Enhancing Public Response to Meteorological Disaster Warnings: A Perspective from the IDEA Model
Anying Chen, J Liu, Z G Zhu, Jun Hu
Jinan University Beijing Normal University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Early warning systems serve as a critical component in the emergency management of meteorological disasters, offering vital lead time for both the public and relevant agencies to implement preventive measures through the timely dissemination of early warning information. However, recent years have witnessed frequent instances where early warnings fail to elicit appropriate risk response behaviors, leading to missed opportunities for disaster mitigation and tragic outcomes. To enhance public comprehension of early warning information and promote proactive behaviors, this study employed a quasi-experimental questionnaire design to examine the effects of varying information content and presentation forms on public risk perception and protective behavioral intentions based on the classic IDEA (internalization, distribution, explanation, and action) model. The results indicate that, for textual warnings, messages incorporating “internalization” and “action” elements significantly improve risk perception and protective behavioral intentions compared to those containing only “explanation” elements. In contrast, video-based warnings featuring “explanation” elements enhance risk perception, whereas images or videos emphasizing “internalization” or “action” elements exhibit either negligible or even adverse effects on public risk perception and behavioral intentions. This study validated and extended the applicability and theoretical foundations of the IDEA model in non-textual contexts, offering insights for the advancement of disaster warning theory. Furthermore, the article provides policy-relevant recommendations for optimizing meteorological disaster warning strategies, ultimately contributing to the enhancement of societal disaster resilience and emergency response capabilities.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
社会科学Disaster Management and Resilience
Public Relations and Crisis Communication · Risk Perception and Management
参考文献 47
此处列出前 3 条