A Virtual Reality–Based Cognitive Defusion Application for Youth Depression and Anxiety: Mixed Methods Experimental Study
Bibliographic record
Abstract
BACKGROUND: Third-wave psychological treatments such as acceptance and commitment therapy can be effective for improving depression and anxiety in youth. However, third-wave therapeutic techniques such as cognitive defusion can be abstract, challenging to learn, and difficult to apply in real-world settings. Translating these techniques into virtual reality (VR) may provide interactive, enjoyable, and concrete learning opportunities, potentially enhancing engagement and effectiveness. This study evaluated a novel VR application that translates the technique of cognitive defusion into a brief, gamified VR experience. OBJECTIVE: The objectives of this study were to evaluate the feasibility, acceptability, usability, and safety of the VR cognitive defusion application; examine whether it could improve negative thinking and mood states; and understand how it compared to a non-VR cognitive defusion exercise. METHODS: In a mixed methods experimental study, 20 young people completed both a VR and audio cognitive defusion exercise in a randomized order within a single session. Quantitative state-based measures were taken before and after each exercise, and a qualitative interview at the end focused on how the two experiences compared. RESULTS: It was feasible to recruit participants, and all participants completed both exercises and assessments. Both the VR and audio exercises were acceptable to participants, with qualitative themes highlighting a preference for VR due to the novel and engaging format; however, there was a need for better guidance and more personalized environments. No severe adverse events were reported, although one participant experienced distress during the VR exercise. Pretest-posttest effects showed improvements in thought discomfort, cognitive defusion, and state anger for both the VR and audio conditions (P<.05), with the latter showing broader improvements, including thought negativity, rumination, tension, depression, distress, and confusion (P<.05). CONCLUSIONS: The VR cognitive defusion application was feasible, safe, and acceptable for young people, with potential to enhance mental health treatment through an engaging and enjoyable approach to learning third-wave cognitive behavioral therapy techniques. While VR was preferred by participants, further refinements could improve effectiveness. Future research should focus on enhancing the VR application design based on user feedback, incorporating audio guidance, and conducting a larger trial in real-world settings to thoroughly evaluate the effectiveness and implementation of the VR application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".