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VR-based psychotherapy intervention on alleviating depression and anxiety for Hong Kong populations: a mixed method pilot implementation study

Int Rev Psychiatry. 2026 Feb 16:1-9. doi: 10.1080/09540261.2026.2631758. Online ahead of print.

ABSTRACT

The increasing prevalence of common mental disorders such as depression and anxiety found in Hong Kong, coupled with substantial public healthcare service gaps, necessitates accessible and immediate therapeutic interventions. This pilot implementation study investigated the feasibility, safety and acceptability of a culturally and linguistically adapted Virtual Reality (VR)-based psychotherapy intervention for Cantonese-speaking adults experiencing mild-to-moderate depression and anxiety in Hong Kong. Employing a sequential explanatory mixed-methods design, the study utilized four culturally specific VR scenarios, namely “Crying Girl” (targeting depression/self-compassion), “MTR” (enabling social anxiety exposure), “Emigration” (addressing separation-related anxiety), and “Rock-paper-scissors” (enhancing prosocial functioning). Quantitative pre-post assessments were combined with qualitative semi-structured interviews and focus groups to explore user experience, immersion, and perceived therapeutic mechanisms. Preliminary quantitative findings indicated statistically significant reductions in depressive symptoms and increases in self-compassion in the “Crying Girl” scenario, alongside reductions in stress in the “MTR” scenario. Focus groups and interviews revealed that participants highly valued immersion, ecological validity, and culturally resonant scenarios in therapeutic practice. Barriers such as technical imperfections, device complexity, and interface demands were identified, particularly for users with limited digital experience. This pilot study highlights the premise of culturally adapted VR psychotherapy as a safe and engaging intervention, emphasizing the need for user-centred design iterations to improve accessibility and subsequent larger controlled trials to rigorously evaluate efficacy and inform real-world implementation.

PMID:41693503 | DOI:10.1080/09540261.2026.2631758

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