在数字时代的COVID-19大流行期间预测信息过载的因素:长度研究
Hiroko Okada1, Tsuyoshi Okuhara1, Takahiro Kiuchi1
1Department of Health Communication, Schoolf of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Interactive journal of medical research
|October 30, 2025
概括
流行病健康信息过载影响年轻男性,健康素养较低,社交媒体使用量较高. 提高关键信息解释技能可以减轻未来的信息流行病.
科学领域:
- 公共卫生 公共卫生
- 卫生沟通 卫生沟通
- 信息科学 信息科学 信息科学
背景情况:
- 人类有限的信息处理能力受到疫情期间庞大而不确定的健康信息的挑战.
- 在COVID-19大流行期间感知到的信息过载阻碍了适当的预防性行为采用.
研究的目的:
- 识别个人特征,能力和媒体关注,预测大流行期间信息过载的感知.
- 了解在公共卫生危机中导致信息过载的因素.
主要方法:
- 一项基于网络的纵向调查对784名日本居民进行了两次时间点 (2020年8月和2021年8月) 的调查.
- 测量了社会人口统计数据,健康素养 (HL),关注各种信息道和感知到的信息过载.
- 层次的多重回归分析确定了信息过载的预测因素.
主要成果:
- 年轻的年龄,男性性别和较低的健康素养 (HL) 是信息过载的重要预测因素.
- 对电视新闻的关注减少,对社交媒体的关注增加与信息过载的增加有关.
- 这些因素预测了大流行后一年的信息过载.
结论:
- 公共卫生沟通人员必须提供简洁,易于理解的信息,特别是对于易受信息过载影响的人群.
- 高的社交媒体参与度可能会加剧信息过载,而高的HL可以减少认知负载.
- 发展关键健康信息解释技能对于疫情准备和减轻未来的信息流行病至关重要.
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