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跨随机样本和互联网样本的 DAS 的多群组不变性。

Multigroup invariance of the DAS across a random and an internet-sourced sample.

机构信息

Department of Social Sciences, University of Nicosia, Cyprus.

Monash University Accident Research Centre, Monash University, Clayton, Australia.

出版信息

Accid Anal Prev. 2019 Oct;131:137-145. doi: 10.1016/j.aap.2019.06.013. Epub 2019 Jun 27.

DOI:10.1016/j.aap.2019.06.013
PMID:31255799
Abstract

It is well established that angry and, subsequently, aggressive drivers pose a problem for road safety. Over recent years, there has been an increase in the number of published studies examining driver anger, particularly using the Driving Anger Scale (DAS). The DAS measures six broad types of situations likely to provoke anger while driving (i.e., police presence, illegal driving, discourtesy, traffic obstructions, slower drivers, and hostile gestures). The majority of the recent studies have moved away from traditional paper-and-pencil methodologies, using the internet to collect data, for reasons of convenience. However, it is not yet completely clear whether data obtained from this methodology differs from more traditional methods. While research outside of the driving arena has not found substantial differences, it is important to establish whether this also applies to driving-related research and measures, such as the DAS. The present study used Multigroup Confirmatory Factor Analysis (MGCFA) to investigate the invariance of the DAS across a random sample from the electoral roll (n = 1,081: males = 45%) and an internet sourced sample (n = 627; males = 55%). The MGCFA showed the same six-factor solution was supported in both datasets. The relationships between the DAS factors and age, sex, trait anger, and annual mileage were broadly similar, although more significant differences were identified in the internet sample. This research demonstrates that driving measures administered over the internet produce similar results to those obtained using more traditional methods.

摘要

众所周知,愤怒的司机,随后是攻击性的司机,对道路安全构成了问题。近年来,研究司机愤怒情绪的出版物数量有所增加,特别是使用驾驶愤怒量表(DAS)。DAS 测量了六种可能在驾驶时引起愤怒的广泛情况(即警察在场、非法驾驶、不礼貌、交通堵塞、速度较慢的司机和敌对手势)。最近的大多数研究都采用了互联网收集数据的方法,而不是传统的纸笔方法,因为这样更方便。然而,目前尚不清楚这种方法获得的数据是否与更传统的方法有所不同。虽然驾驶领域以外的研究没有发现实质性差异,但重要的是要确定这是否也适用于与驾驶相关的研究和措施,例如 DAS。本研究使用多群组验证性因素分析(MGCFA)来调查 DAS 在随机抽样选民名单(n=1081:男性=45%)和互联网来源样本(n=627;男性=55%)中的不变性。MGCFA 表明,两个数据集都支持相同的六因素解决方案。DAS 因素与年龄、性别、特质愤怒和年里程数之间的关系大致相似,尽管在互联网样本中发现了更多的显著差异。这项研究表明,通过互联网管理的驾驶措施与使用更传统方法获得的结果相似。

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