Literature DB >> 28088655

Insurance based lie detection: Enhancing the verifiability approach with a model statement component.

Adam C Harvey1, Aldert Vrij2, Sharon Leal2, Marcus Lafferty2, Galit Nahari3.   

Abstract

PURPOSE: The Verifiability Approach (VA) is verbal lie detection tool that has shown promise when applied to insurance claims settings. This study examined the effectiveness of incorporating a Model Statement comprised of checkable information to the VA protocol for enhancing the verbal differences between liars and truth tellers.
METHOD: The study experimentally manipulated supplementing (or withholding) the VA with a Model Statement. It was hypothesised that such a manipulation would (i) encourage truth tellers to provide more verifiable details than liars and (ii) encourage liars to report more unverifiable details than truth tellers (compared to the no model statement control). As a result, it was hypothesized that (iii) the model statement would improve classificatory accuracy of the VA. Participants reported 40 genuine and 40 fabricated insurance claim statements, in which half the liars and truth tellers where provided with a model statement as part of the VA procedure, and half where provide no model statement.
RESULTS: All three hypotheses were supported. In terms of accuracy, the model statement increased classificatory rates by the VA considerably from 65.0% to 90.0%.
CONCLUSION: Providing interviewee's with a model statement prime consisting of checkable detail appears to be a useful refinement to the VA procedure.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Insurance interviewing; eliciting cues; lie detection

Mesh:

Year:  2017        PMID: 28088655     DOI: 10.1016/j.actpsy.2017.01.001

Source DB:  PubMed          Journal:  Acta Psychol (Amst)        ISSN: 0001-6918


  5 in total

1.  Digging Further Into the Speech of Liars: Future Research Prospects in Verbal Lie Detection.

Authors:  Galit Nahari; Zvi Nisin
Journal:  Front Psychiatry       Date:  2019-02-12       Impact factor: 4.157

2.  Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling.

Authors:  Bennett Kleinberg; Yaloe van der Toolen; Aldert Vrij; Arnoud Arntz; Bruno Verschuere
Journal:  Appl Cogn Psychol       Date:  2018-04-02

3.  The first direct replication on using verbal credibility assessment for the detection of deceptive intentions.

Authors:  Bennett Kleinberg; Lara Warmelink; Arnoud Arntz; Bruno Verschuere
Journal:  Appl Cogn Psychol       Date:  2018-07-16

Review 4.  Verbal Deception and the Model Statement as a Lie Detection Tool.

Authors:  Aldert Vrij; Sharon Leal; Ronald P Fisher
Journal:  Front Psychiatry       Date:  2018-10-09       Impact factor: 4.157

5.  Detecting false intentions using unanticipated questions.

Authors:  Glynis Bogaard; Joyce van der Mark; Ewout H Meijer
Journal:  PLoS One       Date:  2019-12-11       Impact factor: 3.240

  5 in total

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