可定制、可扩展和可靠的基于社区的流动卫生干预措施

Bhanu Kaushik, M. Brunette, Xinwen Fu, Benyuan Liu
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引用次数: 4

摘要

根据联合国2000年制定的千年发展目标,基于社区的参与性研究(CBPR)和移动医疗(mHealth)已被证明是在病人监测、紧急护理和社区赋权方面取得进展的重要工具。在缺乏其他信息和通信技术媒体的情况下,移动电话在低收入、农村和服务不足人口中的迅速普及引起了公共卫生部门研究人员的兴趣。利用移动通信为公共卫生建立了一个可靠和有效的社会技术生态系统。基于社区的参与式研究(CBPR)方法涉及学术研究人员和社区合作伙伴合作开发社会和计算模型,其目标是建立沟通、信任和能力,最终目标是增加社区对研究过程的参与。CBPR是一种合作研究方法,所有合作伙伴公平参与研究过程,以改善目标社区。在本文中,我们提出了进行移动医疗辅助社区干预的概念和实施架构。该框架允许CBPR合作伙伴定制系统,并围绕场所、技术、地理、规模以及社会和文化方面设计干预措施。我们还提出了针对秘鲁安第斯地区服务不足人口的产前监测的计划干预设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Customizable, scalable and reliable community-based mobile health interventions
In pursuance of the Millennium Development Goals (MDGs) set by United Nations in 2000, both Community Based Participatory Research (CBPR) and Mobile Health (mHealth) have proved to be a great tool for advancements in patient monitoring, emergency care and community empowerment. Rapid proliferation of mobile telephony in low income, rural and underserved populations in the absence of other information and communication technology media have prompted the interests of researchers in public health sector. Exploiting mobile communication has resulted in formulation of a dependable and effective socio-technical ecosystem for public health. Whereas, involving academic researchers and community partners to collaborate and develop social and computational models, Community Based Participatory Research (CBPR) approach targets building communication, trust and capacity, with the final goal of increasing community participation in the research process. CBPR is a collaborative approach to research which equitably involves all partners in the research process for betterment of the targeted community. In this paper we present a conceptual and implementation architecture for conducting mHealth assisted community-based interventions. The framework allows CBPR partners to customize the system and design interventions around locale, technology, geographic, scale, and nonetheless social and cultural aspects. We also present the design of our planned intervention addressing prenatal monitoring of underserved populations in the Andean regions of Peru.
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