Law enforcement officer naturalistic decision-making in high-stress conditions

S. Dailey, Lauren N.P. Campbell, Justin Ramsdell
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Abstract

PurposeThis exploratory study aimed to investigate law enforcement officers’ decision-making processes in high-stress scenarios, exploring variations based on experience and how cognitive demands influence officer decision-making processes.Design/methodology/approachEmploying a naturalistic decision-making approach and macrocognitive framework, the study utilizes scenario-based virtual reality simulations and qualitative interviews to examine the decision-making processes of law enforcement officers in high-stress policing contexts.FindingsThematic coding of interview data from twelve LEOs immediately following a high-stress virtual reality task revealed differences in decision-making processes and cognitive demands between novice and expert officers. Findings also revealed differences in the type of cognitive demands experienced by officers at key points in the simulated scenario.Originality/valueThe authors offer theoretical and practical contributions toward an increased understanding of officer decision-making, factors and conditions that impact LEO decisions and potential mitigation strategies that law enforcement organizations may leverage to improve officer decision-making in high-stress contexts.
执法人员在高压力条件下的自然决策
目的这项探索性研究旨在调查执法人员在高压力情景下的决策过程,探索基于经验的变化以及认知需求如何影响执法人员的决策过程。本研究采用自然决策方法和宏观认知框架,利用基于情景的虚拟现实模拟和定性访谈来研究执法人员在高压力警务环境下的决策过程。研究结果对 12 名执法人员在高压力虚拟现实任务后立即进行的访谈数据进行了专题编码,发现新手和专家在决策过程和认知需求方面存在差异。研究结果还显示,在模拟场景的关键点上,警官们所经历的认知需求类型存在差异。原创性/价值作者在理论和实践方面做出了贡献,有助于加深对警官决策、影响执法人员决策的因素和条件以及潜在缓解策略的理解,执法机构可以利用这些策略来改善警官在高压力环境下的决策。
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