Fried Eiko I, van Borkulo Claudia D, Cramer Angélique O J, Boschloo Lynn, Schoevers Robert A, Borsboom Denny
Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129-B, Room G0.28, 1001NK, Amsterdam, Netherlands.
Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Soc Psychiatry Psychiatr Epidemiol. 2017 Jan;52(1):1-10. doi: 10.1007/s00127-016-1319-z. Epub 2016 Dec 5.
The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years.
This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention.
Pertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality-a metric that measures how connected and clinically relevant a symptom is in a network-is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies.
We sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients.
精神病理学的网络视角将精神障碍理解为相互作用症状的复杂网络。尽管该框架最近才首次亮相,其概念基础始于2008年,实证基础始于2010年,但在过去几年中已受到相当多的关注和认可。
本文对2010年至2016年间发表的所有实证网络研究进行了综述,并根据三个主要主题进行了讨论:共病、预测和临床干预。
关于共病,网络方法提供了一个强大的新框架,用以解释为何某些障碍可能比其他障碍更常同时出现。在预测方面,研究一致发现,患有精神障碍者的症状网络呈现出与健康个体不同的特征,并且初步证据表明,健康人的网络在转变为紊乱状态之前会显示出预警信号。在干预方面,中心性——一种衡量症状在网络中的关联程度和临床相关性的指标——是研究最普遍的主题,并且大量研究表明,针对最核心的症状可能会提供新的治疗策略。
我们勾勒了网络方法在临床研究和方法学研究方面的未来方向,并得出结论,网络分析已产生重要见解,并且通过研究个体患者的网络结构可能为个性化医疗提供重要途径。