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Caught virtually lying – crime scenes in virtual reality help to expose suspects' concealed recognition

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Norman, Danielle, Wade, Kimberley A., Williams, Mark A. and Watson, Derrick G. (2020) Caught virtually lying – crime scenes in virtual reality help to expose suspects' concealed recognition. Journal of Applied Memory and Cognition, 9 (1). pp. 118-127. doi:10.1016/j.jarmac.2019.12.008 ISSN 2211-3681.

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Official URL: https://doi.org/10.1016/j.jarmac.2019.12.008

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Abstract

We explore how virtual reality could be used in police investigations to take a suspect ‘back in time’ and demonstrate that they recognize a crime scene despite claiming not to. In this study, participants committed a mock crime before being incentivized to conceal recognition of crime related details (e.g., the stolen item or crime scene). The crime scenes and objects were laser scanned, converted to photo-realistic models, and presented to suspects either in Virtual Reality (VR) or as 2D images on a computer screen. While concealing recognition of crime information, participants’ heart rate and skin conductance were measured using a Concealed Information Test (CIT) to assess recognition. Detection of concealed recognition increased by over 25% when participants viewed crime items in VR compared to 2D images. Our findings suggest that revisiting crime scenes or objects in VR may enhance stimulus recognition and salience resulting in increased CIT diagnosticity.

Item Type: Journal Article
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Faculty of Science, Engineering and Medicine > Science > Psychology
Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Journal or Publication Title: Journal of Applied Memory and Cognition
Publisher: Elsevier
ISSN: 2211-3681
Official Date: March 2020
Dates:
DateEvent
March 2020Published
1 February 2020Available
25 December 2019Accepted
Volume: 9
Number: 1
Page Range: pp. 118-127
DOI: 10.1016/j.jarmac.2019.12.008
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 14 January 2020
Date of first compliant Open Access: 1 February 2021
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