Bottom up construction of a personality taxonomy

David M. Condon, Dustin Wood, Rene Mottus, Tom Booth, Giulio Costantini, Samuel Greiff, Wendy Johnson, Aaron Lukaszewski, Aja Louise Murray, William Revelle, Aidan G. C. Wright, Matthias Ziegler, Johannes Zimmermann

Research output: Contribution to journalArticlepeer-review

Abstract

In pursuit of a more systematic and comprehensive framework for personality assessment, we introduce procedures for assessing personality traits at the lowest level: nuances. We argue that constructing a personality taxonomy from the bottom up addresses some of the limitations of extant top-down assessment frameworks (e.g., the Big Five), including the opportunity to resolve confusion about the breadth and scope of traits at different levels of organization, evaluate unique and reliable trait variance at the item level, and clarify jingle/jangle issues in personality assessment. With a focus on applications in survey methodology and transparent documentation, our procedures contain six steps: (1) identification of a highly inclusive pool of candidate items, (2) programmatic evaluation and documentation of item characteristics, (3) test-retest analyses of items with adequate qualitative and quantitative properties, (4) analysis of cross-ratings from multiple raters for items with adequate retest reliability, (5) aggregation of ratings across diverse samples to evaluate generalizability across populations, (6) evaluations of predictive utility in various contexts. We hope these recommendations are the first step in a collaborative effort to identify a comprehensive pool of personality nuances at the lowest level, enabling subsequent construction of a robust hierarchy -- from the bottom up.
Original languageEnglish
Pages (from-to)923-934
Number of pages12
JournalEuropean journal of psychological assessment
Volume36
Issue number6
Early online date19 Jan 2021
DOIs
Publication statusE-pub ahead of print - 19 Jan 2021

Keywords

  • personality assessment
  • taxonomy
  • nuances
  • hierarchy
  • survey methodology

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