Advances and Continuing Challenges in Objective Personality Testing
Advances and Continuing Challenges in Objective Personality Testing
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客观性格测试的进展和持续挑战
DOI：
10.1027/1015-5759/a000213
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发表时间：
2014
影响因子：
2.5
通讯作者：
Schmitt
中科院分区：
文献类型：
--
作者：
Ortner;Schmitt
使用客观的行为指标而不是自我报告的行为和自我评级在人格评估中有很长的历史。客观人格测验（OPTs）的基本思想可以追溯到詹姆斯·麦基恩·卡特尔（James McKeen Cattell）在1890年提出的心理测验。几十年后，OPT程序在第二次世界大战期间被德国和美国军队采用（见Fitts，1946）。直到今天，大多数为客观评估人格而设计的测试都是基于Raymond Bernard Cattell的全面理论和实证工作以及他的著名假设，即完整的人格调查需要异质数据源，包括自我报告数据（Q数据），经常从观察者报告（L数据）获得的人格生活指标，以及客观表现或测试数据（Cattell，1946; Cattell & Kline，1977）.目前，我们有一个非常大的和多样化的被选专业人员的集合在我们的处置。被占领土最近的发展受到数字技术的启发和推动，数字技术变得更加强大，同时也更加负担得起。计算机作为一种工具，极大地促进了项目和任务呈现的创新和巧妙的程序以及行为反应的精确记录（参见Ortner等人，2007年）。与Cattell和他的学生提出的OPT程序相反，在20世纪90年代及以后开发的大多数OPT并不局限于整体人格方法，并且通常是为评估单一结构而设计的（例如，Lejuez，理查兹等人，2002年; Proyer，2007年）。这些OPTs在任务概念、材料和评分方法方面是最多样化的。其中包括伪装成成就任务的性格测试（例如，Kubinger & Ebenhöh，1996年; Schmidt-Atzert，2007年），或多或少复杂的任务嵌入模拟现实生活中的情况下，（Aguado，鲁比奥，& Lucía，2011;鲁比奥、埃尔南德斯、萨尔迪瓦、马尔克斯和桑塔克雷乌，2010年），和要求评估或决策的面试型OPTs，但评估的结构与项目内容可能建议的结构不同（例如，碧玉和奥特纳，2014）。尽管存在这种多样性，但所有的OPTs都有一个共同的原则，即使用绩效任务或其他高度标准化的微型情境中可观察到的行为作为人格指标（Cattell & Warburton，1967）。作为第二个共同特征，OPTs通常缺乏表面有效性（参见Cattell，1958;施密特，1975）。因此，由于频繁使用基于性能的指标以及不透明的评分规则，OPTs比Q数据和L数据更不容易伪造（见Cattell & Kline，1977）。为了支持这一说法，一些研究令人印象深刻地表明，OPT分数比问卷更难伪造（例如，Arendasy，Sommer，Herle，Schützhofer，& Inwanschitz，2011; Elliot，Lawty-Jones，&杰克逊，1996; Hofmann & Kubinger，2001;齐格勒，Schmidt-Atzert，Bühner，& Krumm，2007）。考虑到这一重要优势，心理学文献中关于选择性行为测试的期刊文章和书籍章节仍然很少，这似乎有点令人惊讶，特别是与过去15年中提出的所谓间接测量方法所引起的巨大关注相比（De Houwer，Teige-Mocigemba，Spruyt，& Moors，2009; Fazio & Olson，2003; Greenwald，Poehlman，Uhlmann，& Banaji，2009）。
The use of objective behavioral indicators instead of self-reported behaviors and self-ratings has a long history in personality assessment. The basic idea of objective personality tests (OPTs) can be traced back to James McKeen Cattell’s proposal of mental tests in 1890. A few decades later, OPT procedures were employed by the German and US militaries during World War II (see Fitts, 1946). Until today, most tests designed for the objective assessment of personality have been based on Raymond Bernard Cattell’s comprehensive theoretical and empirical work and his well-known postulate that a complete investigation of personality requires heterogeneous data sources including self-report data (Q-data), life indicators of personality often obtained from observer reports (L-data), and objective performance or test data (Cattell, 1946; Cattell & Kline, 1977).At present, we have a very large and diverse collection of OPTs at our disposal. More recent developments in OPTs have been inspired and facilitated by the availability of digital technologies that have become more powerful and affordable at the same time. The computer as a tool has contributed greatly to innovative and ingenious procedures for item and task presentation and the precise registration of behavioral responses (see Ortner et al., 2007). In contrast to the OPT procedures proposed by Cattell and his students, most of the OPTs that were developed during the 1990s and later are not bound to holistic personality approaches and are typically designed for the assessment of single constructs (eg, Lejuez, Richards, et al., 2002; Proyer, 2007). These OPTs are most diverse with regard to task concepts, materials, and scoring methods. They include personality tests masked as achievement tasks (eg, Kubinger & Ebenhöh, 1996; Schmidt-Atzert, 2007), more or less complex tasks embedded in simulated real-life situations (eg, Aguado, Rubio, & Lucía, 2011; Rubio, Hernández, Zaldivar, Marquez, & Santacreu, 2010), and questionnaire-type OPTs that ask for evaluations or decisions yet assess different constructs than those that might be suggested by the item content (eg, Jasper & Ortner, 2014). Despite this diversity, all OPTs share as a common principle the use of observable behavior on performance tasks or other highly standardized miniature situations (Cattell & Warburton, 1967) as personality indicators. As a second common feature, OPTs typically lack face validity (see Cattell, 1958; Schmidt, 1975). Therefore, and because of the frequent use of performance-based indicators as well as nontransparent scoring rules, OPTs are less susceptible to faking than Q-data and L-data (see Cattell & Kline, 1977). In support of this claim, several studies have impressively shown that OPT scores are more difficult to fake than questionnaires (eg, Arendasy, Sommer, Herle, Schützhofer, & Inwanschitz, 2011; Elliot, Lawty-Jones, & Jackson, 1996; Hofmann & Kubinger, 2001; Ziegler, Schmidt-Atzert, Bühner, & Krumm, 2007). Given this important advantage, it seems somewhat surprising that journal articles and book chapters dealing with OPTs are still scarce in the psychological literature, especially when compared to the enormous amount of attention that has been paid to the so-called indirect measurement approaches that have been proposed during the last 15 years (De Houwer, Teige-Mocigemba, Spruyt, & Moors, 2009; Fazio & Olson, 2003; Greenwald, Poehlman, Uhlmann, & Banaji, 2009).