The impact of model statements on verbal differences between truth and lies when using a comparable truthful baseline

Abstract Purpose Baselining is a deception detection technique that compares a statement of interest to a baseline. This study focused on verbal baselining: it examined differences in detailedness between the baseline and the statement of interest as a cue to deception. Method Across two experiments, participants watched two crime videos and provided two statements: one truthful baseline and one statement of interest, which was either truthful or deceptive depending on the condition. To manipulate expectations for detail, half of the participants were shown a model statement (i.e., an example of a richly detailed statement) before giving their responses. Results In Experiment 1 (using written statements), both the model statement and the baseline independently improved truth/lie discrimination. In Experiment 2 (using spoken statements), however, these effects were not replicated. Importantly, combining a model statement with baselining did not further improve truth/lie discrimination in either experiment. Conclusion These findings underscore the complexity of verbal lie detection and highlight the need to better understand when and how baselining techniques are most effective.