University of Groningen,University Medical Center Groningen,Department of Psychiatrie,Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE),Groningen,The Netherlands.
Department of Mood Disorders,Parnassia Group,PsyQ,The Hague,The Netherlands.
Psychol Med. 2019 Feb;49(3):380-387. doi: 10.1017/S0033291718002064. Epub 2018 Aug 22.
Recently, there has been renewed interest in the application of assumptions from complex systems theory in the field of psychopathology. One assumption, with high clinical relevance, is that sudden transitions in symptoms may be anticipated by rising instability in the system, which can be detected with early warning signals (EWS). Empirical studies support the idea that this principle also applies to the field of psychopathology. The current manuscript discusses whether assumptions from complex systems theory can additionally be informative with respect to the specific symptom dimension in which such a transition will occur (e.g. whether a transition towards anxious, depressive or manic symptoms is most likely). From a complex systems perspective, both EWS measured in single symptom dynamics and network symptom dynamics at large are hypothesized to provide clues regarding the direction of the transition. Challenging research designs are needed to provide empirical validation of these hypotheses. These designs should be able to follow sudden transitions 'live' using frequent observations of symptoms within individuals and apply a transdiagnostic approach to psychopathology. If the assumptions proposed are supported by empirical studies then this will signify a large improvement in the possibility for personalized estimations of the course of psychiatric symptoms. Such information can be extremely useful for early intervention strategies aimed at preventing specific psychiatric problems.
最近,复杂系统理论在精神病理学领域的应用假设再次引起了人们的兴趣。其中一个具有高度临床相关性的假设是,系统的不稳定性上升可能预示着症状的突然转变,可以通过早期预警信号(EWS)来检测。实证研究支持这样一种观点,即这一原则也适用于精神病理学领域。本文讨论了复杂系统理论的假设是否可以提供更多关于发生这种转变的特定症状维度的信息(例如,向焦虑、抑郁或躁狂症状的转变最有可能发生)。从复杂系统的角度来看,无论是在单个症状动态中测量的 EWS,还是在整个网络症状动态中,都假设它们可以提供有关转变方向的线索。需要具有挑战性的研究设计来提供这些假设的经验验证。这些设计应该能够使用个体内症状的频繁观察来“实时”跟踪突然转变,并采用跨诊断的方法来研究精神病理学。如果所提出的假设得到实证研究的支持,那么这将大大提高对精神症状过程进行个性化估计的可能性。这种信息对于旨在预防特定精神问题的早期干预策略非常有用。