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Related Experiment Videos

Structure of the Coolidge Axis II Inventory Personality Disorder Scales from the five-factor model perspective

N V Ramanaiah1, J P Sharpi

  • 1Department of Psychology, Southern Illinois University, Carbondale 62901-6502, USA.

Psychological Reports
|January 29, 1999
PubMed
Summary

The five-factor model of personality effectively describes personality disorders when canonical variates are rotated. This study supports the model's generality and comprehensiveness in personality disorder research.

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Area of Science:

  • Psychology
  • Personality Psychology
  • Clinical Psychology

Background:

  • The five-factor model (FFM) is a prominent framework for understanding personality structure.
  • Previous research by Coolidge et al. (1994) using canonical correlation analysis did not support the FFM's applicability to personality disorders.
  • A key limitation identified was the lack of rotation for canonical variates, potentially hindering simple structure and meaningful interpretation.

Discussion:

  • This study re-evaluated the FFM's utility for personality disorders by employing canonical correlation analysis with varimax rotation.
  • The rotation aimed to achieve better simple structure and meaningfulness in the canonical variates, addressing limitations of prior research.
  • The findings were compared against the results of Coolidge et al. to test the hypothesis regarding the impact of rotation.

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Key Insights:

  • Canonical correlation analysis with varimax rotation revealed five significant canonical variate pairs.
  • These variate pairs were interpretable as the core dimensions of the FFM: Neuroticism, Extraversion, Openness, Disagreeableness, and Conscientiousness.
  • The results support the hypothesis that the failure to rotate variates in previous studies obscured the FFM's structure in personality disorders.

Outlook:

  • The findings suggest that the FFM is a generalizable and comprehensive model for describing the structure of personality disorders.
  • Further research could explore the application of this rotated approach across diverse clinical populations.
  • This study underscores the importance of appropriate statistical techniques in validating personality models.