LLM-powered socially assistive robot-delivered cognitive behavioral therapy exercises: an exploratory study with university students
Mina Kian; Mingyu Zong; Katrin Fischer; Abhyuday Singh; Anna-Maria Velentza; Amy O'Connell; Lydia Ignatova; Pau Sang · 2026 · Frontiers in Robotics and AI
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Mental health is a significant healthcare challenge, and cognitive behavioral therapy (CBT) is a widely used therapeutic method for treating anxiety and depression. However, traditional CBT often requires access to trained clinicians and can be cost-prohibitive or logistically difficult for many individuals. To address these barriers, we developed a low-cost socially assistive robot (SAR) that uses a large language model (LLM) to guide the user through interactive at-home CBT exercises. In this exploratory study, 38 university students completed CBT exercises across a 15-day period using one o
Abstract by Mina Kian; Mingyu Zong; Katrin Fischer; Abhyuday Singh; Anna-Maria Velentza; Amy O'Connell; Lydia Ignatova; Pau Sang, Frontiers in Robotics and AI (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3389/frobt.2026.1802622