Learning to detect deception from evasive answers and inconsistencies across repeated interviews: a study with lay respondents and police officers

Abstract

[EN]Previous research has shown that inconsistencies across repeated interviews do not indicate deception because liars deliberately tend to repeat the same story. However, when a strategic interview approach that makes it difficult for liars to use the repeat strategy is used, both consistency and evasive answers differ significantly between truth tellers and liars, and statistical software (binary logistic regression analyses) can reach high classification rates (Masip et al., 2016b). Yet, if the interview procedure is to be used in applied settings the decision process will be made by humans, not statistical software. To address this issue, in the current study, 475 college students (Experiment 1) and 142 police officers (Experiment 2) were instructed to code and use consistency, evasive answers, or a combination or both before judging the veracity of Masip et al.’s (2016b) interview transcripts. Accuracy rates were high (60% to over 90%). Evasive answers yielded higher rates than consistency, and the combination of both these cues produced the highest accuracy rates in identifying both truthful and deceptive statements. Uninstructed participants performed fairly well (around 75% accuracy), apparently because they spontaneously used consistency and evasive answers. The pattern of resultswas the same among students, all officers, and veteran officers only, and shows that inconsistencies between interviews and evasive answers reveal deception when a strategic interview approach that hinders the repeat strategy is used.