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

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 non-experience-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% CI [0.78, 1.27], Q = 420.06, p < .001, I² = 92.48%, N = 3429). 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 Finally, unpublished studies showed higher effect sizes than studies published in peer-reviewed journals.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).