Developing mixed-latent-state-trait-models to analyse the temporal characteristics of affect and self-esteem in borderline personality disorder

开发混合潜在状态特质模型来分析边缘性人格障碍的情感和自尊的时间特征

• 批准号: 313940587
• 负责人: Professor Dr. Ulrich Ebner-Priemer
• 金额: --
• 依托单位: Institut für Sport und Sportwissenschaft (IfSS)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/313940587?language=en
• 关键词: Developing; mixed; latent; state; trait

Affective instability is hypothesized to be the core pathology in patients with borderline personality disorder (BPD) and the ICD-10 even lists BPD under the category of emotionally unstable personality disorders. Surprisingly, recent work using e-diaries to assess affect over time did not reveal affective instability as a disorder-specific mechanism, as other disorders did impress by similar instability. Accordingly, it has been hypothesized that statically modeling the dynamic interplay between affect and self-esteem is necessary to discriminate between transdiagnostic and disorder-specific mechanisms. In more details, to better understand affective instability in daily life in patients with BPD we have to dynamically model affect and self-esteem over time, taking additionally into account affect-changing events, reactivity to these events, as well as specific affect regulation mechanisms, like self-mutilating behavior. Therefore statistical models are necessary which allow: a) decomposing random from true variability, b) modeling multiple subcomponents of affective processes at the same time, c) modeling between-subject and group-specific differences in affective response and regulation processes, as well as d) enabling estimations on psychometric properties and the appropriateness of the sampling strategies used.Accordingly our grant proposal follows two main strategies: The clinical goal is to simultaneously model the dynamical characteristics of affect and self-esteem including their interplay and specific regulation mechanisms. We will use electronic diaries to assess affect, self-esteem, and specific regulation strategies in everyday life in 125 patients with BPD, 125 patients with anxiety disorders, as well as 125 healthy controls. We do hypothesize that the covariation of affect and self-esteem is specific for BPD as well as that self-mutilating behavior is predicted by a synchronous increasing negative affect and decreasing self-esteem. As current statistical models are limited for this kind of analyses, our second main goal is to develop and systematically test advanced statistical models. In details, we will expand ordinary mixed-latent-state-trait-models to multigroup-multitrait-mixed-autoregressive-latent-state-trait-growth-curve-models. Beyond that, we will use Monte Carlo simulations studies to investigate under which preconditions these models are fruitful usable in ambulatory assessment research.

情感不稳定被假设为边缘型人格障碍（BPD）患者的核心病理，ICD-10甚至将BPD列为情感不稳定型人格障碍。令人惊讶的是，最近的工作使用电子日记来评估随着时间的推移的影响，并没有揭示情感不稳定作为一个特定的机制，因为其他疾病确实留下了类似的不稳定。因此，有人假设，静态建模的动态相互作用之间的影响和自尊是必要的，以区分transdiagnosis和疾病的具体机制。更详细地说，为了更好地理解BPD患者日常生活中的情感不稳定性，我们必须随着时间的推移动态地模拟情感和自尊，同时考虑到情感改变事件，对这些事件的反应，以及特定的情感调节机制，如自残行为。因此，统计模型是必要的，它允许：a）从真实的变异性中分解随机，B）同时对情感过程的多个子成分建模，c）对情感反应和调节过程中的受试者和群体特异性差异建模，以及d）对心理测量特性和所使用的抽样策略的适当性进行估计。因此，我们的资助提案遵循两个主要策略：临床目标是同时模拟情感和自尊的动态特征，包括它们的相互作用和特定的调节机制。我们将使用电子日记来评估125名BPD患者，125名焦虑症患者以及125名健康对照者的日常生活中的情感，自尊和特定的调节策略。我们假设，影响和自尊的协变是特定的BPD，以及自残行为的预测同步增加的负面影响和降低自尊。由于目前的统计模型对于这类分析是有限的，我们的第二个主要目标是开发和系统地测试先进的统计模型。具体来说，我们将普通的混合潜伏状态-特质模型扩展为多组多特质混合潜伏状态-特质增长曲线模型。除此之外，我们将使用蒙特卡罗模拟研究，调查在哪些前提下，这些模型是富有成效的可用于流动评估研究。