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人格轮廓的相似性和积极性始终能预测二元组中的关系满意度。

Similarity and Positivity of Personality Profiles Consistently Predict Relationship Satisfaction in Dyads.

作者信息

Brandstätter Hermann, Brandstätter Veronika, Pelka Rainer B

机构信息

Institute of Education Science and Psychology, Johannes Kepler University Linz, Linz, Austria.

Department of Psychology, University of Zurich, Zurich, Switzerland.

出版信息

Front Psychol. 2018 Jun 29;9:1009. doi: 10.3389/fpsyg.2018.01009. eCollection 2018.

Abstract

The effect of similarities in the personality traits of romantic partners on their relationship satisfaction () has often been studied, albeit with mixed results. Beyond the main effects of personality traits, incremental validity was often completely missing, or at least very low. In contrast, our five studies, three cross-sectional - including one study on leader-follower dyads to secure generalizability - and two longitudinal, show that, in predicting , the beta-coefficients of (where distance is defined as the average across items of absolute differences between the two partners' self-ratings) or (where positivity is defined as the frequency of extremely positive self-ratings) increase when either the of the profiles or the between the profiles is added as second predictor. Thus, positivity and distance seem to function as reciprocal suppressor variables that allow controlling for irrelevant components of the predictors. Consequently, when combined with positivity, distance proved to be a consistently better predictor of than has been reported in most previous studies. Combining profile distance with profile positivity appears to be promising well beyond research on , in that an individual profile of traits can be matched with a profile of a specific environment's offers and demands when person-environment fit is the focus of interest.

摘要

浪漫伴侣人格特质的相似性对其关系满意度()的影响经常被研究,尽管结果不一。除了人格特质的主效应外,增量效度往往完全缺失,或者至少非常低。相比之下,我们的五项研究,三项横断面研究——包括一项关于领导-下属二元组的研究以确保普遍性——以及两项纵向研究表明,在预测时,当将轮廓的(其中距离定义为两个伴侣自我评分之间绝对差异的项目平均值)或(其中积极性定义为极端积极自我评分的频率)作为第二个预测变量添加时,或轮廓之间的的β系数会增加。因此,积极性和距离似乎起到了相互抑制变量的作用,从而可以控制预测变量的无关成分。因此,与积极性相结合时,距离被证明是比大多数先前研究中报告的更好的关系满意度预测指标。将轮廓距离与轮廓积极性相结合似乎在关系满意度研究之外也很有前景,因为当人与环境匹配是关注焦点时,个人特质轮廓可以与特定环境的提供和需求轮廓相匹配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/974f/6034067/91e9172c8ee9/fpsyg-09-01009-g001.jpg

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