Back to results

University of Ontario Institute of Technology

Dual-task interference and its influence on deception detection and memory

Abstract

dc:description.abstract

Using a dual-task paradigm, I examined how engaging in executive function tasks impacted deception detection and memory performance. University students (N = 185) were randomly assigned to detect deception while also performing a concurrent monitoring, memory, planning, motor, or visual task, or no additional task (single-task control). Compared to those in the single-task control condition, participants in the memory and planning conditions were significantly less likely to be accurate when detecting deception. Those in the memory condition self-reported experiencing higher ratings of cognitive load and exhibited poorer recognition. Differences in decision-making processes could not account for these effects. The results suggest performance deficits in deception detection can be attributable to isolated cognitive demands; even simply adding a secondary task can be impactful. Investigative interviewers may be particularly disadvantaged when under different types of cognitive load while detecting deception.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MSc)
Discipline thesis:degree_discipline
Forensic Psychology
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Blake, Chelsea K.
Advisor dc:contributor.advisor
  • Leach, Amy-May

Subjects

dc:subject × 4

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1671
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1671

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Blake, Chelsea K.. Dual-task interference and its influence on deception detection and memory. University of Ontario Institute of Technology, 2023. https://hdl.handle.net/10155/1671