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驾驶行为量表中的社会期望效应。

Social desirability effects in driver behavior inventories.

机构信息

Department of Psychology, Uppsala University, P. O. Box 1225, 751 42 Uppsala, Sweden.

出版信息

J Safety Res. 2010 Apr;41(2):99-106. doi: 10.1016/j.jsr.2010.02.005. Epub 2010 Mar 30.

Abstract

PROBLEM

The use of lie scales to control for common method variance in driver behavior inventories has been very limited. Given that such questionnaires often use self-reported safety variables as criteria, and have social implications, the risk of artefactual associations is high.

METHOD

A questionnaire containing scales from several well known driver inventories that have been claimed to predict traffic accident involvement was distributed three times to a group of young drivers in a driver education program, as well as a random group twice. The Driver Impression Management scale (DIM) was used to control for socially desirable responding.

RESULTS

For all behavior scales, the correlation with the DIM scale was substantial. If a scale correlated with self-reported crashes, the amount of predictive power was more than halved when social desirability was controlled for. Results were similar for both samples and all waves. The predictive power of the behavior scales was not increased when values were averaged over questionnaire waves, as should have been the case if the measurement and predictive power were valid. Results were similar for self-reported penalty points. The present results indicate that even the most well-known and accepted psychometric scales used in driver research are susceptible to social desirability bias.

DISCUSSION

As social desirability is only one of a number of common method variance mechanisms that can create artefactual associations, and the great popularity of the self-report methodology, the problem for traffic research is grave.

IMPACT ON INDUSTRY

Organizations that fund traffic safety research need to re-evaluate their policies regarding what methods are acceptable. The use of self-reported independent and dependent variables can lead to directly misleading results, with negative effects on traffic safety.

摘要

问题

在驾驶员行为问卷中,使用谎言量表来控制常见的方法偏差的情况非常有限。鉴于此类问卷通常使用自我报告的安全变量作为标准,并且具有社会意义,因此人为关联的风险很高。

方法

一份包含几个知名驾驶员问卷量表的问卷,这些问卷被声称可以预测交通事故的发生,分三次分发给驾驶员教育计划中的一组年轻驾驶员,以及随机组两次。驾驶员印象管理量表(DIM)用于控制社会期望反应。

结果

对于所有行为量表,与 DIM 量表的相关性都很高。如果一个量表与自我报告的事故相关,那么当控制社会期望时,预测能力的数量减少了一半以上。两个样本和所有波次的结果都相似。当值在问卷波次上平均时,行为量表的预测能力并没有增加,因为如果测量和预测能力是有效的,那么情况应该如此。自我报告的罚款点数的结果也相似。目前的结果表明,即使是驾驶员研究中使用的最知名和最可靠的心理计量学量表也容易受到社会期望偏差的影响。

讨论

由于社会期望只是导致人为关联的众多常见方法偏差机制之一,并且自我报告方法学非常流行,因此,交通研究的问题非常严重。

对行业的影响

资助交通安全研究的组织需要重新评估他们对可接受方法的政策。使用自我报告的独立和依赖变量可能会导致直接误导性的结果,对交通安全产生负面影响。

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