Wearable AR for Restorative Breaks: How Interactive Narrative Experiences Support Relaxation for Young Adults
Jindu Wang, Runze Cai, Shuchang Xu, Tianrui Hu, Huamin Qu, Shengdong Zhao, Ling-Ping Yuan
TL;DR
This work tackles how wearable AR can transform breaks for young knowledge workers by embedding lightweight restorative activities into engaging media. It introduces InteractiveBreak, a design framework based on seamless guidance, audio-centric media, and rise–peak–closure pacing, validated through a four-condition within-subject study with $N=16$. Results show smoother media-to-activity transitions, higher rest quality, and stronger post-break readiness for InteractiveBreak compared with passive video, reminders, or non-narrative guidance, supporting long-term adoption. The study contributes a reusable Seamless Guidance Unit pattern, a practical design framework for media-embedded AR breaks, and empirical evidence for AR-assisted restorative breaks with potential applicability across contexts and devices.
Abstract
Young adults often take breaks from screen-intensive work by consuming digital content on mobile phones, which undermines rest through visual fatigue and inactivity. We introduce a design framework that embeds light break activities into media content on AR smart glasses, balancing engagement and recovery. The framework employs three strategies: (1) seamlessly guiding users by embedding activity cues aligned with media elements; (2) transitioning to audio-centric formats to reduce visual load while sustaining immersion; and (3) structuring sessions with "rise-peak-closure" pacing for smooth transitions. In a within-subjects study (N = 16) comparing passive viewing, reminder-based breaks, and non-narrative activities, InteractiveBreak instantiated from our framework seamlessly guided activities, sustained engagement, and enhanced break quality. These findings demonstrate wearable AR's potential to support restorative relaxation by transforming breaks into engaging and meaningful experiences.
