Department of Psychology, Rutgers, The State University of New Jersey.
Department of Computer Science, Aalto University.
Personal Disord. 2021 Jan;12(1):39-50. doi: 10.1037/per0000398. Epub 2020 Apr 16.
Theoretical models of personality disorders can be complex and multifaceted, making it difficult to validate such models in a comprehensive, empirical fashion. One such model of borderline personality disorder (BPD) is the emotional cascade model (Selby & Joiner, 2009), which has garnered empirical support in piecemeal fashion but has not been examined in a gestalt fashion. One way to test comprehensive models of personality pathology is with Temporal Bayesian Network (TBN) modeling, in which the relations between multiple subcomponents of a model can be specified and examined over a dynamic time frame, allowing for the modeling of positive feedback processes in addition to comprehensive model utility. In this study, we applied TBN modeling to examine the emotional cascade model in a sample of adolescents and young adults who actively self-injure, including those with BPD. TBN modeling was applied to ecological momentary assessment data provided via participant smartphone assessments for a period of 2 weeks. TBN analysis suggested that the emotional cascade model has considerable predictive utility, demonstrating substantial accuracy in predicting BPD diagnosis (with accuracy estimates around 90%) and momentary prediction of rumination, negative emotion, and dysregulated behaviors (with accuracy estimates consistently above 70% and reaching up to 100%, depending on the level of momentary prediction specificity). These findings provide support and validity to the notion that BPD may emerge from a dynamic interplay between emotional cascades and dysregulated behaviors. Implications of TBN modeling of BPD and personality disorders, in general, are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
人格障碍的理论模型可能非常复杂和多面，因此很难以全面、经验的方式验证这些模型。边缘型人格障碍（BPD）的一种理论模型是情绪级联模型（Selby & Joiner, 2009），该模型已逐步得到经验支持，但尚未以整体方式进行检验。测试人格病理学综合模型的一种方法是使用时间贝叶斯网络（TBN）建模，在该模型中可以指定模型多个子组件之间的关系，并在动态时间框架内进行检查，从而可以对积极反馈过程进行建模，以及综合模型的实用性。在这项研究中，我们应用 TBN 建模来检验活跃的自我伤害的青少年和年轻人样本中的情绪级联模型，包括那些患有 BPD 的患者。TBN 建模应用于通过参与者智能手机评估在 2 周的时间内提供的生态瞬时评估数据。TBN 分析表明，情绪级联模型具有相当大的预测实用性，在预测 BPD 诊断方面表现出相当高的准确性（准确性估计值约为 90%），并且对反刍、负面情绪和失调行为进行了瞬时预测（准确性估计值始终高于 70%，取决于瞬时预测特异性的水平，最高可达 100%）。这些发现为 BPD 可能是情绪级联和失调行为之间的动态相互作用产生的观点提供了支持和有效性。总体而言，讨论了 TBN 对 BPD 和人格障碍的建模的意义。（PsycInfo 数据库记录（c）2021 APA，保留所有权利）。
