The Prospective Predictive Power of Parent-Reported Personality Traits and Facets in First-Onset Depression in Adolescent Girls

面(心理学) 人格 心理学 五大性格特征 萧条(经济学) 特质 逻辑回归 开放的体验 预测能力 人格评估量表 临床心理学 发展心理学 医学 社会心理学 经济 宏观经济学 哲学 认识论 计算机科学 内科学 程序设计语言
作者
Yiming Zhong,Greg Perlman,Daniel N. Klein,Jingwen Jin,Roman Kotov
出处
期刊:Research on Child and Adolescent Psychopathology [Springer Nature]
卷期号:52 (8): 1221-1231
标识
DOI:10.1007/s10802-024-01186-w
摘要

Abstract Certain personality traits and facets are well-known risk factors that predict first-onset depression during adolescence. However, prior research predominantly relied on self-reported data, which has limitations as a source of personality information. Reports from close informants have the potential to increase the predictive power of personality on first-onsets of depression in adolescents. With easy access to adolescents’ behaviors across settings and time, parents may provide important additional information about their children’s personality. The same personality trait(s) and facet(s) rated by selves (mean age 14.4 years old) and biological parents at baseline were used to prospectively predict depression onsets among 442 adolescent girls during a 72-month follow-up. First, bivariate logistic regression was used to examine whether parent-reported personality measures predicted adolescent girls’ depression onsets; then multivariate logistic regression was used to test whether parent reports provided additional predictive power above and beyond self-reports of same trait or facet. Parent-reported personality traits and facets predicted adolescents’ depression onsets, similar to findings using self-reported data. After controlling for the corresponding self-report measures, parent-reported higher openness (at the trait level) and higher depressivity (at the facet-level) incrementally predicted first-onset of depression in the sample. Findings demonstrated additional variance contributed by parent-reported personality measures and validated a multi-informant approach in using personality to prospectively predict onsets of depression in adolescent girls.
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