An online survey of encouragement strategies for older adults’ daily worries: a conversational robot versus a human partner
Conversational robots are increasingly proposed to provide everyday emotional support for older adults. However, it remains unclear which encouragement strategies are perceived as effective and whether interpersonal strategy preferences transfer to Human–Robot Interaction (HRI). This study compared the perceived effectiveness of five encouragement strategies when delivered by a conversational robot versus a human partner, examined moderation by worry type, and explored associations with recipients’ emotional states. Japanese young-old adults aged 65–74 (final N = 55) completed an online scenario-based survey. Participants were randomly assigned to a human or conversational robot condition, each combining an identity label with distinct voice characteristics (a human-recorded voice or a robot-recorded voice). They recalled one physical and one psychological daily worry and rated perceived encouragement for five strategy types: reassurance and affirmation, expressing concern, encouragement to act, offering specific actions, and distraction. Within-subject standardized ratings were analyzed using linear mixed-effects models with a participant random intercept. Positive and Negative Affect Schedule (PANAS) were examined exploratorily. Results showed that perceived effectiveness differed by strategy type and notably by condition. In the human condition, offering specific actions showed the highest relative effectiveness, with descriptively clearer differentiation among strategies. In the robot condition, reassurance and affirmation ranked highest, and differentiation among strategies was descriptively reduced. Distraction was consistently least preferred. The present study did not observe a statistically significant effect of worry type on the overall ranking patterns. Exploratory analyses suggested that positive affect was associated with encouragement evaluation at the raw-score level in the robot condition, whereas associations involving negative affect did not survive correction for multiple comparisons and are therefore interpreted descriptively rather than as statistically significant findings. These findings suggest that interpersonal encouragement strategy preferences may not directly transfer to human–robot interaction as operationalized in the present study. The observed differences between conditions may reflect the combined effect of the identity label and voice characteristics rather than the robot’s identity alone. The results highlight the need for partner-specific, context-adaptive encouragement design in conversational robots for older adults.