This paper presents a design study exploring the effects of a social robot in facilitating people to participate in light-intensity exercises after a long duration of sitting in a shared workspace. A smart system based on a trolley-like robot, called the Anti-Sedentary Robot, was developed to realize the health intervention as follows. To start, the robot could navigate to the location of a sedentary worker to invite them to participate in a temporal voluntary service of returning items. Upon the invitation being accepted, the robot would then move with the worker to return the item and simultaneously provide guidance for physical exercises. Based on the Anti-Sedentary Robot, a within-subject study (n = 18) was carried out to examine exercise motivations and psychological benefits of our design by making comparisons between a robot-guided intervention and a human-guided intervention. Quantitative results showed that the health intervention based on the Anti-Sedentary Robot increased intrinsic motivations and provided acute mental benefits compared to the human-guided intervention. Qualitative findings suggested that the Anti-sedentary Robot could combat work-related sedentary behaviors due to the pleasant system interactivity and the provision of reciprocal voluntary tasks. We discuss implications for the future development of social robots for office vitality based on our research findings.

Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative process of storyboarding and how to develop AI-powered tools to support designers' individual workflows. In this work, we iteratively developed and implemented StoryDiffusion, a system that integrates text-to-text and text-to-image models, to support the generation of narratives and images in a single pipeline. With a user study, we observed 12 UX designers using the system for both concept ideation and illustration tasks. Our findings identified AI-directed vs. user-directed creative strategies in both tasks and revealed the importance of supporting the interchange between narrative iteration and image generation. We also found effects of the design tasks on their strategies and preferences, providing insights for future development.