BACKGROUND: Mental health systems worldwide face unprecedented strain due to rising psychological distress, limited access to care, and an insufficient number of trained professionals. Even in high-income countries, the ratio of patients to health care providers remains inadequate to address demand. Emerging technologies such as artificial intelligence (AI) and extended reality (XR) are being explored to improve access, engagement, and scalability of mental health interventions. When integrated into immersive metaverse environments, these technologies offer the potential to deliver personalized and emotionally responsive mental health care.
OBJECTIVE: This scoping review explores the state-of-the-art applications of AI and XR technologies in metaverse frameworks for mental health. It identifies technological capabilities, therapeutic benefits, and ethical limitations, focusing on governance gaps related to data privacy, patient-clinician dynamics, algorithmic bias, digital inequality, and psychological dependency.
METHODS: A systematic search was conducted across 5 electronic databases-PubMed, Scopus, IEEE Xplore, PsycINFO, and Google Scholar-for peer-reviewed literature published between January 2014 and October 2024. Search terms included combinations of "AI," "XR," "VR," "mental health," "psychotherapy," and "metaverse." Studies were eligible if they (1) involved mental health interventions; (2) used AI or XR within immersive or metaverse-like environments; and (3) were empirical, peer-reviewed articles in English. Editorials, conference summaries, and articles lacking clinical or technical depth were excluded. Two reviewers independently screened titles, abstracts, and full texts using predefined inclusion and exclusion criteria, with Cohen Īŗ values of 0.85 and 0.80 indicating strong interrater agreement. Risk of bias was not assessed due to the scoping nature of the review. Data synthesis followed a narrative approach.
RESULTS: Of 1288 articles identified, 48 studies met the inclusion criteria. The included studies varied in design and scope, with most studies conducted in high-income countries. AI applications included emotion detection, conversational agents, and clinical decision-support systems. XR interventions ranged from virtual reality-based cognitive behavioral therapy and exposure therapy to avatar-guided mindfulness. Several studies reported improvements in patient engagement, symptom reduction, and treatment adherence. However, many studies were limited by small sample sizes, single-institution settings, and lack of longitudinal validation. Ethical risks identified included opaque algorithmic processes, risks of psychological overdependence, weak data governance, and the exclusion of digitally marginalized populations.
CONCLUSIONS: AI and XR technologies integrated within metaverse settings represent promising tools for enhancing mental health care delivery through personalization, scalability, and immersive engagement. However, the current evidence base is limited by methodological inconsistencies and a lack of long-term validation. Future research should use disorder-specific frameworks; adopt standardized efficacy measures; and ensure inclusive, ethical, and transparent development practices. Strong interdisciplinary governance models are essential to support the responsible and equitable integration of AI-driven XR technologies into mental health care. The narrative synthesis limits generalizability, and the absence of a risk of bias assessment hinders critical appraisal.
