Merz Erin L, Roesch Scott C
SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 6363 Alvarado Court, Suite 103, San Diego, CA 92120-4913, USA.
Pers Individ Dif. 2011 Dec 1;51(8):915-919. doi: 10.1016/j.paid.2011.07.022.
Interactions among the dimensions of the Five Factor Model (FFM) have not typically been evaluated in mental health research, with the extant literature focusing on bivariate relationships with psychological constructs of interest. This study used latent profile analysis to mimic higher-order interactions to identify homogenous personality profiles using the FFM, and also examined relationships between resultant profiles and affect, self-esteem, depression, anxiety, and coping efficacy. Participants (N = 371) completed self-report and daily diary questionnaires. A 3-profile solution provided the best fit to the data; the profiles were characterized as well-adjusted, reserved, and excitable. The well-adjusted group reported better psychological functioning in validation analyses. The reserved and excitable groups differed on anxiety, with the excitable group reporting generally higher anxiety than the reserved group. Latent profile analysis may be a parsimonious way to model personality heterogeneity.
五因素模型（FFM）各维度之间的相互作用在心理健康研究中通常未得到评估，现有文献主要关注与感兴趣的心理结构的二元关系。本研究使用潜在剖面分析来模拟高阶相互作用，以使用FFM识别同质的人格剖面，并检验所得剖面与情感、自尊、抑郁、焦虑和应对效能之间的关系。参与者（N = 371）完成了自我报告和日常日记问卷。一个三剖面解决方案对数据拟合最佳；这些剖面的特征分别为适应良好型、内向型和易激动型。在验证分析中，适应良好组报告的心理功能更好。内向型和易激动型在焦虑方面存在差异，易激动组报告的焦虑总体上高于内向型组。潜在剖面分析可能是一种简约的方式来对人格异质性进行建模。
