Network Psychiatry: Using Network Science to Advance Our Understanding of Post-Bereavement Psychopathology

摘要 丧亲之痛是一种强大而普遍的压力源。超过1000万人经历了他们所爱的人的死亡 在美国，每年一次，增加了许多精神疾病的风险，包括复杂的 悲伤尽管这些疾病带来了巨大的负担，但我们对其性质和病因知之甚少 因此，我们预测、预防和治疗丧亲后精神病理学的能力有限。 最近，我和我的同事提出，与丧亲有关的精神障碍，如复杂的悲伤， 最好理解为相互强化症状的复杂系统。在两项研究中，我们使用了 网络科学研究复杂悲伤症状网络的结构。这些研究使我们能够 确定哪些症状是复杂的悲伤网络的最核心，并提供了一些最早的 有证据表明，理解网络拓扑结构可以帮助我们理解复杂的悲伤过程。 我获得这个职业发展奖的核心目标是成为网络科学方面的专家， 网络科学的工具来研究复杂的悲伤作为一个复杂的心理生物学系统。拟议 研究将通过四个关键创新建立在我们以前的研究基础上。首先，我们将使用密集型 时间序列数据，以估计每个患者的个体内网络结构，提供有关 这个人体内独特的心理生物学过程其次，我们将重点分析 与丧亲相关研究领域标准相一致的复杂悲伤综合征的要素 （RDoC）结构，将我们的分析与更广泛的努力联系起来，以了解这些单独的组成部分， 精神病理学第三，我们将把生物分析单位纳入我们的个体内部网络， 研究生理反应的个体差异如何导致复杂的悲伤综合征。 第四，我们将使用个体内网络参数来预测复杂悲伤的过程。 本研究采用的方法是创新的，因为它采用了一个新颖的概念框架， 理解和研究精神疾病，这是植根于迅速发展的多学科领域， 网络科学这是有意义的，因为它将阐明病人的具体心理生物学机制 导致与丧亲有关的精神障碍的发展和发作。此外，它将引入 新的工具进入精神病学领域，使我们能够更好地预测，预防和治疗精神病理学， 个体患者的水平，使我们更接近精神病学的精确医学方法的目标。

ABSTRACT Bereavement is a potent and ubiquitous stressor. More than 10 million individuals experience the death a loved one each year in the United States, increasing risk for numerous psychiatric disorders, including complicated grief. Despite the substantial burden conferred by these disorders, we know little about their nature and etiology and, consequently, are limited in our ability to predict, prevent, and treat post-bereavement psychopathology. Recently, my colleagues and I proposed that bereavement-related mental disorders, such as complicated grief, are best understood as complex systems of mutually reinforcing symptoms. In two studies, we used the tools of network science to study the structure of the complicated grief symptom network. These studies allowed us to identify which symptoms are most central to the complicated grief network and provided some of the earliest evidence that understanding network topology can inform our understanding of the course of complicated grief. My core aim for this career development award is to become an expert in network science and to use the tools of network science to study complicated grief as a complex psychobiological system. The proposed research study will build on our previous research through four critical innovations. First, we will use intensive time-series data to estimate the intra-individual network structure for each patient, providing information about the unique psychobiological processes operating within that individual. Second, we will focus our analyses on the elements of the complicated grief syndrome that align with bereavement-related Research Domain Criteria (RDoC) constructs, linking our analyses to the broader effort to understand these individual components of psychopathology. Third, we will incorporate biological units of analysis into our intra-individual network and study how individual differences in physiological reactivity contribute to the complicated grief syndrome. Fourth, we will use intra-individual network parameters to predict the course of complicated grief over time. The approach taken in this study is innovative because it adopts a novel conceptual framework for understanding and studying psychiatric disorders that is rooted in the rapidly growing multi-disciplinary field of network science. It is significant because it will elucidate the patient-specific psychobiological mechanisms contributing to the development and onset of bereavement-related mental disorders. Moreover, it will introduce new tools into the field of psychiatry that will allow us to better predict, prevent, and treat psychopathology at the level of the individual patient, moving us closer to the aim of a precision medicine approach to psychiatry.