Exploring the Design Space of Glanceable Smartwatch Feedback Displays: Experimental Study

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