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

DOI

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. 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. Half of the participants were shown a model statement before giving their responses. 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. These findings underscore the complexity of verbal lie detection and highlight the need to better understand when and how baselining techniques are most effective.

Identifier
DOI https://doi.org/10.34894/GI4MVT
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/GI4MVT
Provenance
Creator Glynis, Bogaard ORCID logo; Broers, Nick J. ORCID logo; Meijer, Ewout H. ORCID logo
Publisher DataverseNL
Contributor faculty data manager FPN; Bogaard, Glynis
Publication Year 2025
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact faculty data manager FPN (Maastricht University); Bogaard, Glynis (Maastricht University)
Representation
Resource Type Experimental data; Dataset
Format application/x-spss-sav
Size 19801; 15931
Version 1.1
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences