Measuring cues to deception: a multitrait-multimethod analysis
dc.contributor.advisor | Leach, Amy-May | |
dc.contributor.author | Lahay, Ryan | |
dc.date.accessioned | 2022-01-17T20:13:24Z | |
dc.date.accessioned | 2022-03-29T17:44:00Z | |
dc.date.available | 2022-01-17T20:13:24Z | |
dc.date.available | 2022-03-29T17:44:00Z | |
dc.date.issued | 2021-12-01 | |
dc.degree.discipline | Forensic Psychology | |
dc.degree.level | Master of Science (MSc) | |
dc.description.abstract | Cognitive load and arousal are constructs typically included in theories of deception, but they are often measured using a range of unvalidated techniques. Using a multitrait-multimethod analysis, I assessed the reliability and construct validity of common measures of cognitive load and arousal – self-report, trained coders’ observations, and behavioral measures – across three studies as secondary data. All measures showed good reliability, but achieved differing levels of validation. Measures of cognitive load (i.e., self-reported cognitive load, trained coders’ observations of thinking hard, and average response latency) showed some evidence of construct validity. In contrast, measures of arousal (i.e., self-reported arousal, trained coders’ observations of nervousness, and average skin conductance) did not achieve sufficiently high levels of validity. These findings suggest that researchers may not be assessing constructs of interest. Thus, researchers should exercise caution when using unvalidated measures to evaluate theories of, and the diagnosticity of cognitive and arousal-based cues to, deception. | en |
dc.description.sponsorship | University of Ontario Institute of Technology | en |
dc.identifier.uri | https://hdl.handle.net/10155/1396 | |
dc.language.iso | en | en |
dc.subject | Cues to deception | en |
dc.subject | Validity | en |
dc.subject | Multitrait-multimethod | en |
dc.title | Measuring cues to deception: a multitrait-multimethod analysis | en |
dc.type | Thesis | en |
thesis.degree.discipline | Forensic Psychology | |
thesis.degree.grantor | University of Ontario Institute of Technology | |
thesis.degree.name | Master of Science (MSc) |