title: Communicating information concerning potential medication harms and benefits: What gist do numbers convey?
abstract: Fuzzy trace theory was used to examine the effect of information concerning medication benefits and side-effects on willingness to use a hypothetical medication.
  
  
  
  Participants (N=999) were recruited via Amazon Mechanical Turk. Using 3×5 experimental research design, each participant viewed information about medication side effects in 1 of 3 formats and information about medication benefits in 1 of 5 formats. For both side-effects and benefits, one format presented only non-numeric information and the remaining formats presented numeric information.
  
  
  
  Individuals in the non-numeric side-effect condition were less likely to take the medication than those in the numeric conditions (p<0.0001). In contrast, individuals in the non-numeric benefit condition were more likely to take the medication than those in the numeric conditions (p<0.0001).
  
  
  
  Our findings suggest that non-numeric side-effect information conveys the gist that the medication can cause harm, decreasing willingness to use the medication; whereas non-numeric benefit information has the opposite effect.
  
  
  
  Presenting side-effect and benefit information in non-numeric format appears to bias decision-making in opposite directions. Providing numeric information for both benefits and side-effects may enhance decision-making. However, providing numeric benefit information may decrease adherence, creating ethical dilemmas for providers.
authors.affiliation: Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, United States. Electronic address: s_blalock@unc.edu.
authors.forename: Susan J
authors.initials: SJ
authors.lastname: Blalock
authors.affiliation: Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, United States.
authors.forename: Adam
authors.initials: A
authors.lastname: Sage
authors.affiliation: Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, United States.
authors.forename: Michael
authors.initials: M
authors.lastname: Bitonti
authors.affiliation: Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, United States.
authors.forename: Payal
authors.initials: P
authors.lastname: Patel
authors.affiliation: School of Healthcare, University of Leeds, Leeds, UK.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Dickinson
authors.affiliation: Department of Health Sciences and the Hull York Medical School, University of York, York, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Knapp
mesh_terms: D000328:Adult; D003142:Communication; D032882:Comprehension; D064420:Drug-Related Side Effects and Adverse Reactions; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D057220:Health Literacy; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D063046:Patient Medication Knowledge
keywords: Fuzzy trace theory; Gist; Medications; Risk communication