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精神障碍的动力系统观点——实际意义:综述

A Dynamical Systems View of Psychiatric Disorders-Practical Implications: A Review.

机构信息

Wageningen University, Wageningen, the Netherlands.

Amsterdam UMC, Amsterdam, the Netherlands.

出版信息

JAMA Psychiatry. 2024 Jun 1;81(6):624-630. doi: 10.1001/jamapsychiatry.2024.0228.

Abstract

IMPORTANCE

Dynamical systems theory is widely used to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. It has been suggested that the same theory may be used to explain the nature and dynamics of psychiatric disorders, which may come and go with symptoms changing over a lifetime. Here we review evidence for the practical applicability of this theory and its quantitative tools in psychiatry.

OBSERVATIONS

Emerging results suggest that time series of mood and behavior may be used to monitor the resilience of patients using the same generic dynamical indicators that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforest and tipping elements of the climate system. Other dynamical systems tools used in ecology and climate science open ways to infer personalized webs of causality for patients that may be used to identify targets for intervention. Meanwhile, experiences in ecological restoration help make sense of the occasional long-term success of short interventions.

CONCLUSIONS AND RELEVANCE

Those observations, while promising, evoke follow-up questions on how best to collect dynamic data, infer informative timescales, construct mechanistic models, and measure the effect of interventions on resilience. Done well, monitoring resilience to inform well-timed interventions may be integrated into approaches that give patients an active role in the lifelong challenge of managing their resilience and knowing when to seek professional help.

摘要

重要性

动力系统理论被广泛用于解释从气候到生态系统等复杂系统中的临界点、周期和混沌。有人认为,同样的理论也可以用来解释精神疾病的性质和动态,这些疾病可能会随着一生中症状的变化而出现和消失。在这里,我们回顾了该理论及其在精神病学中的定量工具的实际适用性的证据。

观察结果

新兴的研究结果表明,可以使用情绪和行为的时间序列来监测患者的恢复能力,使用的是与现在全球用于监测热带雨林和气候系统临界点等复杂系统崩溃风险的相同通用动力指标。生态和气候科学中使用的其他动力系统工具为患者推断个性化因果关系网络开辟了道路,这些网络可用于确定干预目标。与此同时,生态恢复的经验有助于理解短期干预偶尔取得长期成功的原因。

结论和相关性

这些观察结果虽然有希望,但引发了关于如何最好地收集动态数据、推断信息时间尺度、构建机械模型以及衡量干预对恢复力的影响的后续问题。如果做得好,监测恢复力以提供及时的干预措施,可能会被整合到让患者在管理自身恢复力和了解何时寻求专业帮助的终身挑战中发挥积极作用的方法中。

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