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Faking Ipsative Questionnaires: The Role of General Mental Ability and Ability to Identify Criteria

Year: 2026

Type: article

Abstract: Questionnaires in ipsative (relative-to-self) formats ask respondents to compare several stimuli, for example behaviors or personal characteristics, at a time. Since it is impossible to endorse all desirable stimuli, the ipsative formats are often used in high-stakes personality assessments to reduce impression management (aka ‘faking good’). However, their high cognitive complexity may contaminate the intended measurement of personality with cognitive abilities. This study investigated the role of general mental ability (GMA) and the Ability to Identify Criteria (ATIC) in faking personality assessments utilizing a ‘graded preference’ format, scored normatively using Thurstonian modeling. We recruited N = 200 participants who completed the Leadership Style Questionnaire (de Klerk-van Someren et al., 2023) under two conditions: imagining they are applying for a specified job ( high-stakes condition) and responding normally ( low-stakes condition). In both completions, participants’ response latencies and click counts were recorded. The results indicate that participants can improve their scores on job-relevant traits, but effect sizes are small to medium (0.26 to 0.47). Participants with higher GMA tend to inflate their scores more, and participants with higher ATIC produce personality profiles that closer match the target job when faking. Through cross-classified path analysis, we unpick effects at block and person level and show that criteria recognition is the main driver for targeted increases in personality scores, and strategic editing of responses is the most plausible explanation for increased response latencies and click counts when faking. We also suggest that in repeated measures faking studies, high-stakes condition should precede low stakes.

Source: Journal of Business and Psychology

DOI: 10.1007/s10869-026-10135-x

Authors: Miriam Fuechtenhans, Anna Brown

Institution: University of Kent

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,090

Funder: Innovate UK