Mapping the Knowledge Landscape of Virtual and Augmented Reality–Based Interventions for Depression: A Bibliometric and Visualized Analysis (Preprint)

BACKGROUND Background: Virtual and augmented reality (VR/AR) technologies have gained increasing attention as digital interventions for depression due to their ability to provide immersive and controllable therapeutic environments. Although research output has expanded rapidly over the past decade, a systematic overview of the field’s intellectual structure, thematic evolution, and emerging priorities is still lacking. OBJECTIVE Objectives: This study aimed to map the global research landscape of VR/AR-based interventions for depression using bibliometric and visual analytic methods. METHODS Methods: Publications related to VR/AR and depression published between 2016 and 2025 were retrieved from the Web of Science Core Collection. Bibliometric analyses and network visualizations were conducted using VOSviewer, CiteSpace, Bibliometrix (R package), SCImago Graphica, and Microsoft Excel. Analyses covered annual publication trends, country and institutional collaboration networks, author and journal co-citation patterns, keyword co-occurrence, citation burst detection, thematic evolution, and strategic thematic mapping. RESULTS Results: A total of 810 publications were included, showing a pronounced increase in both annual output and citation impact. China contributed the largest number of publications, whereas the United States and the United Kingdom demonstrated greater citation influence. Keyword and cluster analyses identified five major thematic domains: transdiagnostic mental health applications, neurological rehabilitation, pain management and oncology supportive care, cognitive and aging-related research, and methodological evaluation. Temporal analyses revealed a shift from early anxiety- and cognitive behavioral therapy–focused studies toward broader clinical translation, pediatric populations, and intervention-oriented research in recent years. Strategic thematic mapping indicated that several core themes have reached relative maturity, while emerging topics related to intervention optimization and real-world application remain underdeveloped. CONCLUSIONS Conclusions: VR/AR-based interventions for depression have progressed from exploratory research toward thematic consolidation and clinical expansion. Nevertheless, limited emphasis on mechanistic understanding, implementation science, and geographic diversity suggests that future progress will depend on strengthening methodological rigor and enhancing translational relevance to support real-world mental health care.