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Context-Aware Micro-Interventions for Social Anxiety

NIMH R01

Using mobile and wearable sensing and AI to recognize when social anxiety is most likely to arise and deliver personalized support when it matters most.

Pipeline: during a social interaction, wearable and mobile sensing infer a person's momentary state; the phone flags elevated social anxiety and delivers a brief, timely breathing intervention.
From everyday social interactions, wearable and mobile sensing infer a person's momentary social-anxiety state in real time — triggering brief, just-in-time interventions exactly when support is needed.

Description

Social anxiety happens in context—meeting someone new, navigating a conversation, or moving through a socially demanding day—yet most digital interventions know little about what is happening in a person's life when support is delivered. This project combines mobile and wearable sensing with multimodal AI to characterize social behavior, physiology, and context in everyday life and understand how these patterns vary across individuals and over time. We use these insights to develop context-aware micro-interventions: brief, personalized support designed to be delivered at moments when it may be most useful, moving digital mental health toward systems that adapt to the person, the moment, and the social context.

Publications

  • 2025 E. R. Toner, M. Rucker, Z. Wang, M. A. Larrazabal, L. Cai, D. Datta, H. Lone, M. Boukhechba, B. A. Teachman, L. E. Barnes. "Wearable Sensor-Based Multimodal Physiological Responses of Socially Anxious Individuals in Social Contexts on Zoom." IEEE Trans. Affective Computing, 16(3), 2025.
  • 2024 V. Reddy, Z. Wang, E. R. Toner, M. A. Larrazabal, M. Boukhechba, B. A. Teachman, L. E. Barnes. "AudioInsight: Detecting Social Contexts Relevant to Social Anxiety from Speech." Int. Conf. on Affective Computing and Intelligent Interaction (ACII), 2024.
  • 2023 Z. Wang, M. A. Larrazabal, M. Rucker, E. R. Toner, K. E. Daniel, S. Kumar, M. Boukhechba, B. A. Teachman, L. E. Barnes. "Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals." Proc. ACM IMWUT, 7(3), 2023.
  • 2023 Z. Wang, M. Rucker, E. R. Toner, M. A. Larrazabal, M. Boukhechba, B. A. Teachman, L. E. Barnes. "Understanding Privacy Risks versus Predictive Benefits in Wearable Sensor-Based Digital Phenotyping: A Quantitative Cost-Benefit Analysis." IEEE BSN, 2023.
  • 2023 Z. Wang, M. Tang, M. A. Larrazabal, E. R. Toner, M. Rucker, C. Wu, B. A. Teachman, M. Boukhechba, L. E. Barnes. "Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline." IEEE EMBC, 2023.

Team