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Strong, but Wrong: Lay People’s and Police Officers’ Beliefs about Verbal and Nonverbal Cues to Deception
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The present study investigated the beliefs of students and police officers about cues to deception. A total of 95 police officers and 104 undergraduate students filled out a questionnaire addressing beliefs about cues to deception. Twenty-eight verbal cues were included in the questionnaire, all extracted from verbal credibility assessment tools (i.e., CBCA, RM, and SCAN). We investigated to what extent beliefs about nonverbal and verbal cues of deception differed between lay people (students) and police officers, and whether these beliefs were in agreement with objective cues known from research. Both students and police officers believed the usual stereotypical, but non-diagnostic (nonverbal) cues such as gaze aversion and increased movement to be indicative of deception. Yet, participants were less inclined to overestimate the relationship between verbal cues and deception and their beliefs fitted better with what we know from research. The implications of these findings for practice are discussed.
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“Liars often provide less consistent or coherent verbal accounts lacking informational content, with fewer event details (Bogaard et al., 2016; DePaulo et al., 2003; Hartwig et al., 2011).”
From Sorting Insiders From Co-Workers: Remote Synchronous Computer-Mediated Triage for Investigating Insider Attacks (2024) · cites this paper as Bogaard et al., 2016
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“Our results confirm findings of previous research in face-to-face and remote person-to-person contexts that questioning strategies which maximize cognitive burden can amplify signals of deception (e.g., Bogaard et al., 2016; DePaulo et al., 2003; Pentland et al., 2017), highlighting the potential of remote automated CMC.”
From Sorting Insiders From Co-Workers: Remote Synchronous Computer-Mediated Triage for Investigating Insider Attacks (2024) · cites this paper as Bogaard et al., 2016
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Metadata
- Authors
- Bogaard, G., Meijer, E. H., Vrij, A., & Merckelbach, H.
- Affiliations
- Maastricht University (NL)
- University of Portsmouth (GB)
- Corresponding author
- Bogaard, Glynis
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-06-03
- Volume
- 11
- Issue
- 6
- Pages
- e0156615
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4892574
- OpenAlex
- W2412576869
- Cited by
- 123
- References
- 71
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 9 · 2023: 16 · 2022: 14 · 2021: 19 · 2020: 18 · 2019: 15 · 2018: 8 · 2017: 8
- FWCI
- 16.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- Ministerie van Binnenlandse Zaken en Koninkrijksrelaties
- Topics
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- deception detection, verbal cues, nonverbal cues, lay beliefs, police officers, students, gaze aversion, credibility assessment, deception detection training
- MeSH terms
- Adult, Cues, Culture, Female, Humans, Deception, Male, Middle Aged, Surveys and Questionnaires, Students, Verbal Behavior, Police, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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