collaborators

9 papers

cs.HC2026

Engagement Phenotypes for a Sample of 102,684 AI Mental Health Chatbot Users and Dose-Response Associations with Clinical Outcomes

Emma C. Wolfe, Ting Su, Olivier Tieleman +3

Background: Conversational AI chatbots are emerging as scalable mental health tools, but little is known about real world engagement or its relationship to clinical outcomes. Objec…

cs.HC2026

Functional outcomes and naturalistic engagement with a purpose-built conversational AI for mental health (Ash)

Kristen M. Van Swearingen, Thomas D. Hull, Karthik V. Sarma +1

Background: Conversational AI chatbots designed for mental health may offer an accessible, scalable avenue for supporting psychological well-being, yet prior evaluations have large…

cs.CL2026

Fine-tuning LLMs for Passive Depression Severity Estimation from AI Mental Health Dialogue

Olivier Tieleman, Ziyi Zhu, Ting Su +3

Depression is the leading cause of disability worldwide, and early detection of symptom change is essential for timely intervention. Validated instruments such as the Patient Healt…

cs.CL2026

DIAL: Direct Iterative Adversarial Learning for Realistic Multi-Turn Dialogue Simulation

Ziyi Zhu, Olivier Tieleman, Caitlin A. Stamatis +5

Realistic user simulation is crucial for training and evaluating multi-turn dialogue systems, yet creating simulators that accurately replicate human behavior remains a significant…

cs.HC2026

Talking to a Human as an Attitudinal Barrier: A Mixed Methods Evaluation of Stigma, Access, and the Appeal of AI Mental Health Support

Caitlin A. Stamatis, Emma C. Wolfe, Matteo Malgaroli +1

Background: Many people who could benefit from therapy do not receive it. Conversational AI is increasingly used for mental health support, yet it is unclear which barriers AI help…

cs.CL2026

Language Markers of Emotion Flexibility Predict Depression and Anxiety Treatment Outcomes

Benjamin Brindle, George A. Bonanno, Thomas Derrick Hull +2

Predicting treatment non-response for anxiety and depression is challenging, in part because of sparse symptom assessments in real-world care. We examined whether passively capture…