Psychologische Hochschule Berlin.
Department of Psychology, University of Pittsburgh.
J Abnorm Psychol. 2019 Nov;128(8):823-839. doi: 10.1037/abn0000460. Epub 2019 Sep 26.
Interpersonal problems are key transdiagnostic constructs in psychopathology. In the past, investigators have neglected the importance of operationalizing interpersonal problems according to their latent structure by using divergent representations of the construct: (a) computing scores for severity, agency, and communion ("dimensional approach"), (b) classifying persons into subgroups with respect to their interpersonal profile ("categorical approach"). This hinders cumulative research on interpersonal problems, because findings cannot be integrated both from a conceptual and a statistical point of view. We provide a comprehensive evaluation of interpersonal problems by enlisting several large samples (Ns = 5,400, 491, 656, and 712) to estimate a set of latent variable candidate models, covering the spectrum of purely dimensional (i.e., confirmatory factor analysis using Gaussian and nonnormal latent t-distributions), hybrid (i.e., semiparametric factor analysis), and purely categorical approaches (latent class analysis). Statistical models were compared with regard to their structural validity, as evaluated by model fit (corrected Akaike's information criterion and the Bayesian information criterion), and their concurrent validity, as defined by the models' ability to predict relevant external variables. Across samples, the fully dimensional model performed best in terms of model fit, prediction, robustness, and parsimony. We found scant evidence that categorical and hybrid models provide incremental value for understanding interpersonal problems. Our results indicate that the latent structure of interpersonal problems is best represented by continuous dimensions, especially when one allows for nonnormal latent distributions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
人际关系问题是精神病理学中关键的跨诊断结构。过去,研究人员忽视了根据潜在结构对人际关系问题进行操作化的重要性,使用了该结构的不同表示方式:(a)计算严重程度、能动性和交流性的分数(“维度方法”),(b)根据人际特征对人进行分类(“分类方法”)。这阻碍了人际关系问题的累积研究,因为从概念和统计的角度来看,无法整合研究结果。我们通过招募几个大型样本(N=5400、491、656 和 712),对人际关系问题进行了全面评估,以估计一组潜在变量候选模型,涵盖了纯粹维度(即使用高斯和非正态潜在 t 分布的验证性因素分析)、混合(即半参数因素分析)和纯粹分类方法(潜在类别分析)的范围。统计模型在结构有效性方面进行了比较,通过模型拟合(修正的赤池信息量准则和贝叶斯信息量准则)进行评估,以及通过模型预测相关外部变量的能力进行了同时有效性评估。在所有样本中,完全维度模型在模型拟合、预测、稳健性和简约性方面表现最佳。我们发现几乎没有证据表明分类和混合模型为理解人际关系问题提供了额外的价值。我们的结果表明,人际关系问题的潜在结构最好用连续维度来表示,特别是当允许存在非正态潜在分布时。(心理学信息数据库记录(c)2019 APA,保留所有权利)。