The Influence of Graphic Display Format on the Interpretations of Quantitative Risk Information among Adults with Lower Education and Literacy
Medical Decision Making(2011)
摘要
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).
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要