ImportanceDynamical 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.ObservationsEmerging 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 RelevanceThose 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.

中文翻译：

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精神疾病的动态系统观——实际意义

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、循环和混沌。有人建议，同样的理论可以用来解释精神疾病的性质和动态，这些疾病可能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。观察结果表明，情绪和行为的时间序列可用于使用目前在全球范围内用于监测的相同通用动态指标来监测患者的恢复力复杂系统崩溃的风险，例如热带雨林和气候系统的倾斜因素。生态学和气候科学中使用的其他动力系统工具开辟了推断患者个性化因果关系网的方法，这些网络可用于确定干预目标。同时，生态恢复的经验有助于理解短期干预措施偶尔取得的长期成功。结论和相关性这些观察结果虽然有希望，但引发了后续问题：如何最好地收集动态数据、推断信息丰富的时间尺度、构建机制模型以及衡量干预措施对复原力的影响。如果做得好，监测复原力以告知适时的干预措施可能会被纳入到一些方法中，使患者在应对管理其复原力和知道何时寻求专业帮助的终生挑战中发挥积极作用。