Abstract：
OBJECTIVE: We sought to analyze interactive visualizations and animations of health probability data (such as chances of disease or side effects) that have been studied in head-to-head comparisons with either static graphics or numerical communications.
METHODS: Secondary analysis of a large systematic review on ways to communicate numbers in health.
RESULTS: We group the research to show that 4 types of animated or interactive visualizations have been studied by multiple researchers: those that simulate experience of probabilistic events; those that demonstrate the randomness of those events; those that reduce information overload by directing attention sequentially to different items of information; and those that promote elaborative thinking. Overall, these 4 types of visualizations do not show strong evidence of improving comprehension, risk perception, or health behaviors over static graphics.
CONCLUSIONS: Evidence is not yet strong that interactivity or animation is more effective than static graphics for communicating probabilities in health. We discuss 2 possibilities: that the most effective visualizations haven\'t been studied, and that the visualizations aren\'t effective.
CONCLUSIONS: Future studies should rigorously compare participant performance with novel interactive or animated visualizations against their performance with static visualizations. Such evidence would help determine whether health communicators should emphasize novel interactive visualizations or rely on older forms of visual communication, which may be accessible to broader audiences, including those with limited digital access.
METHODS: Secondary analysis of a large systematic review on ways to communicate numbers in health.
RESULTS: We group the research to show that 4 types of animated or interactive visualizations have been studied by multiple researchers: those that simulate experience of probabilistic events; those that demonstrate the randomness of those events; those that reduce information overload by directing attention sequentially to different items of information; and those that promote elaborative thinking. Overall, these 4 types of visualizations do not show strong evidence of improving comprehension, risk perception, or health behaviors over static graphics.
CONCLUSIONS: Evidence is not yet strong that interactivity or animation is more effective than static graphics for communicating probabilities in health. We discuss 2 possibilities: that the most effective visualizations haven\'t been studied, and that the visualizations aren\'t effective.
CONCLUSIONS: Future studies should rigorously compare participant performance with novel interactive or animated visualizations against their performance with static visualizations. Such evidence would help determine whether health communicators should emphasize novel interactive visualizations or rely on older forms of visual communication, which may be accessible to broader audiences, including those with limited digital access.
摘要：
目的：我们试图分析健康概率数据（如疾病或副作用的机会）的交互式可视化和动画，这些数据在静态图形或数字通信的头对头比较中进行了研究。
方法：关于健康中的数字交流方法的大型系统综述的二次分析。
结果：我们对研究进行了分组，以表明多种研究人员已经研究了4种类型的动画或交互式可视化：模拟概率事件的经验的；那些证明这些事件的随机性的；那些通过将注意力依次引导到不同的信息项来减少信息过载的；以及那些促进精细思维的。总的来说,这4种可视化并没有显示出提高理解力的有力证据，风险感知，或静态图形上的健康行为。
结论：目前还没有强有力的证据表明，交互性或动画在传达健康概率方面比静态图形更有效。我们讨论了两种可能性：最有效的可视化尚未被研究，并且可视化效果无效。
结论：未来的研究应严格比较参与者的表现与新颖的交互式或动画可视化与静态可视化的表现。这些证据将有助于确定健康传播者是否应该强调新颖的交互式可视化或依赖较旧的视觉交流形式，更广泛的受众可以接触到，包括那些有限的数字访问。
方法：关于健康中的数字交流方法的大型系统综述的二次分析。
结果：我们对研究进行了分组，以表明多种研究人员已经研究了4种类型的动画或交互式可视化：模拟概率事件的经验的；那些证明这些事件的随机性的；那些通过将注意力依次引导到不同的信息项来减少信息过载的；以及那些促进精细思维的。总的来说,这4种可视化并没有显示出提高理解力的有力证据，风险感知，或静态图形上的健康行为。
结论：目前还没有强有力的证据表明，交互性或动画在传达健康概率方面比静态图形更有效。我们讨论了两种可能性：最有效的可视化尚未被研究，并且可视化效果无效。
结论：未来的研究应严格比较参与者的表现与新颖的交互式或动画可视化与静态可视化的表现。这些证据将有助于确定健康传播者是否应该强调新颖的交互式可视化或依赖较旧的视觉交流形式，更广泛的受众可以接触到，包括那些有限的数字访问。
