Contextual considerations for deception production and detection in forensic interviews
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Date
2023-02-07
Authors
Markowitz, David M.
Hancock, Jeffery T.
Woodworth, Michael T.
Ely, Maxwell
Journal Title
Journal ISSN
Volume Title
Publisher
Frontiers in Psychology
Abstract
Most deception scholars agree that deception production and deception detection
effects often display mixed results across settings. For example, some liars use more
emotion than truth-tellers when discussing fake opinions on abortion, but not
when communicating fake distress. Similarly, verbal and nonverbal cues are often
inconsistent predictors to assist in deception detection, leading to mixed accuracies
and detection rates. Why are lie production and detection effects typically inconsistent?
In this piece, we argue that aspects of the context are often unconsidered in how lies
are produced and detected. Greater theory-building related to contextual constraints
of deception are therefore required. We reintroduce and extend the Contextual
Organization of Language and Deception (COLD) model, a framework that outlines
how psychological dynamics, pragmatic goals, and genre conventions are aspects of
the context that moderate the relationship between deception and communication
behavior such as language. We extend this foundation by proposing three additional
aspects of the context — individual differences, situational opportunities for deception,
and interpersonal characteristics — for the COLD model that can specifically inform
and potentially improve forensic interviewing. We conclude with a forward-looking
perspective for deception researchers and practitioners related to the need for more
theoretical explication of deception and its detection related to the context.
Description
7 pages
Keywords
Deception, Lying, Context, Cold model, Language, Forensic interviewing
Citation
Markowitz DM, Hancock JT, Woodworth MT and Ely M (2023) Contextual considerations for deception production and detection in forensic interviews. Front. Psychol. 14:1134052. doi: 10.3389/fpsyg.2023.1134052