Trends and knowledge structure of artificial intelligence and digital technologies for mental health: A Bibliometric analysis of international databases (2017–2025)

Abstract

This study aimed to analyze trends, knowledge structure, and academic collaboration networks in the field of Artificial Intelligence (AI) and digital technology in mental health using bibliometric analysis. Data were retrieved from the Dimensions database for the period 2017–2025 using keywords related to AI, digital technology, and mental health. Document selection followed the PRISMA guidelines, yielding 145 eligible articles, which were subsequently analyzed using VOSviewer and Biblioshiny. The findings revealed an exponential growth pattern in publication output, with a notable surge from 7 articles in 2021 to 61 articles in 2025, reflecting heightened global research interest in this domain. In terms of country-level distribution, China led with 40 documents and 474 citations, while the United States and the United Kingdom demonstrated higher per-document citation impact, highlighting the distinction between research quantity and quality. Journal co-citation network analysis identified four prominent journal clusters spanning digital psychology and behavioral science, clinical medicine, psychiatry and mental health, and developmental and educational sciences. Keyword co-occurrence analysis further delineated five major research clusters encompassing clinical and social dimensions, bibliometric methodology, public health, and the application of technology in international contexts. These findings indicate that this research field is highly interdisciplinary and remains in an expansive growth phase. The results offer valuable insights for researchers, academics, and policymakers in strategically directing future research on digital mental health.