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利用基于社区的系统动态来了解非洲裔美国人社区的长期Covid差异:健康公平研究的一个模型

Chad R Evans¹, Melvin R Echols¹, D Martin²

¹Morehouse School of Medicine, Cardiovascular Research Institute, Atlanta, Georgia, USA.

Health expectations : an international journal of public participation in health care and health policy

|December 15, 2025

概括

基于社区的系统动力学 (CBSD) 研讨会有效地让非裔美国人社区了解长期的Covid差异. 这种方法为量身定制的公共卫生战略产生了可操作的见解,并增强了社区的性.

科学领域:

公共卫生公共卫生
健康差异在健康上的差异
社区参与社区参与

背景情况:

长期的Covid不成比例地影响了非洲裔美国人社区,加剧了现有的健康不平等.
传统的干预措施往往忽视了解决这些差异至关重要的系统因素和社区知识.
需要新的方法来捕捉社区对长期Covid生活的观点.

研究的目的:

探索基于社区的系统动力学 (CBSD) 研讨会在理解和解决非洲裔美国社区长期Covid差异方面的有效性.
为了开发有针对性的公共卫生干预措施,引发社区驱动的见解.

主要方法:

利用混合社区系统动力学 (CBSD) 研讨会,涉及受影响的个人,医疗保健专业人员和研究人员.
采用系统动态因果循环图来可视化长期Covid的复杂社会背景.
在所有研究阶段,从设计到解释,积极参与具有实践经验的个人.

主要成果:

在CBSD研讨会上,制作了视觉系统动态模型,说明了长期Covid的多方面的影响.
社区的洞察力确定了特定的卫生系统障碍,并为加强弹性制定了一项行动计划.
参与者的反确保了调查结果准确地反映了社区的观点和优先事项.

结论:

CBSD研讨会是有效的,可复制的社区参与和赋权解决健康差异的模式.
整合社区来源的知识和系统动态建模,可以提高长期Covid的公共卫生策略.
这种方法可以促进对复杂健康问题的社会文化背景的更深入的理解.

关键词:

基于社区的系统动力学.原因循环图表原因循环图组建模型的组建模型.卫生公平性健康公平性长时间的Covid.参与式研究参与式研究患者参与患者参与

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