Department of Psychology, University of Toronto.
Department of Psychiatry, University of Toronto.
Personal Disord. 2024 Sep;15(5):322-331. doi: 10.1037/per0000687.
In this study, we compare the incremental predictive capacities of the , Section II personality disorders (SII-PDs) with Section III trait domains of the Alternative Model of Personality Disorders (AMPD) in a psychiatric outpatient sample ( = 185). To this end, a series of hierarchical regression analyses was conducted in which the 10 SII-PDs and the five AMPD trait domains served as the predictor variables and five areas of clinical dysfunction as the criterion variables. Two models for each criterion were tested. In Model A, the 10 PDs were entered as a block, followed by the block entry of trait domains; in Model B, the block entry of these predictors was reversed. As the AMPD was designed to address the shortcomings of the SII-PDs, it was hypothesized that the AMPD trait domains would show greater predictive capacity vis-à-vis the latter by (a) explaining more overall variance for each criterion variables when entered first into the model versus when SII-PDs was entered first and (b) explaining more incremental variance than SII-PDs when block was entered second. These hypotheses were partially supported. Overall, the AMPD trait domains predicted more variance than SII-PDs and demonstrated better model fit and more predictive power for three of the criterion variables. Similarly, the AMPD domains predicted a significant but modest incremental increase in variance over that of the SII-PDs for three of the criterion variables. We conclude that more work needs to be done to improve the AMPD, particularly in the assessment of externalizing psychopathology as it relates to clinical dysfunction. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
在这项研究中,我们比较了精神病门诊患者样本(n=185)中人格障碍第二部分(SII-PD)的增量预测能力与替代人格障碍模型(AMPD)第三部分特质领域。为此,我们进行了一系列层次回归分析,其中 SII-PD 的 10 种和 AMPD 的 5 种特质领域作为预测变量,5 个临床功能障碍领域作为标准变量。每个标准变量都测试了两种模型。在模型 A 中,首先输入 10 个 PD,然后输入特质领域;在模型 B 中,这些预测器的块输入顺序相反。由于 AMPD 旨在解决 SII-PD 的缺点,因此我们假设,与 SII-PD 相比,AMPD 特质领域将通过以下方式表现出更大的预测能力:(a)当首先输入模型时,与 SII-PD 相比,对每个标准变量的总体方差解释更多;(b)当块输入第二时,比 SII-PD 解释更多的增量方差。这些假设得到了部分支持。总体而言,AMPD 特质领域比 SII-PD 预测更多的方差,并且对三个标准变量的模型拟合度更好,预测能力更强。同样,AMPD 领域对三个标准变量的方差预测比 SII-PD 有显著但适度的增量增加。我们得出结论,需要做更多的工作来改进 AMPD,特别是在评估与临床功能障碍相关的外化精神病理学方面。(PsycInfo 数据库记录(c)2024 APA,保留所有权利)。