title: Insurance based lie detection: Enhancing the verifiability approach with a model statement component.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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%.
  
  
  CONCLUSIONS
  Providing interviewee's with a model statement prime consisting of checkable detail appears to be a useful refinement to the VA procedure.
authors.affiliation: Department of Psychology, University of Portsmouth, UK. Electronic address: adam.harvey@port.ac.uk.
authors.forename: Adam C
authors.initials: AC
authors.lastname: Harvey
authors.affiliation: Department of Psychology, University of Portsmouth, UK.
authors.forename: Aldert
authors.initials: A
authors.lastname: Vrij
authors.affiliation: Department of Psychology, University of Portsmouth, UK.
authors.forename: Sharon
authors.initials: S
authors.lastname: Leal
authors.affiliation: Department of Psychology, University of Portsmouth, UK.
authors.forename: Marcus
authors.initials: M
authors.lastname: Lafferty
authors.affiliation: Department of Criminology, Bar-Ilan University, Israel.
authors.forename: Galit
authors.initials: G
authors.lastname: Nahari
mesh_terms: D000293:Adolescent; D000328:Adult; D008192:Deception; D005260:Female; D006801:Humans; D007344:Insurance Claim Reporting; D007345:Insurance Claim Review; D008014:Lie Detection; D008297:Male; D055815:Young Adult
keywords: Insurance interviewing; eliciting cues; lie detection