Vanlaar Ward, Yannis George
Belgian Road Safety Institute, Behaviour and Policy Department, Haachtsesteenweg 1405, 1130 Brussels, Belgium.
Accid Anal Prev. 2006 Jan;38(1):155-61. doi: 10.1016/j.aap.2005.08.007. Epub 2005 Sep 26.
A theoretical two-dimensional model on prevalence and risk was developed. The objective of this study was to validate this model empirically to answer three questions: How do European drivers perceive the importance of several causes of road accidents? Are there important differences in perceptions between member states? Do these perceptions reflect the real significance of road accident causes? Data were collected from 23 countries, based on representative national samples of at least 1000 respondents each (n=24,372). Face-to-face interviews with fully licensed, active car drivers were conducted using a questionnaire containing closed answer questions. Respondents were asked to rate 15 causes of road accidents, each using a six-point ordinal scale. The answers were analyzed by calculating Kendall's tau for each pair of items to form lower triangle similarity matrices per country and for Europe as a whole. These matrices were then used as the input files for an individual difference scaling to draw a perceptual map of the 15 items involved. The hypothesized model on risk and prevalence fits the data well and enabled us to answer the three questions of concern. The subject space of the model showed that there are no relevant differences between the 23 countries. The group space of the model comprises four quadrants, each containing several items (high perceived risk/low perceived prevalence items; high perceived risk/high perceived prevalence items; low perceived risk/high perceived prevalence items and low perceived risk/low perceived prevalence items). Finally, perceptions of the items driving under the influence of alcohol, drugs and medicines and driving using a handheld or hands-free mobile phone are discussed with regard to their real significance in causing road accidents. To conclude, individual difference scaling offers some promising possibilities to study drivers' perception of road accident causes.
建立了一个关于患病率和风险的理论二维模型。本研究的目的是通过实证验证该模型,以回答三个问题:欧洲司机如何看待道路交通事故的几种原因的重要性?成员国之间在认知上是否存在重要差异?这些认知是否反映了道路交通事故原因的实际重要性?基于每个国家至少1000名受访者的代表性全国样本(n = 24372),从23个国家收集了数据。使用包含封闭式回答问题的问卷,对持有全驾照的在职汽车司机进行面对面访谈。要求受访者对15种道路交通事故原因进行评分,每种原因使用六点序数量表。通过计算每对项目的肯德尔tau系数来分析答案,以形成每个国家以及整个欧洲的下三角相似性矩阵。然后将这些矩阵用作个体差异缩放的输入文件,以绘制所涉及的15个项目的感知图。关于风险和患病率的假设模型与数据拟合良好,使我们能够回答所关注的三个问题。模型的主体空间表明,23个国家之间没有相关差异。模型的群体空间包括四个象限,每个象限包含几个项目(高感知风险/低感知患病率项目;高感知风险/高感知患病率项目;低感知风险/高感知患病率项目和低感知风险/低感知患病率项目)。最后,讨论了在酒精、药物和药品影响下驾驶以及使用手持或免提移动电话驾驶这些项目在导致道路交通事故方面的实际重要性。总之,个体差异缩放为研究司机对道路交通事故原因的认知提供了一些有前景的可能性。