ArticleFrontiers in digital health2025
Simulated virtual reality experiences for predicting early treatment response in panic disorder.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Artificial Intelligence-Integrated Virtual Reality in Mental Health Care: A Scoping Review of Evidence, Clinical Applications, and Future Directions.Journal of clinical medicine · 2026Review
- Immersive metaverse art as a psychological intervention for depression and anxiety: a narrative review and multilevel model integrating engagement, cultural identity, and neurocognitive mechanisms.Frontiers in psychology · 2026Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Panic disorder (PD) is a disabling anxiety condition in which early improvement during treatment can predict better long-term outcomes. Objectives: This study investigated whether a newly developed virtual reality-based assessment tool, the Virtual Reality Assessment of Panic Disorder (VRA-PD), can help predict early treatment response in individuals with PD. Methods: In total, 52 participants, including 25 patients diagnosed with PD and 27 healthy individuals, were evaluated every 2 months over a 6-month period. Assessments included self-reported anxiety levels and heart rate variability measured during virtual reality scenarios, as well as standard clinical questionnaires. Patients with PD were further categorized based on their treatment progress into early responders ( Results: The model that combined virtual reality-based and conventional clinical data achieved higher accuracy (85%) and F1-score (0.71) than models using only clinical (accuracy: 77%, F1-score: 0.56) or only virtual reality data (accuracy: 75%, F1-score: 0.64). The most important predictors included anxiety levels during virtual scenarios, heart rate variability metrics, and scores from clinical scales such as the Panic Disorder Severity Scale and Anxiety Sensitivity Index. Conclusions: This study highlights the value of virtual reality-based assessments for predicting early treatment outcomes in PD. By providing ecologically valid and individualized measures, virtual reality may enhance clinical decision-making and support personalized mental healthcare.
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