Ross Jared, Miller Lucas, Deuster Patricia A
J Spec Oper Med. 2018 Fall;18(3):86-91. doi: 10.55460/QU7U-8ICE.
Cognitive agility reflects the capacity of an individual to easily move back and forth between openness and focus. The concept is being translated into a tool to help train leaders to perform well in the "dynamic decision-making context." Cognitive agility training (CAT) has the potential to increase emotional intelligence by improving an individual's ability to toggle between highly focused states to levels of broad, outward awareness, which should enable dynamic decision-making and enhance personal communication skills. Special Operations Forces (SOF) Operators must work in rapidly evolving, complex environments embedded with multiple high-risk factors. Generally, success in these operational environments requires the ability to maintain highly focused states. However, SOF Operators must also be able to transition rapidly back to their roles within their families, where a more outwardly aware state is needed to allow flexibility in emotional responses. CAT addresses these seemingly conflicting requirements. Successful CAT must reflect the methodologies and culture already familiar within the SOF community (i.e., "live" scenario-based activities) to replicate challenges they may encounter when operationally deployed and when at home. This article provides an overview of cognitive agility, the potential benefits, applications that could be used for training SOF Operators to improve their cognitive agility to optimize performance, and sample training scenarios. The issue of what metrics to use is also discussed.
认知灵活性反映了个体在开放与专注之间轻松切换的能力。这一概念正被转化为一种工具，以帮助培训领导者在“动态决策环境”中表现出色。认知灵活性训练（CAT）有可能通过提高个体在高度专注状态与广泛的外部意识水平之间切换的能力来提升情商，这应能实现动态决策并增强个人沟通技巧。特种作战部队（SOF）的操作员必须在充满多种高风险因素的快速演变、复杂环境中工作。一般来说，在这些作战环境中取得成功需要具备保持高度专注状态的能力。然而，特种作战部队的操作员还必须能够迅速回归到家庭角色中，在家庭环境中需要更具外部意识的状态，以便在情感反应上具备灵活性。认知灵活性训练就能应对这些看似相互冲突的要求。成功的认知灵活性训练必须反映特种作战部队社区内已经熟悉的方法和文化（即基于“实战”场景的活动），以重现他们在作战部署和在家时可能遇到的挑战。本文概述了认知灵活性、潜在益处、可用于培训特种作战部队操作员以提高其认知灵活性从而优化表现的应用，以及示例训练场景。还讨论了使用何种指标的问题。
