一项针对多层次数字干预的现场随机试验的研究协议,以减少孕产妇发病率和死亡率
Sydney S Kelpin1, Claire E Margerison2, Athena S McKay3
1Charles Stewart Mott Department of Public Health, Michigan State University, Flint, MI, USA.
medRxiv : the preprint server for health sciences
|November 24, 2025
概括
这项研究开发了一个数字干预措施,以减少密歇根州的与怀孕有关的死亡率和发病率 (PRAMM). 基于技术的方法旨在改善个人,支持系统,提供者和社区层面的孕产妇健康结果.
科学领域:
- 公共卫生 公共卫生
- 数字健康干预措施 数字健康干预措施
- 孕产妇健康 孕产妇健康
背景情况:
- 美国面临高怀孕相关死亡率和发病率 (PRAMM),特别是在农村地区和非西班牙裔黑人人口中.
- 超过80%的妊娠相关死亡是可以预防的,但目前的干预措施面临传播挑战.
- 技术提供了一个潜在的解决方案,以克服在提供孕产妇健康干预措施的障碍.
研究的目的:
- 开发一个多层次的数字干预,密歇根州健康的 (MI MOM) 计划,以减少PRAMM.
- 为了评估MI MOM干预的有效性,使用现场随机试验.
主要方法:
- MI MOM干预采用社区合作的方法,通过移动网络应用程序和短信向孕妇参与者及其支持系统提供内容.
- 医疗保健提供者每两周收到短信和/或传单,而社区卫生工作者 (CHW) 则可以通过安全的现场聊天来访问.
- 一个集群随机试验涉及密歇根州10家产前护理诊所的500名孕妇参与者,将在PRAMM结果和风险因素上比较干预和控制组.
主要成果:
- 该部分应在研究完成并获得结果后填写.
结论:
- 本研究旨在证明多层次数字干预的潜力,以显著减少与怀孕有关的死亡率和发病率.
- 预计这些发现将为改善高风险人群中的孕产妇健康结果提供可扩展的技术解决方案.
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