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Development and Implementation of Culturally Tailored Offline Mobile Health Surveys
BACKGROUND: In low and middle income countries (LMICs), and other areas with low resources and unreliable access to the Internet, understanding the emerging best practices for the implementation of new mobile health (mHealth) technologies is needed for efficient and secure data management and for in...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911512/ https://www.ncbi.nlm.nih.gov/pubmed/27256208 http://dx.doi.org/10.2196/publichealth.5408 |
Sumario: | BACKGROUND: In low and middle income countries (LMICs), and other areas with low resources and unreliable access to the Internet, understanding the emerging best practices for the implementation of new mobile health (mHealth) technologies is needed for efficient and secure data management and for informing public health researchers. Innovations in mHealth technology can improve on previous methods, and dissemination of project development details and lessons learned during implementation are needed to provide lessons learned to stakeholders in both the United States and LMIC settings. OBJECTIVE: The aims of this paper are to share implementation strategies and lessons learned from the development and implementation stages of two survey research projects using offline mobile technology, and to inform and prepare public health researchers and practitioners to implement new mobile technologies in survey research projects in LMICs. METHODS: In 2015, two survey research projects were developed and piloted in Puerto Rico and pre-tested in Costa Rica to collect face-to-face data, get formative evaluation feedback, and to test the feasibility of an offline mobile data collection process. Fieldwork in each setting involved survey development, back translation with cultural tailoring, ethical review and approvals, data collector training, and piloting survey implementation on mobile tablets. RESULTS: Critical processes and workflows for survey research projects in low resource settings were identified and implemented. This included developing a secure mobile data platform tailored to each survey, establishing user accessibility, and training and eliciting feedback from data collectors and on-site LMIC project partners. CONCLUSIONS: Formative and process evaluation strategies are necessary and useful for the development and implementation of survey research projects using emerging mHealth technologies in LMICs and other low resource settings. Lessons learned include: (1) plan institutional review board (IRB) approvals in multiple countries carefully to allow for development, implementation, and feedback, (2) in addition to testing the content of survey instruments, allow time and consideration for testing the use of novel mHealth technology (hardware and software), (3) incorporate training for and feedback from project staff, LMIC partner staff, and research participants, and (4) change methods accordingly, including content, as mHealth technology usage influences and is influenced by the content and structure of the survey instrument. Lessons learned from early phases of LMIC research projects using emerging mHealth technologies are critical for informing subsequent research methods and study designs. |
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