Impacto de la inteligencia artificial en la salud mental de adolescentes y jóvenes: revisión sistemática
Keywords:
artificial intelligence; mental health; adolescents; machine learning; chatbots; PRISMA.Abstract
Introduction: Mental disorders affect between 10% and 20% of adolescents and young adults, making them a global health priority. In this context, artificial intelligence is emerging as a promising tool for reducing gaps in the detection, diagnosis, and intervention of mental health conditions.
Objective: To synthesize the available evidence on the impact of artificial intelligence applications on the mental health of adolescents and young adults.
Methods: A systematic review was conducted in accordance with the PRISMA 2020 guidelines using PubMed, PsycINFO, the Cochrane Library, CINAHL, Embase, Web of Science, Scopus, IEEE Xplore, and Google Scholar. Studies published between January 2010 and July 2025 were included. Two independent reviewers performed the study selection, data extraction, and methodological quality assessment.
Results: Of the 3,742 records identified, 62 met the inclusion criteria. The applications were classified into chatbots and conversational agents for therapeutic intervention (n= 31), machine-learning models for risk prediction and diagnosis (n= 24), and natural language processing tools for symptom detection (n= 7). In this regard, chatbots produced small to moderate effects in reducing mental health problems (standardized mean difference [SMD]: −0.35; 95% CI: −0.46 to −0.24), with significant improvements in depression (SMD: −0.43) and anxiety (SMD: −0.37). Machine-learning models demonstrated promising predictive performance for suicidal behaviors (AUC: 0.79–0.84).
Conclusions: Artificial intelligence may support early intervention and risk prediction; however, the evidence remains insufficient to recommend its widespread clinical implementation.
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