title: Presenting Numeric Information with Percentages and Descriptive Risk Labels: A Randomized Trial.
abstract: Previous research demonstrated that providing (v. not providing) numeric information about the adverse effects (AEs) of medications increased comprehension and willingness to use medication but left open the question about which numeric format is best. The objective was to determine which of 4 tested formats (percentage, frequency, percentage + risk label, frequency + risk label) maximizes comprehension and willingness to use medication across age and numeracy levels.
  
  
  
  In a cross-sectional internet survey (N = 368; American Life Panel, 15 May 2008 to 18 June 2008), respondents were presented with a hypothetical prescription medication for high cholesterol. AE likelihoods were described using 1 of 4 tested formats. Main outcome measures were risk comprehension (ability to identify AE likelihood from a table) and willingness to use the medication (7-point scale; not likely = 0, very likely = 6).
  
  
  
  The percentage + risk label format resulted in the highest comprehension and willingness to use the medication compared with the other 3 formats (mean comprehension in percentage + risk label format = 95% v. mean across the other 3 formats = 81%; mean willingness = 3.3 v. 2.95, respectively). Comprehension differences between percentage and frequency formats were smaller among the less numerate. Willingness to use medication depended less on age and numeracy when labels were used. Generalizability is limited by the use of a sample that was older, more educated, and better off financially than national averages.
  
  
  
  Providing numeric AE-likelihood information in a percentage format with risk labels is likely to increase risk comprehension and willingness to use a medication compared with other numeric formats.
authors.affiliation: Ohio State University, Columbus, OH (AS, EP, MT)
authors.forename: Aleksandr
authors.initials: A
authors.lastname: Sinayev
authors.affiliation: Ohio State University, Columbus, OH (AS, EP, MT)
authors.forename: Ellen
authors.initials: E
authors.lastname: Peters
authors.affiliation: Ohio State University, Columbus, OH (AS, EP, MT)
authors.forename: Martin
authors.initials: M
authors.lastname: Tusler
authors.affiliation: Yale School of Medicine, New Haven, CT (LF).
authors.forename: Liana
authors.initials: L
authors.lastname: Fraenkel
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D003142:Communication; D032882:Comprehension; D003657:Decision Making; D004348:Drug Labeling; D064420:Drug-Related Side Effects and Adverse Reactions; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D006937:Hypercholesterolemia; D020407:Internet; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D063046:Patient Medication Knowledge; D055553:Prescription Drugs; D018570:Risk Assessment; D055815:Young Adult
chemical_list: D055553:Prescription Drugs
keywords: adherence; aging; informed decision making; numeracy; pharmaceutical decision making; risk communication; risk comprehension; statins