Individual Difference Variables, Affective Differentiation, and the Structures of Affect


  • *Antonio Terracciano, Robert R. McCrae, Dirk Hagemann, and Paul T. Costa, Jr., Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore.
    Dirk Hagemann is now at the Department of Psychology, Universität Trier, Trier, Germany.
    Portions of this research were presented at the Society for Multivariate Experimental Psychology, Charlottesville, VA, October, 2002, and at the NYAS conference “Emotions Inside Out: 130 Years After Darwin's The expression of the emotions in man and animals,” New York, November, 2002. We wish to thank Ivan Conte, Lisa Di Blas, Carmen Migliaccio, and Bruno Varriale for their help in recruiting subjects. Thanks to an anonymous reviewer for helpful comments that contributed to the interpretation of results and to Jerry Wiggins and Krista Trobst for ratings.

Address correspondence to Antonio Terracciano, Laboratory of Personality & Cognition, National Institute on Aging, NIH, 5600 Nathan Shock Drive, Baltimore, MD 21224-6825. E-mail:


Abstract Methodological arguments are usually invoked to explain variations in the structure of affect. Using self-rated affect from Italian samples (N=600), we show that individual difference variables related to affective differentiation can moderate the observed structure. Indices of circumplexity (Browne, 1992) and congruence coefficients to the hypothesized target were used to quantify the observed structures. Results did not support the circumplex model as a universal structure. A circular structure with axes of activation and valence was approximated only among more affectively differentiated groups: students and respondents with high scores on Openness to Feelings and measures of negative emotionality. A different structure, with unipolar Positive Affect and Negative Affect factors, was observed among adults and respondents with low Openness to Feelings and negative emotionality. The observed structure of affect will depend in part on the nature of the sample studied.