evidence suggests that these relationships may be bidirectional: psychological distress can motivate GenAI use for companionship, emotional support, or escape, while problematic use may reinforce maladaptive beliefs, displace real-world relationships, and amplify existing vulnerabilities. However, evidence remains predominantly cross-sectional, limiting causal inference. GenAI may interact with and amplify underlying psychiatric vulnerabilities during adolescence, highlighting the importance of understanding patterns and motivations of use. Pediatricians and other clinicians caring for adolescents could consider not only the frequency of GenAI use but also motivations for use, problematic dependency, and socioemotional reliance. Identifying high-risk usage patterns of GenAI through longitudinal research, particularly among youth with preexisting psychiatric risks, may inform the development of tailored screening, intervention, and prevention strategies.