Customizable, scalable and reliable community-based mobile health interventions
| Autor: | Maria J. Brunette, Xinwen Fu, Benyuan Liu, Bhanu Kaushik |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
medicine.medical_specialty
Knowledge management business.industry Computer science Public health Psychological intervention Community-based participatory research Millennium Development Goals Underserved Population Information and Communications Technology Scale (social sciences) medicine business mHealth |
| Zdroj: | MobileHealth@MobiHoc |
| DOI: | 10.1145/2633651.2633659 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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