Suppr超能文献

预测老年驾驶员的责任交通事故。

Predicting at-fault car accidents of older drivers.

作者信息

De Raedt R, Ponjaert-Kristoffersen I

机构信息

Department of Developmental and Lifespan Psychology, Free University of Brussels, Belgium.

出版信息

Accid Anal Prev. 2001 Nov;33(6):809-19. doi: 10.1016/s0001-4575(00)00095-6.

Abstract

Considerable research shows car accidents are difficult to predict using screening tests. The objective of this exploratory study is to determine whether detailed accident analysis taking into account the specific accident type might enhance the predictive power of a standardised road test and a set of selected neuropsychological tests. Moreover, this study addresses the validity and reliability of performance-based driving evaluation. The sample consisted of 84 older drivers between 65 and 96 years of age who were referred for a fitness-to-drive evaluation. Using discriminant analyses, the subjects were classified as drivers with and without at-fault accidents. We compared the accuracy of neuropsychological tests and a road test for postdicting all accidents, accidents classified into two categories and accidents classified into four different categories. The percentages of correctly classified subject were highest at the level of the most detailed classification. These results suggest that, although accident prediction is difficult, the predictability of car accidents by neurocognitive measurements and a road test increases when the kind of accident is specified.

摘要

大量研究表明,使用筛查测试很难预测车祸。这项探索性研究的目的是确定,考虑到具体事故类型的详细事故分析是否可能增强标准化路考和一组选定的神经心理学测试的预测能力。此外,本研究探讨了基于表现的驾驶评估的有效性和可靠性。样本包括84名年龄在65岁至96岁之间的老年驾驶员,他们被转介进行驾驶适宜性评估。使用判别分析,将受试者分为有过错事故的驾驶员和无过错事故的驾驶员。我们比较了神经心理学测试和路考对所有事故、分为两类的事故以及分为四类不同事故的事后预测准确性。在最详细分类水平上,正确分类受试者的百分比最高。这些结果表明,虽然事故预测很难,但当明确事故类型时,通过神经认知测量和路考对车祸的可预测性会增加。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验