
JITAI for Mental Health
Delivering just-in-time adaptive interventions for adolescent mental health
Description
This project explores the design of just-in-time adaptive interventions (JITAIs) to support adolescent mental health, with a particular focus on anxiety in girls. Drawing from a lineage of work that began with iCoach (a self-curation system) and evolved through collaborations on social media-based prediction and delivery of JITAIs, the project has grown into a broader initiative on technology-assisted mental health support.
The project is now anchored in a DCIS COBRE grant focused on adolescent anxiety, bringing together an interdisciplinary team of researchers in HCI, clinical psychology, and computer science. Our work examines how mobile and wearable technologies can detect early signals of distress and deliver timely, personalized interventions to support young people's well-being.
Collaborators
Bill Hudenko, Sarah Preum, Steve Voida, Clayton Lewis, Ben Genzel
Keywords
mental health
anxiety
adolescents
girls
JITAI
social media
machine learning
Team Members
Emma Ricci-De Lucca
Allen Song
Vafa Batool
Dylan Moore
Liz Murnane
Sonny Tao
Pape Sow Traoré
Ajwa Shahid