Effect of arrangement of stick figures on estimates of proportion in risk graphics

Jessica S. Ancker, Elke U. Weber, Rita Kukafka

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Background. Health risks are sometimes illustrated with stick figures, with a certain proportion colored to indicate they are affected by the disease. Perception of these graphics may be affected by whether the affected stick figures are scattered randomly throughout the group or arranged in a block. Objective. To assess the effects of stick-figure arrangement on first impressions of estimates of proportion, under a 10-s deadline. Design. Questionnaire. Participants and Setting. Respondents recruited online (n = 100) or in waiting rooms at an urban hospital (n = 65). Intervention. Participants were asked to estimate the proportion represented in 6 unlabeled graphics, half randomly arranged and half sequentially arranged. Measurements. Estimated proportions. Results. Although average estimates were fairly good, the variability of estimates was high. Overestimates of random graphics were larger than overestimates of sequential ones, except when the proportion was near 50%; variability was also higher with random graphics. Although the average inaccuracy was modest, it was large enough that more than one quarter of respondents confused 2 graphics depicting proportions that differed by 11 percentage points. Low numeracy and educational level were associated with inaccuracy. Limitations. Participants estimated proportions but did not report perceived risk. Conclusions. Randomly arranged arrays of stick figures should be used with care because viewers' ability to estimate the proportion in these graphics is so poor that moderate differences between risks may not be visible. In addition, random arrangements may create an initial impression that proportions, especially large ones, are larger than they are.

Original languageEnglish (US)
Pages (from-to)143-150
Number of pages8
JournalMedical Decision Making
Volume31
Issue number1
DOIs
StatePublished - Jan 2011

All Science Journal Classification (ASJC) codes

  • Health Policy

Keywords

  • Cost utility analysis
  • Population-based studies
  • Randomized trial methodology
  • Risk stratification
  • Scale development/validation

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