J-2 AVATARS AND ANIMATION OF RANDOMNESS IN RISK GRAPHICS HELP PEOPLE BETTER UNDERSTAND THEIR RISK OF CARDIOVASCULAR DISEASE

Tuesday, October 25, 2011: 1:15 PM
Grand Ballroom EF (Hyatt Regency Chicago)
(DEC) Decision Psychology and Shared Decision Making

Holly O. Witteman, PhD1, Andrea Fuhrel-Forbis1, Mark Dickson, MA1, Harindra C. Wijeysundera, MD2 and Brian J. Zikmund-Fisher, PhD1, (1)University of Michigan, Ann Arbor, MI, (2)Schulich Heart Center, Sunnybrook Health Sciences Center, Toronto, ON, Canada

Purpose: To test whether using 1) an avatar (a figure representing an individual) and 2) animations of randomness in a pictograph help people better understand a personal health risk by explicitly showing 1) how population-based statistics apply to individuals and 2) the random element of risk estimates.

Methods: 3676 adults in a demographically diverse US-based online sample (mean age 53, 55% female, 78% white, 54% no college degree) with no history of cardiovascular disease entered their personal health information in a validated model that calculates 10-year risk of general cardiovascular disease (CVD risk). The median 10-year risk of CVD within this population was 8% (interquartile range 11%). Risk levels were classified as low if <5% (24% of participants), moderate if 5-9% (32%) and high if 10% or higher (45%). Participants were randomized to different versions of an animated pictograph showing their CVD risk. Pictographs either included an avatar or not, and were either standard versions that grouped all event rectangles together or versions that first displayed event rectangles randomly distributed in the pictograph before transitioning to a standard version. Participants answered a brief set of questions about their risk perceptions (how large or small the risk feels and how likely do they think they are to have CVD in the next ten years) and their behavioral intentions in the next 30 days. At the conclusion of the survey, participants were asked to recall their risk estimate.

Results: Using an avatar in the graphic increased perceptions of CVD likelihood for those at moderate and high risk (F(1,2792)=8.45, p=.004), but not for those at low risk. Using animated randomness made lower risks feel smaller and less likely, and higher risks feel larger (F(2,3623)=3.40, p=.03) and more likely (F(2,3669)=4.28, p=.01). Both avatars (F(2,3648)=6.03, p=.002) and animated randomness (F(2,3648)=3.95, p=.02) resulted in people at lower risk reporting lower intentions and those at higher risk reporting higher intentions to see a doctor in the next 30 days. Neither avatars nor animated randomness affected recall.

Conclusions: Using avatars and animated randomness can help convey difficult concepts in personal health risk. These types of design features are straightforward to implement in an online environment, require minimal viewing time, and suggest potential to improve the effectiveness of health risk communication methods.