Dissertation/Thesis Abstract

Detecting deception using drawings
by De Cicco, Anthony, M.A., Western Illinois University, 2015, 64; 1597373
Abstract (Summary)

Detecting deception remains a difficult task. Currently, much of the detecting deception techniques rely on arousal-based interviewing, which has been deemed ineffective in determining veracity. The current study examines the possibility of using cognitive load theory, through the use of drawings, to circumvent the limitations of arousal-based interviewing. A predictive model was created from variables used in previous research, as well as new variables in attempt to strengthen previous models. Participants were asked to perform three predesignated tasks. After the three tasks were completed, participants were chosen at random to either lie about the tasks performed or to tell the truth. When the participants assumed their roles, they were asked to fill out a questionnaire which first asked the participants to recall the event through a narrative. Next participants were asked to draw a picture of the event. A comparison of means analysis revealed that drawings accurately distinguished a participant in the truthful condition from a participant in the deceptive condition.

Indexing (document details)
Advisor: Schafer, John R.
Commitee: Dodson, Kimberly D., Meyers, Jill J.
School: Western Illinois University
Department: Law Enforcement and Justice Administration
School Location: United States -- Illinois
Source: MAI 55/01M(E), Masters Abstracts International
Subjects: Communication, Criminology, Cognitive psychology
Keywords: Cognitive load, Deception, Detecting, Drawing, Lying
Publication Number: 1597373
ISBN: 9781339001685
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