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在标准和基于影响的天气警报中,龙卷风避难所寻求意愿的时间折扣:一项众包实验。

Temporal discounting of tornado shelter-seeking intentions amidst standard and impact-based weather alerts: A crowdsourced experiment.

机构信息

Department of Applied Behavioral Science.

出版信息

J Exp Psychol Appl. 2020 Mar;26(1):16-25. doi: 10.1037/xap0000246. Epub 2019 Aug 26.

DOI:10.1037/xap0000246
PMID:31448936
Abstract

Tornadoes are atmospheric events capable of massive devastation, involving physical destruction and human casualties. Following the 2011 Joplin, MO tornado that claimed the lives of nearly 160 people, the National Weather Service and National Institute of Standards and Technology concluded that better warning systems would have saved lives. This conclusion prompted the creation of (IBW) messages that use explicit language to convey damage threats and potential outcomes. The current study examined the efficacy of impact-based warnings for evoking shelter-seeking intentions in a simulated tornado event. We stratified participants recruited through a crowdsourcing service into 1 of 4 simulated tornado warning conditions, varying with respect to the content and description (IBW) provided. Participants rated their likelihood of immediate shelter-seeking given increasing lead times to the potential tornado strike. Analyses indicated that participants receiving IBW maintained shelter-seeking most across increasing delays. Results suggest viable warning delivery at longer lead times when employing IBW, thereby providing more preparation while bypassing risks of delay-induced inaction. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

摘要

龙卷风是一种能够造成大规模破坏的大气事件,涉及物质破坏和人员伤亡。在 2011 年密苏里州乔普林的龙卷风夺走近 160 人生命之后,美国国家气象局和美国国家标准与技术研究院得出结论,更好的预警系统本可以拯救生命。这一结论促使他们创建了 (IBW) 信息,这些信息使用明确的语言来传达破坏威胁和潜在后果。本研究考察了基于影响的警报在模拟龙卷风事件中引发避难意图的效果。我们通过众包服务招募的参与者被分为 4 种模拟龙卷风预警条件之一,这些条件在提供的内容和描述 (IBW) 上有所不同。参与者根据潜在龙卷风袭击的提前时间,对立即寻求避难的可能性进行了评分。分析表明,在提前时间增加的情况下,收到 IBW 的参与者最能保持寻求避难的意愿。结果表明,在使用 IBW 时,可以在更长的提前时间内进行可行的警报传递,从而在避免因延迟而不采取行动的风险的同时提供更多的准备时间。(PsycINFO 数据库记录 (c) 2020 APA,保留所有权利)。

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