| Literature DB >> 25844516 |
Michael Logue1, Angela S Book1, Paul Frosina1, Tylor Huizinga1, Shelby Amos1.
Abstract
Research has found that deception detection accuracy in the context of suspect interrogation hovers around chance levels. Geiselman (2012) adapted the cognitive interview (typically used for witnesses) for use with suspects (CIS) and found that judgments of deception were more accurate than previous interrogation techniques. The current study attempted to use the CIS to improve deception detection with Reality Monitoring (RM: Vrij et al., 2008), which has already been validated in the context of witness statements. One hundred sixty-six undergraduate students were randomly assigned to 2 conditions. In the Truthful condition, participants played a game with a confederate, whereas in the Deceptive condition, participants rehearsed (but did not experience) a synopsis of the game scenario. Participants in the Deceptive condition were also instructed to steal $10 from a confederate's wallet. In both conditions, $10 was purported to be missing and a researcher blind to condition conducted a CIS. Statement veracity was coded using 6 of the RM criteria advanced by Vrij et al. (frequency of visual, auditory, spatial, temporal, cognitive, and affective details). According to results from a MANOVA, truthful and deceptive statements differed significantly on all RM criteria, with the exception of affective details, validating the importance for evaluation of statement veracity (p ≤ .01). Further, a binary logistic regression found that combining the RM criteria together correctly classified 86.6% of statements, χ(²)(6) = 114.4, p < .001, with excellent sensitivity and specificity (.899 and .833, respectively). As well, Visual, Auditory, and Cognitive details uniquely predicted condition. Findings support using RM criteria to detect deception in interviews conducted with the CIS. (c) 2015 APA, all rights reserved).Entities:
Mesh:
Year: 2015 PMID: 25844516 DOI: 10.1037/lhb0000127
Source DB: PubMed Journal: Law Hum Behav ISSN: 0147-7307