Motor Vehicle Crash Involvement and Moving Violations: Convergence of Self-Report and Archival Data

Author:

Arthur Winfred1,Tubre Travis1,Day Eric Anthony2,Sheehan M. Kathleen1,Sanchez-Ku Maria L.1,Paul Don1,Paulus Leigh1,Archuleta Kathryn1

Affiliation:

1. Texas A&M University, College Station, Texas

2. The Ohio State University, Columbus, Ohio

Abstract

In the crash involvement literature, it is generally assumed that archival and other "objective" criterion data are superior to self-reports of crash involvement. Using 394 participants (mean age = 36.23 years), the present study assessed the convergence of archival and self-report measures of motor vehicle crash involvement and moving violations. We also sought to determine whether predictor/criterion relationships would vary as a function of criterion type (i.e., archival vs. self-report), and if a combination of both criteria would result in better prediction than would either by itself. The degree of agreement between the two criterion sources was low, with participants self-reporting more crashes and tickets than were found in their state records. Different predictor/criterion relationships were also found for the two criterion types; stronger effects were obtained for self-report data. Combining the two criteria did not result in relationships stronger than those obtained for self-reports alone. Our findings suggest that self-report data are not inherently inferior to archival data and, furthermore, that the two sources of data cannot be used interchangeably. Actual or potential applications include choosing the appropriate criterion to use, which, as the finding of this study reveals, may depend on the purpose of the investigation.

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

Cited by 41 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3