Toward a New Method of Detecting Deliberately Faked Personality Tests: The Use of Idiosyncratic Item Responses

N. Kuncel, Matthew J. Borneman
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引用次数: 80

Abstract

This study presents a new method for developing faking detection scales based on idiosyncratic item-response patterns. Two scoring schemes based on this approach strongly differentiated between scores obtained under honest vs directed faking conditions in cross-validation samples (r=(pb).45 and .67). This approach is shown to successfully classify between 20% and 37% of faked personality measures with only a 1% false positive rate in a sample comprised of 56% honest responses. Of equal importance, this method does not result in a scale that meaningfully correlates with personality or cognitive ability tests. This study raises many questions about both the source and generalizabiltiy of the effect. Key directions for future research and improved scale development that may limit or enhance the utility of the idiosyncratic item-response method are discussed.
一种检测故意伪造人格测试的新方法:特质项目反应的使用
本研究提出了一种基于特质项目反应模式的虚假检测量表的新方法。在交叉验证样本中,基于这种方法的两种评分方案在诚实和直接伪造条件下获得的分数之间存在显著差异(r=(pb))。45和0.67)。这种方法被证明可以成功地对20%到37%的虚假人格测试进行分类,而在由56%的诚实回答组成的样本中,只有1%的假阳性率。同样重要的是,这种方法不能得出与人格或认知能力测试有意义相关的量表。这项研究提出了许多关于影响的来源和普遍性的问题。讨论了未来研究和改进量表开发的关键方向,这些方向可能限制或增强特质项目反应方法的效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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