LLM搭載の社会的支援ロボットは認知行動療法を安全かつ効果的に提供できるか：大学生を対象とした検討
Can an LLM-Powered Socially Assistive Robot Effectively and Safely Deliver Cognitive Behavioral Therapy? A Study With University Students
LLMを活用した社会的支援ロボットが自宅での認知行動療法を導くシステムを開発し、大学生38名を対象に15日間の比較実験を行ったところ、ロボット条件はチャットボット条件より心理的苦痛の軽減とセッション直後の不安低減に優れる可能性が示された。
著者: Mina J. Kian, Mingyu Zong, Katrin Fischer, Abhyuday Singh, Anna-Maria Velentza, Pau Sang, Shriya Upadhyay, Anika Gupta, Misha A. Faruki, Wallace Browning, Sebastien M. R. Arnold, Bhaskar Krishnamachari, Maja J. Mataric
分類: cs.RO
原文アブストラクト
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.
