Systematic errors (biases) in applying verbal lie detection tools: richness in detail as a test case

Galit Nahari, Aldert Vrij

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

The current paper describes potential systematic errors (or biases) that may appear while applying content-based lie detection tools, by focusing on richness in detail–a core indicator in verbal tools–as a test case. Two categories of biases are discussed: those related to the interviewees (i.e., interviewees with different characteristics differ in the number of details they provide when lying or telling the truth) and those related to the tool expert (i.e., tool experts with different characteristics differ in the way they perceive and interpret verbal cues). We suggested several ways to reduce the influence of these biases, and emphasized the need for future studies in this matter.

Original languageEnglish
Pages (from-to)98-107
Number of pages10
JournalCrime Psychology Review
Volume1
Issue number1
DOIs
StatePublished - 1 Jan 2015

Bibliographical note

Publisher Copyright:
© 2016, © 2016 Taylor & Francis.

Keywords

  • Richness in detail
  • criteria based content analysis
  • judgmental biases
  • reality monitoring
  • scientific content analysis
  • verbal lie detection tools

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