How do you fake a personality test? An investigation of cognitive models of impression-managed responding
Mindy K. Shoss and
Michael J Strube
Organizational Behavior and Human Decision Processes, 2011, vol. 116, issue 1, 163-171
Abstract:
Because faking poses a threat to the validity of personality measures, research has focused on ways of detecting faking, including the use of response times. However, the applicability and validity of these approaches are dependent upon the actual cognitive process underlying faking. This study tested three competing cognitive models in order to identify the process underlying faking and to determine whether response time patterns are a viable method of detecting faking. Specifically, we used a within-subjects manipulation of instructions (respond honestly, make a good impression, make a specific impression) to examine whether the distribution of response times across response scale options (e.g., disagree, agree) could be used to identify faking on the NEO PI-R. Our results suggest that individuals reference a schema of an ideal respondent when faking. As a result, response time patterns such as the well-known inverted-U cannot be used to identify faking.
Keywords: Cognition; Faking; Personality; questionnaire (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0749597811000665
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jobhdp:v:116:y:2011:i:1:p:163-171
Access Statistics for this article
Organizational Behavior and Human Decision Processes is currently edited by John M. Schaubroeck
More articles in Organizational Behavior and Human Decision Processes from Elsevier
Bibliographic data for series maintained by Catherine Liu ().