JMIR Publications

ABSTRACT

Background:

The global shortage of trained mental health professionals has created a significant barrier to accessible mental healthcare, with patient-to-clinician ratios falling short even in well-resourced countries like the United States. Artificial Intelligence (AI) and Extended Reality (XR), when integrated within immersive metaverse environments, offer innovative approaches to augment mental healthcare delivery and extend its reach beyond traditional clinical settings.

Objective:

This scoping review aims to explore the state-of-the-art applications of AI and XR in metaverse frameworks for mental healthcare, assessing their capabilities and limitations while identifying key ethical challenges and societal risks. Specifically, it examines governance gaps related to data privacy, patient-clinician dynamics, algorithmic biases, digital inequality, and psychological dependency.

Methods:

A systematic search was conducted across five electronic databases for peer-reviewed literature published from 2014 to October 2024. The search incorporated terms related to XR, mental healthcare, psychotherapy, and the metaverse. Studies were screened against predefined eligibility criteria by two independent reviewers, with relevant data extracted and synthesized through a narrative review approach.

Results:

Of the 1,288 articles identified, 48 studies met the inclusion criteria. The reviewed literature highlighted diverse AI applications, including emotion recognition, therapy chatbots, and decision-support systems, alongside XR-enabled therapeutic interventions. Key ethical concerns included inadequate transparency in AI algorithms, data privacy vulnerabilities, and risks of AI-induced biases in therapeutic decisions. XR-driven interventions showed promise in enhancing therapy accessibility and engagement but raised concerns about psychological dependency and the exclusion of underprivileged populations due to digital inequality. While these technologies demonstrated potential efficacy in controlled settings, many studies relied on single-institution datasets and lacked longitudinal validation.

Conclusions:

AI-XR technologies hold transformative potential for addressing global mental healthcare challenges, but their adoption must be guided by ethical considerations. Future research must prioritize the development of inclusive, transparent, and equity-driven frameworks for responsible integration. Multicentre collaborations, public datasets, and rigorous regulatory standards will be essential to ensure sustainable innovation that balances scalability with patient safety and societal well-being.