UNDERSTAND: Uplifting the New generation through DBT Education and Resilience for Social Triggers, Anxiety, Negativity, and Depression


Overview

Many college students experience comorbid depression and anxiety, exacerbating symptom severity and functional impairment. While evidence-based treatments like CBT and DBT demonstrate efficacy, they lack real-time, context-aware delivery at moments of heightened distress.

We are developing a mobile health (mHealth) system that leverages ubiquitous computing, wearable sensing, and machine learning to detect physiological and socio-behavioral indicators of distress in situ. Upon detection, the system delivers Just-In-Time Adaptive Interventions (JITAI) informed by DBT principles to provide personalized, contextually relevant support.

By targeting transdiagnostic mechanisms such as emotional dysregulation, interpersonal challenges, and cognitive distortions, our approach aims to improve scalability and relevance across diverse populations with comorbid mood and anxiety disorders.


Nadir Weibel
Nadir Weibel
Professor of Computer Science and Engineering
Manas Bedmutha
Manas Bedmutha
Ph.D. Student

Manas is currently working on developing technologies for supporting social wellbeing – across in-person conversations (social signal processing) as well as building digital just-in-time interventions (JITAIs) for social engagement

Aaron Broukhim
Aaron Broukhim
Ph.D. Student