Lies divorced from context: evidence for Context Embedded Perception (CEP) as a feasible measure for deception detection

Zvi Nisin, Galit Nahari, Morris Goldsmith

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


This study examined the efficacy of a novel measure for lie detection—Context Embedded Perception (CEP). CEP exploits a qualitative difference between the functional roles of provided perceptual and contextual details: By framing the perceptual details in time and space, or by annotating them semantically, the contextual details are those that confer upon the perceptual details the status of verifiability. Consequently, expanding on the tenets of the Verifiability Approach (VA), liars, who are generally motivated to adopt an ‘unverifiable-information’ reporting strategy, should also tend to avoid such contextualization. The proportion of contextual details can then be used to differentiate deceptive from truthful accounts. Participants provided deceptive or truthful accounts during a mock-crime interview; Half were warned beforehand about an upcoming verification procedure and ratification interview. For each account, the CEP measure was calculated as the proportion of contextual details out of contextual and perceptual details combined. As predicted, CEP scores were significantly lower for liars than for truthtellers; warning condition had no effect. A CEP-based discriminant function correctly identified 92% of the truthtellers and 66% of the liars, resulting in 79% total classification accuracy. CEP’s theoretical and practical strengths and weaknesses, specifically in relation to sources of verifiability, are discussed.

Original languageEnglish
Pages (from-to)189-205
Number of pages17
JournalPsychology, Crime and Law
Issue number2
StatePublished - 2024

Bibliographical note

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© 2022 Informa UK Limited, trading as Taylor & Francis Group.


  • Context Embedded Perception
  • Verifiability approach
  • detection of deception
  • output-bound measures
  • verbal lie detection


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