Behavior Genetics

, Volume 42, Issue 5, pp 743–763 | Cite as

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

  • Daniel A. BrileyEmail author
  • Elliot M. Tucker-Drob
Original Research


The Five Factor Model of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. For three of the Big Five domains, models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality.


Personality Five Factor Model Facet structure Broad versus narrow measurement Bandwidth-fidelity dilemma 



The Population Research Center at the University of Texas at Austin is supported by a center grant from the National Institute of Child Health and Human Development (R24 HD042849). We would like to thank John Loehlin and Sam Gosling for helpful comments on an earlier version of this article. Additionally, we would like to thank Chris Soto for the scoring algorithm for the CPI-Big Five.


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© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Psychology and Population Research CenterUniversity of Texas at AustinAustinUSA

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