Abstract
BACKGROUND: The rising prevalence of mental health disorders such as depression and anxiety challenges traditional treatments limited by resource shortages, poor accessibility, and low adherence. Digital health technologies-particularly digital mental health interventions-offer innovative, scalable, and personalized solutions. Mobile health applications, online cognitive behavioral therapy (CBT), and AI-driven tools are becoming essential in mental health care. METHODS: This study employs bibliometric methods to examine research trends and thematic evolution in digital mental health self-management interventions, using data retrieved from the Web of Science Core Collection (WoSCC). CiteSpace, VOSviewer, and Bibliometrix were applied to quantify research output, collaboration networks, and influential topics. The analysis covered English-language publications from 2006 to 2025, with internal consistency checks and sensitivity analyses within the WoSCC dataset ensuring robustness. RESULTS: A total of 2262 eligible publications were retrieved, showing a clear growth trajectory. The United States led with 932 publications, followed by the United Kingdom and Australia. Citations surged after 2016, peaking in 2023, reflecting increasing academic and clinical relevance. Research has shifted from feasibility studies to AI-enhanced and personalized interventions. Keywords such as "artificial intelligence," "digital CBT," and "personalized care" showed notable growth. International and interdisciplinary collaborations also expanded, underscoring the field's global integration. CONCLUSION: Digital mental health interventions are evolving from traditional models to intelligent, personalized solutions, providing scalable solutions to global mental health challenges. This study offers insights into future research directions, focusing on technology integration, ethical issues, and clinical validation to drive global application.