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使用人工智能进行适应性疫苗信息的计划-做-研究-行动框架

Olivia A Stein¹, Neil Seeman²

¹Olivia A. Stein, is a global health professional with a background in digital health, bioethics and public health research. Olivia is currently a MDCM student in the Faculty of Medicine at McGill University.

Healthcare quarterly (Toronto, Ont.)

|October 14, 2025

概括

这项研究引入了一个人工智能驱动的计划-做-研究-行动框架,通过分析社交媒体和创建适应性消息来打击疫苗犹. 其目标是改善公共卫生沟通策略.

科学领域:

公共卫生公共卫生
人工智能的人工智能
卫生沟通健康沟通

背景情况:

计划-做-研究-行动 (PDSA) 周期是加强公共卫生计划的公认方法.
越来越多的疫苗犹对公共卫生倡议构成了重大挑战.
社交媒体平台对于理解公众情绪和传播信息至关重要.

研究的目的:

提出一个创新的人工智能 (AI) 支持的PDSA框架,适用于适应性疫苗信息传递.
利用社交媒体数据进行实时分析和消息改进.
通过动态的沟通策略来解决疫苗犹日益严重的问题.

主要方法:

进行了关于PDSA循环和AI在健康沟通中的应用的综合文献审查.
开发了一个新的AI-enabled PDSA框架,集成社交媒体数据分析.
使用Reddit的数据对框架进行了试点评估,以评估其可行性和有效性.

主要成果:

拟议的框架将AI整合到"计划"阶段的社交媒体话语分析中.
人工智能有助于为"完成"阶段创建量身定制的消息,旨在提高参与度.
"研究"和"行动"阶段涉及评估情绪和行为变化,以持续调整消息.

结论:

支持人工智能的PDSA框架为疫苗沟通提供了一个动态的方法,适应公众的情绪.
利用社交媒体数据和人工智能可以提高公共卫生信息的有效性,以打击犹.
这种适应性策略有可能不断改进疫苗传播活动.

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