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Validity of Content-Based Techniques to Distinguish True and Fabricated Statements: A Meta-Analysis

机译:基于内容的区分真实陈述和捏造陈述的技术的有效性:荟萃分析

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Within the scope of judicial decisions, approaches to distinguish between true and fabricated statements have been of particular importance since ancient times. Although methods focusing on "prototypical" deceptive behavior (e.g., psychophysiological phenomena, nonverbal cues) have largely been rejected with regard to validity, content-based techniques constitute a promising approach and are well established within the applied forensic context. The basic idea of this approach is that experience-based and nonexperience-based statements differ in their content-related quality. In order to test the validity of the most prominent content-based techniques, criteria-based content analysis (CBCA) and reality monitoring (RM), we conducted a comprehensive meta-analysis on English-and German-language studies. Based on a variety of decision criteria, 56 studies were included revealing an overall effect size of g = 1.03 (95% confidence interval [ 0.78, 1.27], Q = 420.06, p <.001, I-2 = 92.48%, N = 3,429). There was no significant difference in the effectiveness of CBCA and RM. Additionally, we investigated a number of moderator variables, such as characteristics of participants, statements, and judgment procedures, as well as general study characteristics. Results showed that the application of all CBCA criteria outperformed any incomplete CBCA criteria set. Furthermore, statement classification based on discriminant functions revealed higher discrimination rates than decisions based on sum scores. Finally, unpublished studies showed higher effect sizes than studies published in peer-reviewed journals. All results are discussed in terms of their significance for future research (e.g., developing standardized decision rules) and practical application (e.g., user training, applying complete criteria set).
机译:自古以来,在司法裁决的范围内,区分真实陈述和捏造陈述的方法就显得尤为重要。尽管关注有效性的方法已被拒绝,但主要针对“原型”欺骗行为(例如,心理生理现象,非言语提示)的方法,基于内容的技术构成了一种有前途的方法,并且在所应用的法证环境中得到了很好的确立。这种方法的基本思想是基于经验的陈述和基于非经验的陈述在与内容相关的质量上有所不同。为了测试最杰出的基于内容的技术,基于标准的内容分析(CBCA)和现实监控(RM)的有效性,我们对英语和德语语言研究进行了全面的荟萃分析。根据各种决策标准,共进行了56项研究,揭示总体影响大小为g = 1.03(95%置信区间[0.78,1.27],Q = 420.06,p <.001,I-2 = 92.48%,N = 3,429)。 CBCA和RM的疗效无明显差异。此外,我们调查了许多主持人变量,例如参与者的特征,陈述和判断程序以及一般学习特征。结果表明,所有CBCA标准的应用均优于任何不完整的CBCA标准集。此外,基于判别函数的语句分类显示出比基于和得分的决策更高的判别率。最后,未发表的研究显示出比在同行评审期刊上发表的研究更大的效应量。讨论了所有结果对未来研究(例如,开发标准化决策规则)和实际应用(例如,用户培训,应用完整标准集)的重要性。

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