Faking on self-report emotional intelligence and personality tests: Effects of faking opportunity, cognitive ability, and job type

► Faking on trait-EI and personality scales is examined in a simulated selection setting. ► Faking is 60% greater when faking opportunity is above average. ► Faking is 26% greater on job-relevant traits and 20% greater when g is above average. ► Combining conditions yields 3.6× the faking seen under...

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Bibliographic Details
Published in:Personality and individual differences 2012, Vol.52 (2), p.195-201
Main Authors: Tett, Robert P., Freund, Kurt A., Christiansen, Neil D., Fox, Kevin E., Coaster, John
Format: Article
Language:English
Subjects:
Biological and medical sciences
Cognitive abilities
Cognitive ability
Computers
Emotional intelligence
Emotions
Faking
Fundamental and applied biological sciences. Psychology
Intelligence
Nurse practitioners
Personality
Personality testing
Personality tests
Personality. Affectivity
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics
Selfreport
Trait specificity
Trait-emotional intelligence
Trait-job-relevance
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Summary:► Faking on trait-EI and personality scales is examined in a simulated selection setting. ► Faking is 60% greater when faking opportunity is above average. ► Faking is 26% greater on job-relevant traits and 20% greater when g is above average. ► Combining conditions yields 3.6× the faking seen under low faking conditions. ► Prior faking estimates averaging across conditions understate the faking problem. We assessed the combined effects of cognitive ability, opportunity to fake, and trait job-relevance on faking self-report emotional intelligence and personality tests by having 150 undergraduates complete such tests honestly and then so as to appear ideal for one of three jobs: nurse practitioner, marketing manager, and computer programmer. Faking, as expected, was greater (a) in higher- g participants, (b) in those scoring lower under honest conditions (with greater opportunity to fake), and (c) on job-relevant traits. Predicted interactions accounted for additional unique variance in faking. Combining all three factors yielded a “perfect storm” standardized difference of around 2, more than double the overall .83 estimate. Implications for the study of faking are discussed.
ISSN:0191-8869
1873-3549
DOI:10.1016/j.paid.2011.10.017