The Role of Emotions as Mechanisms of Mid-Test Warning Messages DuringPersonality Testing: A Field Experiment

  • Hairong Li
  • , Jinyan Fan
  • , Guoxiang Zhao*
  • , Minghui Wang
  • , Lu Zheng
  • , Hui Meng
  • , Qingxiong Weng
  • , Yanping Liu
  • , Filip Lievens
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

This study focuses on the role of emotions in personnel selection and faking research. In particular, we posit that emotions are likely to be activated when applicants receive warning messages from organizations. Drawing on Nabi (Nabi, Communication Theory, 9, 1999, 292) cognitive-functional model of discrete negative emotions, we propose and empirically test the effects of three discrete negative emotions (guilt, fear, and anger) triggered by a warning message during a personality test on personality score accuracy and perceived test fairness. Participants in this within-subjects field experiment were 1,447 applicants for graduate school at a large public university in China. They completed two parallel forms of a personality test: one within a selection context, and another within a developmental context 6 months later as a baseline measure. In the selection context, a warning (or a control) message was randomly assigned to participants during the personality test. Emotions and perceived test fairness were measured after the test was completed. Results indicated that guilt, fear, and anger each played a unique role. Guilt explained how mid-test warnings improved personality score accuracy among fakers, whereas fear accounted for why nonfakers over-corrected their personality scores. Finally, anger explained why the mid-test warnings reduced perceived test fairness for both fakers and nonfakers.

Original languageEnglish
Pages (from-to)40-59
Number of pages20
JournalJournal of Applied Psychology
Volume107
Issue number1
DOIs
StatePublished - 2022

Keywords

  • Anger
  • Applicant faking
  • Fear
  • Guilt
  • Warnings

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