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Virtual Reality Based Cognitive Behavioral Therapy for Social Anxiety Among Youths in Hong Kong
Sponsor: Hong Kong Shue Yan University
Summary
This randomized controlled trial evaluates the effectiveness of a VR-based CBT intervention for social anxiety-driven depression among Hong Kong youth (ages 15-24). Given the limitations of traditional CBT in addressing deep-seated fears, this study explores a more engaging and scalable alternative. Ninety participants with depressive symptoms and social difficulties will undergo six 60-minute VR sessions based on Clark and Wells' cognitive model of social phobia, with assessments at baseline, post-treatment, and three-month follow-up using the Social Phobia Inventory and PHQ-9. The study investigates whether VR intervention reduces social anxiety-driven depression and assesses its cost-effectiveness. Expected outcomes include symptom reduction, sustained benefits at follow-up, and evidence for VR as an innovative, scalable mental health intervention, informing clinical practice, research, and policy in Hong Kong and beyond.
Official title: Virtual Reality Based Cognitive Behavioral Therapy for Social Anxiety-Driven Depression Among Youths: A Randomized Controlled Trial
Key Details
Gender
All
Age Range
15 Years - 24 Years
Study Type
INTERVENTIONAL
Enrollment
90
Start Date
2025-11-01
Completion Date
2026-12-30
Last Updated
2025-09-15
Healthy Volunteers
Yes
Interventions
VR intervention
The intervention comprises six sessions of 60 minutes each. There are six VR scenarios such as a café, MTR, school scene, and classroom. The difficulty levels of these scenarios are determined by several factors: (1) the density and proximity of individuals present, as observed in a café or MTR setting, (2) the presence of familiar individuals, such as acquaintances or classmates who may be encountered and greeted in a school environment, and (3) the level of interaction required, such as engaging in a group discussion within a classroom. Participants have the flexibility to choose a different scenario for each session or repeat a previously selected one.