OBJECTIVE: To test optimal graphic risk communication formats for presenting small probabilities using graphics with a denominator of 1000 to adults with lower education and literacy. METHODS: A randomized experimental study, which took place in adult basic education classes in Sydney, Australia. The participants were 120 adults with lower education and literacy. An experimental computer-based manipulation compared 1) pictographs in 2 forms, shaded "blocks" and unshaded "dots"; and 2) bar charts across different orientations (horizontal/vertical) and numerator size (small <100, medium 100-499, large 500-999). Accuracy (size of error) and ease of processing (reaction time) were assessed on a gist task (estimating the larger chance of survival) and a verbatim task (estimating the size of difference). Preferences for different graph types were also assessed. RESULTS: Accuracy on the gist task was very high across all conditions (>95%) and not tested further. For the verbatim task, optimal graph type depended on the numerator size. For small numerators, pictographs resulted in fewer errors than bar charts (blocks: odds ratio [OR] = 0.047, 95% confidence interval [CI] = 0.023-0.098; dots: OR = 0.049, 95% CI = 0.024-0.099). For medium and large numerators, bar charts were more accurate (e.g., medium dots: OR = 4.29, 95% CI = 2.9-6.35). Pictographs were generally processed faster for small numerators (e.g., blocks: 14.9 seconds v. bars: 16.2 seconds) and bar charts for medium or large numerators (e.g., large blocks: 41.6 seconds v. 26.7 seconds). Vertical formats were processed slightly faster than horizontal graphs with no difference in accuracy. Most participants preferred bar charts (64%); however, there was no relationship with performance. CONCLUSIONS: For adults with low education and literacy, pictographs are likely to be the best format to use when displaying small numerators (<100/1000) and bar charts for larger numerators (>100/1000).
RCT Entities:
OBJECTIVE: To test optimal graphic risk communication formats for presenting small probabilities using graphics with a denominator of 1000 to adults with lower education and literacy. METHODS: A randomized experimental study, which took place in adult basic education classes in Sydney, Australia. The participants were 120 adults with lower education and literacy. An experimental computer-based manipulation compared 1) pictographs in 2 forms, shaded "blocks" and unshaded "dots"; and 2) bar charts across different orientations (horizontal/vertical) and numerator size (small <100, medium 100-499, large 500-999). Accuracy (size of error) and ease of processing (reaction time) were assessed on a gist task (estimating the larger chance of survival) and a verbatim task (estimating the size of difference). Preferences for different graph types were also assessed. RESULTS: Accuracy on the gist task was very high across all conditions (>95%) and not tested further. For the verbatim task, optimal graph type depended on the numerator size. For small numerators, pictographs resulted in fewer errors than bar charts (blocks: odds ratio [OR] = 0.047, 95% confidence interval [CI] = 0.023-0.098; dots: OR = 0.049, 95% CI = 0.024-0.099). For medium and large numerators, bar charts were more accurate (e.g., medium dots: OR = 4.29, 95% CI = 2.9-6.35). Pictographs were generally processed faster for small numerators (e.g., blocks: 14.9 seconds v. bars: 16.2 seconds) and bar charts for medium or large numerators (e.g., large blocks: 41.6 seconds v. 26.7 seconds). Vertical formats were processed slightly faster than horizontal graphs with no difference in accuracy. Most participants preferred bar charts (64%); however, there was no relationship with performance. CONCLUSIONS: For adults with low education and literacy, pictographs are likely to be the best format to use when displaying small numerators (<100/1000) and bar charts for larger numerators (>100/1000).
Authors: Helen W Sullivan; Amie C O'Donoghue; Kathryn J Aikin; Dhuly Chowdhury; Rebecca R Moultrie; Douglas J Rupert Journal: Patient Educ Couns Date: 2015-12-22
Authors: Adriana Arcia; Michael E Bales; William Brown; Manuel C Co; Melinda Gilmore; Young Ji Lee; Chin S Park; Jennifer Prey; Mark Velez; Janet Woollen; Sunmoo Yoon; Rita Kukafka; Jacqueline A Merrill; Suzanne Bakken Journal: AMIA Annu Symp Proc Date: 2013-11-16
Authors: Edward R Melnick; Marc A Probst; Elizabeth Schoenfeld; Sean P Collins; Maggie Breslin; Cheryl Walsh; Nathan Kuppermann; Pat Dunn; Benjamin S Abella; Dowin Boatright; Erik P Hess Journal: Acad Emerg Med Date: 2016-12 Impact factor: 3.451