title: Effects of game-like interactive graphics on risk perceptions and decisions.
abstract: Many patients have difficulty interpreting risks described in statistical terms as percentages. Computer game technology offers the opportunity to experience how often an event occurs, rather than simply read about its frequency.
  
  
  
  . To assess effects of interactive graphics on risk perceptions and decisions.
  
  
  
  . Electronic questionnaire. Participants and setting. Respondents (n = 165) recruited online or at an urban hospital. Intervention. Health risks were illustrated by either static graphics or interactive game-like graphics. The interactive search graphic was a grid of squares, which, when clicked, revealed stick figures underneath. Respondents had to click until they found a figure affected by the disease. Measurements. Risk feelings, risk estimates, intention to take preventive action.
  
  
  
  . Different graphics did not affect mean risk estimates, risk feelings, or intention. Low-numeracy participants reported significantly higher risk feelings than high-numeracy ones except with the interactive search graphic. Unexpectedly, respondents reported stronger intentions to take preventive action when the intention question followed questions about efficacy and disease severity than when it followed perceived risk questions (65% v. 34%; P < 0.001). When respondents reported risk feelings immediately after using the search graphic, the interaction affected perceived risk (the longer the search to find affected stick figures, the higher the risk feeling: ρ = 0.57; P = 0.009). Limitations. The authors used hypothetical decisions.
  
  
  
  . A game-like graphic that allowed consumers to search for stick figures affected by disease had no main effect on risk perception but reduced differences based on numeracy. In one condition, the game-like graphic increased concern about rare risks. Intentions for preventive action were stronger with a question order that focused first on efficacy and disease severity than with one that focused first on perceived risk.
authors.affiliation: Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York (JSA, RK)
authors.forename: Jessica S
authors.initials: JS
authors.lastname: Ancker
authors.affiliation: Department of Psychology, Columbia University, New York (EUW)|Department of Management, Columbia University Business School, New York (EUW)
authors.forename: Elke U
authors.initials: EU
authors.lastname: Weber
authors.affiliation: Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York (JSA, RK)|Department of Sociomedical Sciences, Columbia University, Mailman School of Public Health, New York (RK)
authors.forename: Rita
authors.initials: R
authors.lastname: Kukafka
mesh_terms: D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D003142:Communication; D003196:Computer Graphics / Q000295:instrumentation*; D003657:Decision Making; D003661:Decision Support Techniques; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008297:Male; D008875:Middle Aged; D010353:Patient Education as Topic / Q000379:methods; D010865:Pilot Projects; D036301:Qualitative Research; D018570:Risk Assessment; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014584:User-Computer Interface; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult
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