Internet-Based Cognitive Behavioral Therapy and Virtual Reality Exposure Therapy for Social Anxiety Disorder: Protocol for a Randomized Controlled Trial in Hong Kong
Bibliographic record
Abstract
BACKGROUND: Social anxiety disorder (SAD), also known as social phobia, is one of the most common mental disorders worldwide. In Hong Kong, the prevalence of SAD is high, but its treatment rate is low. SAD has immense impact on academic or work performance, social life, career development, and quality of life. One of the most effective treatments for SAD is cognitive behavioral therapy (CBT), with internet-based CBT (iCBT) and virtual reality exposure therapy (VRET) showing promise in treating SAD. However, internet interventions are underdeveloped in Chinese communities including Hong Kong. OBJECTIVE: This study aims to develop an iCBT program that includes VRET, called "Ease Anxiety in Social Event Online" (Ease Online), for Hong Kong adults with SAD in a randomized controlled trial. METHODS: The 14-week Ease Online program is a guided self-help iCBT program with a blended mode of service delivery. The program comprises 9 web-based modules and 5 individual counseling sessions (including 2 VRET sessions) conducted remotely or face-to-face with a therapist to provide therapist support, as guided iCBT shows superior effects than unguided iCBT. Other program components include therapist feedback on assignments, internal messages, forums, client portfolios, web-based questionnaires, reminders, and web-based bookings. The program can be accessed either through a mobile app or program website through a PC with an internet connection. The participants are openly recruited and screened using a questionnaire and through an intake interview. Eligible participants are randomized by placing them into a web-based iCBT group, app-based iCBT group, or a waitlist control (WLC) group. Participants in the WLC group are assigned to the app-based program upon completion of the service of the 2 experimental groups. Measurements of social anxiety, depression and anxiety symptoms, psychological distress, automatic thoughts, and quality of life are administered at pretest, posttest, and 3- and 6-month follow-ups. Multivariate ANOVA with repeated measures will be performed to determine the intervention effectiveness on the continuous variables over time. RESULTS: Participant recruitment commenced in January 2021. As of February 2023, a total of 1811 individuals applied for the Ease Online program. In total, 401 intake interviews have been completed, and 329 eligible participants have joined the program, among whom 166 have completed the service. Data collection is still ongoing, which is expected to be completed in March 2024. CONCLUSIONS: This study is the first of its kind in combining iCBT and VRET for the treatment of SAD in Hong Kong. At a theoretical level, this study contributes to the development and evaluation of internet-based psychological interventions in Hong Kong. At a practical level, the Ease Online program may serve as an alternative service option for SAD clients in Hong Kong if proven effective. TRIAL REGISTRATION: ClinicalTrials.gov NCT04995913; https://clinicaltrials.gov/study/NCT04995913. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48437.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.065 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".