{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T03:16:25Z","timestamp":1786677385913,"version":"build-2736575974"},"reference-count":140,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Social anxiety often manifests through behaviors such as reduced gaze to the eyes and lower speech volume. While these markers have been examined in face-to-face interactions, large-scale assessments remain challenging. Social virtual reality (VR) offers a promising alternative by enabling naturalistic interactions in which behavior can be captured at scale, but it remains unclear if people show naturalistic behavior in such artificial environments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We examined whether behavioral and physiological markers associated with social anxiety in real-life interactions similarly emerge in dyadic social VR. We additionally examined whether these patterns overlap with patterns linked to the broader constructs of psychopathology and verticality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this cross-sectional study, 128 participants (105 females, 22 males, 1 diverse; age 18-51 years; mean age 22.60, SD 3.57 years), recruited from a university student population, engaged in a 30-minute avatar-mediated dyadic conversation in social VR while physically located in separate rooms. We assessed gaze toward the partner\u2019s eyes, smiling, and speaking behavior by using the VR headsets\u2019 built-in eye trackers, face trackers, and microphones, and assessed high-frequency heart rate variability (HF-HRV) by using an electrocardiogram.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Relationships between traits and behavioral and physiological measures were analyzed using linear mixed-effects models (\u03b1=.05). Social anxiety was linked to reduced gaze toward the partner\u2019s eyes while speaking (\u03b2=\u2013.20, 95% CI \u20130.35 to \u20130.04; t126=\u20132.51; P=.01), quieter speech (\u03b2=\u2013.18, 95% CI \u20130.35 to \u20130.01; t126=\u20132.12; P=.04), and reduced HF-HRV (\u03b2=\u2013.23, 95% CI \u20130.39 to \u20130.08; t119=\u20133.00; P=.003). These findings were not entirely specific to social anxiety, as Pearson correlations revealed similar patterns for social anxiety and psychopathology (r=0.94, 95% CI 0.75-0.99; t7=7.61; P&lt;.001), whereas verticality was linked to an overall opposite pattern (social anxiety: r=\u20130.92, 95% CI \u20130.98 to \u20130.65; t7=\u20136.14; P&lt;.001; psychopathology: r=\u20130.83, 95% CI \u20130.96 to \u20130.38; t7=\u20133.98; P=.005).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In dyadic interactions in social VR, social anxiety was associated with behavioral and physiological modulations similar to those observed in face-to-face interactions, indicating heightened social stress and submissiveness even in avatar-mediated communication. Patterns were similar for heightened psychopathology and reversed for verticality, indicating that these traits may lie on a shared social-behavioral spectrum. Extending previous research focused on face-to-face interactions or reactions toward artificial agents displayed in VR, this study is the first to provide a comprehensive account of the behavioral and physiological modulations associated with social anxiety in avatar-based human-human interactions. Since social VR setups allow researchers to assess a rich set of behavioral data as a byproduct of the setup\u2019s core functionality, the technique opens novel possibilities to detect social stress, track therapeutic progress, or tailor interventions to individual behavior when interactions take place in VR.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/79147","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T18:05:07Z","timestamp":1773252307000},"page":"e79147","source":"Crossref","is-referenced-by-count":1,"title":["Automated Inference of Social Anxiety From Behavior in Social Virtual Reality: Cross-Sectional Observational 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