Jiaxin Xu

Fostering human–robot bonding is increasingly recognized as an important goal in human–robot interaction design, yet little is still known about the antecedents and consequences of such bonds. This study investigated caregiving toward robots—defined here as providing emotional support to a robot that appears distressed—as a potential antecedent of bonding, and examined whether bonding was related to the robot’s persuasive effectiveness. Individual characteristics were also considered as potential moderators. In a between-subjects experiment, participants played a game with a robot, during which they either provided care to it (n = 30) or did not (n = 29). After the interaction, the robot attempted to persuade participants to stand up and walk around the room. Bonding was assessed using a set of psychological scales, and behavioral compliance with the robot’s persuasion was video-recorded and coded. The results showed that caregiving did not, in itself, increase bonding. However, participants with higher trait empathy reported stronger bonding after providing care to the robot. We also found that caregiving significantly increased compliance with the robot’s persuasion, and that it appeared to create a relational context in which bonding and compliance became positively associated. These findings shed light on the mechanisms underlying social bonding and social influence in human–robot interaction.

Social robots are increasingly applied as health behavior change interventions, yet actionable knowledge to guide their design and evaluation remains limited. This systematic review synthesizes (1) the behavior change strategies used in existing HRI studies employing social robots to promote health behavior change, and (2) the evaluation methods applied to assess behavior change outcomes. Relevant literature was identified through systematic database searches and hand searches. Analysis of 39 studies revealed four overarching categories of behavior change strategies: coaching strategies, counseling strategies, social influence strategies, and persuasion-enhancing strategies. These strategies highlight the unique affordances of social robots as behavior change interventions and offer valuable design heuristics. The review also identified key characteristics of current evaluation practices, including study designs, settings, durations, and outcome measures, on the basis of which we propose several directions for future HRI research.

To design social robots to effectively promote health behavior change, it is essential to understand how people respond to various health communication strategies employed by these robots. This study examines the effectiveness of two types of social control strategies from a social robot, relationship-focused strategies (emphasizing relational consequences) and target-focused strategies (emphasizing health consequences), in encouraging people to reduce sedentary behavior. A two-session lab experiment was conducted (n = 135), where participants first played a game with a robot, followed by the robot persuading them to stand up and move using one of the strategies. Half of the participants joined a second session to have a repeated interaction with the robot. Results showed that relationship-focused strategies motivated participants to stay active longer. Repeated sessions did not strengthen participants' relationship with the robot, but those who felt more attached to the robot responded more actively to the target-focused strategies. These findings offer valuable insights for designing persuasive strategies for social robots in health communication contexts.