Understanding the Clance Impostor Phenomenon Scale Through the Lens of a Bifactor Model

Abstract

Abstract: The Clance Impostor Phenomenon Scale (CIPS) is the most frequently used self-report instrument for the assessment of the Impostor Phenomenon (IP). The literature provided mixed findings on the factorial structure of the CIPS. We extend previous work on the German-language CIPS by testing a bifactor exploratory factor model in two large and independently collected samples ( Ntotal = 1,794). Our analyses show that the bifactor model comprising a general IP factor and three group factors (labeled Luck, Fear of Failure, and Discount) fits the data well and 7 of the 20 items could be clearly assigned to the factors. The general factor (ω ≥ .90) and facets (α ≥ .67) show satisfying internal consistencies and differential correlations to attributional styles and the broader Big Five and HEXACO personality traits. Our findings support the use of the CIPS total score and expand the understanding of the CIPS’ multidimensional measurement model. Taking limitations into account, the identification and use of fine-grained facets contribute to understanding the correlates and consequences of the IP. We discuss potential improvements to the CIPS.