Clinical Research Directory
Browse clinical research sites, groups, and studies.
Personalized AI-Driven Models in Cognitive Behavioral Therapy for Anxiety
Sponsor: University of Southern California
Summary
Untreated anxiety undermines long-term physical and emotional wellbeing, especially among college students, with rates worsening since the onset of the COVID-19 pandemic. Cognitive Behavioral Therapy (CBT) is the leading evidence-based intervention for anxiety, but many students fail to complete exercises between CBT sessions, reducing its effectiveness. Socially assistive robots (SARs) help promote adherence to home-based practice in the context of elder care, social skill learning, and physical therapy, but it is unknown how SARs can enhance CBT. The specific objective of this research is to develop personalized CBT SARs that can support CBT compliance for college students with anxiety. To meet the goals of the proposed work, these studies will determine how SAR personalization based on implicit and explicit feedback can help promote greater CBT compliance and anxiety reduction outcomes for students.
Official title: SCH: Personalized AI-Driven Models for Supporting User Engagement and Adherence in Health Interventions: Validation in Cognitive Behavioral Therapy for Anxiety
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
140
Start Date
2026-03
Completion Date
2028-08
Last Updated
2026-02-27
Healthy Volunteers
No
Conditions
Interventions
Explicit CBT SAR Personalization for 6 weeks
College student participants with clinically elevated anxiety will engage in 6 weeks of in-home CBT daily exercises with an explicitly personalized CBT SAR in the participants' homes. Participants will receive personalized re-engagement feedback delivered by the SAR will be based on explicit user feedback regarding their subjective preferences related to the robot attributes and engagement features.
Implicit CBT SAR Personalization for 6 weeks
College student participants with clinically elevated anxiety will engage in 6 weeks of in-home CBI daily exercises with an implicitly personalized CBT SAR in the participants' homes. The personalized re-engagement feedback provided by the SAR will be based on machine learning methods applied to implicit visual and auditory cues.
Control CBT SAR for 6 weeks
College student participants with clinically elevated anxiety will engage in 6 weeks of in-home CBT daily exercises with a non-personalized CBT SAR. Participants will not have the capability to personalize the robot's attributes, and this condition will be a control baseline comparison group for the personalized intervention conditions described above.