Detecting deceit within a predominantly true statement using two parallel assessment methods: A pilot study

Abstract In human intelligence, a verbal statement from a source is seldom 100% true or false, and not very often is the source a total liar or a truth teller. From this standing point, a simple dichotomy of a liar or a truth teller might not offer an adequate diagnostic value for the purposes of human intelligence. A more diagnostic approach would be to assess which parts of the predominantly truthful verbal statement are likely to be true and which parts are assessed to be doubtful. In addition, the use of two parallel methods to detect deceit should improve the diagnostic value of the results. A pilot study in laboratory conditions ( n = 8, yielding 190 assessment points) utilising an applied mock crime scenario was conducted. Correlation calculations showed that a dual-method approach slightly improved the within-statement truth accuracy, and it was achieved mainly by decreasing the number of false positives. As the truth accuracy was increased, the lie accuracy within the test group slightly decreased. The results confirmed that by applying parallel orienting response (EDA) and cognitive load (speech-related indices)-based assessment methods, it is possible to detect embedded lies successfully in an information-gathering interview setup.