Artificial Intelligence and Mental Health: Bibliometric Analysis

Abstract

Artificial intelligence (AI) is transforming mental health research and care by introducing tools for diagnosis, prevention, and treatment. This bibliometric analysis reviews 68 empirical studies (2004–2024) from Scopus and Web of Science, analyzed using LENS software. Results show a surge in publications after 2020, with strong contributions from the U.S., U.K., and Italy—led by institutions like the University of Washington and Sapienza University of Rome. AI technologies such as machine learning, chatbots, and mobile apps are widely used to detect depression and suicidal ideation and provide scalable psychological support. Mobile-based interventions—like chatbot therapy, mood tracking, and self-help platforms—are increasingly common and user-centered. While AI shows moderate effectiveness when combined with traditional therapy, challenges remain, including limited population diversity and unclear factors influencing user engagement. This study maps the current research landscape, highlighting key trends, leading institutions, and gaps. Findings stress the need for future research on interactivity, personalization, and mobile delivery to improve the reach and impact of AI-driven mental health interventions.