The Impact of Model Statements on Verbal Differences between Truth and Lies when using a Comparable Truthful Baseline

Baselining is a deception detection technique that compares a statement of interest to a baseline. This study focused on verbal baselining: it looks at differences in detailedness between the baseline and the statement of interest as a cue to deception. Specifically, in two experiments, we investigated whether truth/lie discrimination improved when combining verbal baselining with a model statement—an example of a truthful account unrelated to the event. Participants watched two crime scenarios and provided a statement for each; the first statement, always truthful, served as a truthful baseline. Depending on the condition, participants either lied or told the truth about the second scenario, generating the statement of interest. Half of the participants were also presented with a model statement before providing their statements. Experiment 1 involved written statements, while Experiment 2 involved spoken statements. Whereas Experiment 1 supported the effectiveness of using a model statement and a truthful baseline independently, neither experiment showed that combining the two further improved truth/lie discrimination. These findings highlight the challenges of lie detection and suggest the need for more research to refine truth/lie discrimination.