Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Aug 6, 2025
Date Accepted: Jun 16, 2026
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Self-monitoring at a Glance: Exploring the Design Space of Glanceable Smartwatch Feedback Displays
ABSTRACT
Background:
Self-monitoring technologies are commonly used to promote health behavior change, with glanceable displays offering continuous feedback throughout the day. Yet, it is still unclear how various aspects of these glanceable representations affect their interpretability and usability.
Objective:
Our objective is to investigate the effects of three design factors—stylization, granularity, and salience—on users’ ability to understand glanceable smartwatch-based feedback on daily step goals.
Methods:
We conducted an online simulation study to examine how three design dimensions—stylization, salience, and granularity—influence the effectiveness of glanceable feedback displays. Stylization and salience were crossed in a 2×2 factorial design, while granularity varied from 1% to 20% progress increments. A total of 202 Amazon Mechanical Turk participants were randomly assigned to one of 16 smartwatch display conditions. In each condition, participants viewed feedback on daily step progress and estimated the level of progress shown. We collected estimation error, perceived usability, and acceptability through the questionnaire. Collected data were analyzed using generalized estimating equations (GEE) and linear regression.
Results:
High stylization reduced accuracy (+4.52 error points; P< .001) and negatively affected perceptions across six dimensions, including comprehension (P=.003), complexity (P<.001), and usability (P=.001). Granularity had a non-linear effect: error was lowest around 5–10%, with sharp increases at 20%. The 10% level also received the most favorable ratings, e.g., comprehension (+0.656, P=.003). Salience had no effect. Previous smartwatch users were less accurate than never-users (+7.46 points) but rated displays as more useful (P=.002) and easier to focus on (P<.001). Current users gave similarly positive ratings on attention and usefulness.
Conclusions:
These findings could help researchers design effective glanceable smartwatch feedback displays and expand the design space for glanceable feedback. Clinical Trial: N/A
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