Literature DB >> 31070382

Does forcing reduce faking? A meta-analytic review of forced-choice personality measures in high-stakes situations.

Mengyang Cao1, Fritz Drasgow2.   

Abstract

Forced-choice (FC) is a popular format for developing personality measures, where individuals must choose 1 or multiple statements from several options. Although FC measures have been proposed to reduce score inflation in high-stakes assessments, inconsistent results have been found in empirical studies regarding their effectiveness. In this study, we conducted a meta-analysis of studies comparing FC personality measure scores between low-stakes and (both simulated and actual) high-stakes situations. Results suggest that the overall score inflation effect size for FC personality measures is 0.06. In selection scenarios, score inflation for FC scales is much lower than the meta-analytic effect size for single-statement personality measures across most personality facets. The score inflation effect size was also found to vary across FC scale characteristics and study design factors. Specifically, FC scales were consistently found to be more faking-resistant when constructed with statements balanced in social desirability and with responses scored via a normative approach. FC scales constructed with the PICK format were also found to be faking-resistant, while more applicant-incumbent studies are needed to examine the fakability of MOLE FC scales. Evidence at the overall level supports the use of multidimensional scales and extremity balance of statements, but results are not consistent across personality facets, or when large samples are excluded. Personality facets of high relevance to the target job were found to exhibit larger inflation than facets of low relevance to the target job. Practical guidance on constructing and using FC personality measures for personnel selection purposes is provided. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Year:  2019        PMID: 31070382     DOI: 10.1037/apl0000414

Source DB:  PubMed          Journal:  J Appl Psychol        ISSN: 0021-9010


  5 in total

1.  autoFC: An R Package for Automatic Item Pairing in Forced-Choice Test Construction.

Authors:  Mengtong Li; Tianjun Sun; Bo Zhang
Journal:  Appl Psychol Meas       Date:  2021-10-08

2.  A genetic algorithm for optimal assembly of pairwise forced-choice questionnaires.

Authors:  Rodrigo Schames Kreitchmann; Francisco J Abad; Miguel A Sorrel
Journal:  Behav Res Methods       Date:  2021-09-09

3.  Applying Evidence-Centered Design to Measure Psychological Resilience: The Development and Preliminary Validation of a Novel Simulation-Based Assessment Methodology.

Authors:  Sabina Kleitman; Simon A Jackson; Lisa M Zhang; Matthew D Blanchard; Nikzad B Rizvandi; Eugene Aidman
Journal:  Front Psychol       Date:  2022-01-10

4.  Transformer-Based Deep Neural Language Modeling for Construct-Specific Automatic Item Generation.

Authors:  Björn E Hommel; Franz-Josef M Wollang; Veronika Kotova; Hannes Zacher; Stefan C Schmukle
Journal:  Psychometrika       Date:  2021-12-14       Impact factor: 2.290

5.  Modeling Faking in the Multidimensional Forced-Choice Format: The Faking Mixture Model.

Authors:  Susanne Frick
Journal:  Psychometrika       Date:  2021-12-20       Impact factor: 2.290

  5 in total

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