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首页> 外文期刊>Risk analysis >The Influence of Uncertain Map Features on Risk Beliefs and Perceived Ambiguity for Maps of Modeled Cancer Risk from Air Pollution
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The Influence of Uncertain Map Features on Risk Beliefs and Perceived Ambiguity for Maps of Modeled Cancer Risk from Air Pollution

机译：不确定的地图特征对空气污染建模癌症风险图的风险信念和感知歧义的影响

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Maps are often used to convey information generated by models, for example, modeled can cer risk from air pollution. The concrete nature of images, such as maps, may convey more certainty than warranted for modeled information. Three map features were selected to com municate the uncertainty of modeled cancer risk: (i) map contours appeared in or out of fo cus, (ii) one or three colors were used, and (iii) a verbal-relative or numeric risk expression was used in the legend. Study aims were to assess how these features influenced risk beliefs and the ambiguity of risk beliefs at four assigned map locations that varied by risk level. We applied an integrated conceptual framework to conduct this full factorial experiment with 32 maps that varied by the three dichotomous features and four risk levels; 826 univer sity students participated. Data was analyzed using structural equation modeling. Unfocused contours and the verbal-relative risk expression generated more ambiguity than their coun terparts. Focused contours generated stronger risk beliefs for higher risk levels and weaker beliefs for lower risk levels. Number of colors had minimal influence. The magnitude of risk level, conveyed using incrementally darker shading, had a substantial dose-response influence on the strength of risk beliefs. Personal characteristics of prior beliefs and numeracy also had substantial influences. Bottom-up and top-down information processing suggest why iconic visual features of incremental shading and contour focus had the strongest visual influences on risk beliefs and ambiguity. Variations in contour focus and risk expression show promise for fostering appropriate levels of ambiguity.
机译：地图通常用于传达模型生成的信息，例如，建模可能会增加空气污染的风险。图像（例如地图）的具体性质可能传达出比建模信息所保证的更为确定的信息。选择了三种地图特征来沟通模型化的癌症风险的不确定性：（i）地图轮廓出现在焦点内或焦点外；（ii）使用一种或三种颜色；以及（iii）相对语言或数字风险表达在传说中使用。研究目的是评估这些特征如何影响四个因风险级别而异的指定地图位置的风险信念和风险信念的歧义性。我们应用了一个集成的概念框架，以32个地图进行了完整的阶乘实验，这些地图因三个二分特征和四个风险级别而有所不同。 826名大学生参加了比赛。使用结构方程模型分析数据。不集中的轮廓和相对言语的风险表达比他们的竞争对手产生更多的歧义。集中的轮廓对于较高的风险级别生成了更强的风险信念，对于较低的风险级别生成了较弱的信念。颜色数量影响最小。使用逐渐变暗的阴影来表示的风险水平的大小，对风险信念的强度具有重大的剂量反应影响。先验信念和计算能力的个人特征也有重大影响。自下而上和自上而下的信息处理表明了为什么渐增的阴影和轮廓焦点的标志性视觉特征对风险信念和模糊性具有最强的视觉影响。等高线重点和风险表达方式的变化显示出促进适当模糊度水平的希望。

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