title: Numbers can be worth a thousand pictures: individual differences in understanding graphical and numerical representations of health-related information.
abstract: OBJECTIVE
  Informed medical decision making requires comprehending statistical information. We aimed to improve the understanding of conveying health-related statistical information with graphical representations compared with numerical representations. First, we investigated whether the iconicity of representations (i.e., their abstractness vs. concreteness) affected comprehension and recall of statistical information. Second, we investigated whether graph literacy helps to identify individuals who comprehend graphical representations better than numerical representations.
  
  
  METHODS
  Participants (N = 275) were randomly assigned to receive different representations of health-related statistical information, ranging from very low iconicity (numbers) to very high iconicity (icon arrays including photographs). Comprehension and recall of the information were assessed. Additionally, participants rated the accessibility of the information and the attractiveness of the representation. Graph literacy was assessed by means of a recently developed scale.
  
  
  RESULTS
  The only difference between representations that affected comprehension and recall was the difference between graphics and numbers; the actual level of iconicity of graphics did not matter. Individuals with high graph literacy had better comprehension and recall when presented with graphics instead of numbers, and they rated graphical information as more accessible than numerical information, whereas the reverse was true for individuals with low graph literacy, F(4, 185) = 2.60, p = .04, η(p)(²) = .05, and F(4, 245) = 2.71, p = .03, η(p)(2) = .04, respectively. Both groups judged graphical representations as more attractive than numerical representations.
  
  
  CONCLUSIONS
  An assessment of graph literacy distinguished individuals who are best informed with graphical representations of statistical information from those who are better informed with numerical representations.
authors.affiliation: Harding Center for Risk Literacy, Max Planck Institute for Human Development, Berlin, Germany. gaissmaier@mpib-berlin.mpg.de
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Gaissmaier
authors.forename: Odette
authors.initials: O
authors.lastname: Wegwarth
authors.forename: David
authors.initials: D
authors.lastname: Skopec
authors.forename: Ann-Sophie
authors.initials: AS
authors.lastname: Müller
authors.forename: Sebastian
authors.initials: S
authors.lastname: Broschinski
authors.forename: Mary C
authors.initials: MC
authors.lastname: Politi
mesh_terms: D000328:Adult; D032882:Comprehension; D003657:Decision Making; D005260:Female; D006262:Health / Q000706:statistics & numerical data*; D015438:Health Behavior; D057220:Health Literacy; D006801:Humans; D007206:Individuality; D008297:Male; D008433:Mathematics; D011939:Mental Recall; D013223:Statistics as Topic