STUDY PROTOCOL: EXPOSURE IN VIRTUAL REALITY FOR SOCIAL ANXIETY DISORDER - a randomized controlled superiority trial comparing cognitive behavioral therapy with virtual reality based exposure to cognitive behavioral therapy with in vivo exposure
Bibliographic record
Abstract
BACKGROUND: Social Anxiety Disorder (SAD) is characterized by an intense fear of negative judgement by others. Cognitive Behavioral Therapy (CBT) is recommended for treatment, but a substantial part of individuals with SAD either do not seek treatment or drop-out. CBT with Virtual Reality (VR)-based exposure has several advantages compared to traditional exposure methods, mainly due to increased control of situational elements. The aim of the current study is to develop a CBT program containing VR-based exposure. The intervention is targeted to adult patients suffering from SAD and treatment effect will be assessed by changes in SAD symptoms. METHODS: This article describes the study protocol of a Randomized Controlled Trial with three arms: 1) CBT with VR exposure based on 360° videos 2) CBT with in vivo exposure and 3) VR relaxation therapy. There will be 30 participants in each arm with a crossover at the end of the treatment period during which the participants in the third group will be randomly re-allocated to one of the two former groups. The treatment program consists of 10 weekly individual sessions with a psychologist, and a six month follow-up consisting of a questionnaire. The primary outcome measure is reduction in SAD symptoms which will be assessed with the Social Interaction Anxiety Scale (SIAS). DISCUSSION: There are currently no published studies on CBT with VR exposure based on 360° videos for SAD treatment. Furthermore, the current study will be the first Danish SAD treatment program that includes VR technology. TRIAL REGISTRATION: clinicaltrials.gov (NCT03973541) June 3rd 2019.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.047 | 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".