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Background  Risk communication involves conveying two inherently difficult concepts about the nature of risk: the underlying random distribution of outcomes and how a population-based proportion applies to an individual.    Objective  The objective of this study was to test whether 4 design factors in icon arrays—animated random dispersal of risk events, avatars to represent an individual, personalization (operationalized as choosing the avatar’s color), and a moving avatar—might help convey randomness and how a given risk applies to an individual, thereby better aligning risk perceptions with risk estimates.    Methods  A diverse sample of 3630 adults with no previous heart disease or stroke completed an online nested factorial experiment in which they entered personal health data into a risk calculator that estimated 10-year risk of cardiovascular disease based on a robust and validated model. We randomly assigned them to view their results in 1 of 10 risk graphics that used different combinations of the 4 design factors. We measured participants’ risk perceptions as our primary outcome, as well as behavioral intentions and recall of the risk estimate. We also assessed subjective numeracy, whether or not participants knew anyone who had died of cardiovascular causes, and whether or not they knew their blood pressure and cholesterol as potential moderators.    Results  Animated randomness was associated with better alignment between risk estimates and risk perceptions ( F   1,3576 =6.12,  P =.01); however, it also led to lower scores on healthy lifestyle intentions ( F   1,3572 =11.1,  P <.001). Using an avatar increased risk perceptions overall ( F   1,3576 =4.61,  P =.03) and most significantly increased risk perceptions among those who did not know a particular person who had experienced the grave outcomes of cardiovascular disease ( F   1,3576 =5.88,  P =.02). Using an avatar also better aligned actual risk estimates with intentions to see a doctor ( F   1,3556 =6.38,  P =.01). No design factors had main effects on recall, but animated randomness was associated with better recall for those at lower risk and worse recall for those at higher risk ( F   1,3544 =7.06,  P =.01).    Conclusions  Animated randomness may help people better understand the random nature of risk. However, in the context of cardiovascular risk, such understanding may result in lower healthy lifestyle intentions. Therefore, whether or not to display randomness may depend on whether one’s goal is to persuade or to inform. Avatars show promise for helping people grasp how population-based statistics map to an individual case.

Animated Randomness, Avatars, Movement, and Personalization in Risk Graphics