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Can an LLM-Powered Socially Assistive Robot Effectively and Safely Deliver Cognitive Behavioral Therapy? A Study With University Students

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arxiv 2402.17937 v1 pith:V35E2JYM submitted 2024-02-27 cs.RO

Mina J. Kian , Mingyu Zong , Katrin Fischer , Abhyuday Singh , Anna-Maria Velentza , Pau Sang , Shriya Upadhyay , Anika Gupta
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Misha A. Faruki Wallace Browning Sebastien M. R. Arnold Bhaskar Krishnamachari Maja J. Mataric
This is my paper · ORCID
classification cs.RO
keywords robotanxietytherapeuticassistivebehavioralchatbotcognitivecompleting
verification ladder T0 review T1 audit T2 compute T3 formal
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Cognitive behavioral therapy (CBT) is a widely used therapeutic method for guiding individuals toward restructuring their thinking patterns as a means of addressing anxiety, depression, and other challenges. We developed a large language model (LLM)-powered prompt-engineered socially assistive robot (SAR) that guides participants through interactive CBT at-home exercises. We evaluated the performance of the SAR through a 15-day study with 38 university students randomly assigned to interact daily with the robot or a chatbot (using the same LLM), or complete traditional CBT worksheets throughout the duration of the study. We measured weekly therapeutic outcomes, changes in pre-/post-session anxiety measures, and adherence to completing CBT exercises. We found that self-reported measures of general psychological distress significantly decreased over the study period in the robot and worksheet conditions but not the chatbot condition. Furthermore, the SAR enabled significant single-session improvements for more sessions than the other two conditions combined. Our findings suggest that SAR-guided LLM-powered CBT may be as effective as traditional worksheet methods in supporting therapeutic progress from the beginning to the end of the study and superior in decreasing user anxiety immediately after completing the CBT exercise.

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Cited by 2 Pith papers

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  1. Personalized Socially Assistive Robots With End-to-End Speech-Language Models For Well-Being Support

    cs.RO 2025-07 conditional novelty 6.0 of 10

    An end-to-end speech-language model integrated into a social robot was perceived as empathetic and natural in a small study, but movement and voice expressiveness remain weak.

  2. CoRI: Communication of Robot Intent for Physical Human-Robot Interaction

    cs.RO 2025-05 conditional novelty 6.0 of 10

    CoRI automatically generates natural-language intent statements from a robot's image view and planned trajectory, and its user study shows it outperforms scripted and no-communication baselines in clarity.

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