A Robot-Led Intervention for Emotion Regulation: from Expression to Reappraisal

Abstract

Emotion regulation (ER) is a crucial skill for managing emotions in everyday life, yet finding a constructive and accessible method to practice ER remains challenging due to cognitive demands. In this study, we explore how regular interactions with a social robot, conducted in a structured yet familiar environment within university halls and departments, can provide effective support for practising ER via cognitive reappraisal. Twenty-one students participated in a five-session study at a university hall or department in the U.K., where the robot (QTrobot, LuxAI), powered by a large language model (GPT 3.5) facilitated structured conversations, encouraging the students to reinterpret emotionally charged situations that they shared with the robot. Quantitative and qualitative results indicate significant improvements in ER, with participants reporting better understanding and control of their emotions, significant changes in constructive ER tendencies and positive effects on mood and sentiment after each session. The findings also demonstrate that repeated interactions with the robot encouraged greater emotional expression, including longer speech disclosures, increased use of affective language, and heightened facial arousal. Notably, expression peaked during key reappraisal moments, particularly when participants were prompted to reinterpret negative experiences. The qualitative feedback further highlighted how the robot fostered introspection and provided a supportive space for discussing emotions, enabling participants to confront long-avoided emotional challenges. These findings demonstrate the potential of robots to effectively assist in ER in familiar environments, offering both emotional support and cognitive guidance