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General Traits of Personality and Affectivity as Predictors of Satisfaction in Intimate Relationships: Evidence from Self‐ and Partner‐Ratings

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Watson, David, Hubbard, Brock, Wiese, David·2000·Journal of Personality

Abstract

Self‐ and partner‐ratings on trait affect and the Big Five were obtained from 74 married and 136 dating couples. The relationship satisfaction of each person (the ‘target’) was correlated with four sets of ratings: (a) target’s self‐rated personality, (b) target’s partner‐rated personality, (c) partner’s self‐rated personality, and (d) partner’s target‐rated personality. Self‐ and partner‐ratings of the target’s personality yielded very similar results. Negative and positive affectivity were consistent predictors of satisfaction in both samples. Conscientiousness and agreeableness were reliably related to satisfaction in the dating couples, whereas extraversion consistently correlated with satisfaction in the married couples. These traits jointly predicted as much as 34% (self‐ratings) and 26% (partner‐ratings) of the variance in satisfaction. In contrast, the partner’s personality played a lesser role in satisfaction.

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Metadata

Authors
Watson, D., Hubbard, B., & Wiese, D.
Venue
Journal of Personality
Publisher
Wiley
Published
2000-06
Volume
68
Issue
3
Pages
413-449
ISSN
  • 0022-3506 (ISSN-L)
  • 1467-6494
OpenAlex
W2069704569
Cited by
313
References
0
FWCI
7.06
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: General Traits of Personality and Affectivity as Predictors of Satisfaction in Intimate Relationships: Evidence from Self‐ and Partner‐Ratings. https://app.cochat.ai/papers/10.1111/1467-6494.00102
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Watson, D., Hubbard, B., & Wiese, D. (2000). General Traits of Personality and Affectivity as Predictors of Satisfaction in Intimate Relationships: Evidence from Self‐ and Partner‐Ratings. Journal of Personality. https://doi.org/10.1111/1467-6494.00102

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.