Department of Psychology, University of Minnesota, Minnesota, MN, USA.
Department of Family, Population, & Preventative Medicine, Program in Public Health, Stony Brook University, Stony Brook, NY, USA.
J Pers. 2023 Jun;91(3):653-666. doi: 10.1111/jopy.12765. Epub 2022 Aug 30.
Loneliness represents a public health threat given its central role in predicting adverse mental and physical health outcomes. Prior research has established four of the Big Five personality traits as consistent cross-sectional predictors of loneliness in largely western, White samples. However, it is not clear if the personality predictors of loneliness vary across cultures.
The present study estimates associations between the Big Five traits and loneliness across distinct samples of White American, Black American, and Japanese adults (n = 6051 at T1). Confirmatory factor analysis and exploratory structural equation modeling were used to examine measurement invariance properties of the Big Five and loneliness across these groups. The factor structures were then carried forward to estimate associations between personality and loneliness across two assessments waves using structural equation modeling.
While Neuroticism was a strong predictor across groups, low Extraversion was more predictive of loneliness in Japan than in the U.S., and low Conscientiousness was only a significant predictor in the U.S.
Previous literature offers a framework for interpreting these findings in that loneliness may be shaped comparatively more through interconnectedness in Japanese culture, while, in the U.S., individual goals and personal romantic expectations are more salient.
孤独感是一种公共健康威胁,因为它在预测不良心理和身体健康结果方面起着核心作用。先前的研究已经确定了五大人格特质中的四个特质,它们是孤独感在很大程度上是西方、白人样本的一致横断面预测因素。然而,尚不清楚孤独感的人格预测因素是否因文化而异。
本研究在白人美国、黑人美国和日本成年人的不同样本中(T1 时 n=6051),估计了大五人格特质与孤独感之间的关联。验证性因子分析和探索性结构方程模型用于检验大五人格和孤独感在这些群体中的测量不变性特征。然后,将这些因子结构进一步用于使用结构方程模型估计两个评估波次之间人格与孤独感之间的关联。
虽然神经质在所有群体中都是一个强有力的预测因素,但在日本,低外向性比在美国更能预测孤独感,而低尽责性在美国才是一个显著的预测因素。
先前的文献为解释这些发现提供了一个框架,即孤独感可能在日本文化中通过相互联系而形成,而在美国,个人目标和个人浪漫期望则更为突出。