This paper is in the following e-collection/theme issue:

Editorial (49) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (788) mHealth for Data Collection and Research (914) Protocols for Public Health Research and Surveillance (58) JHU Theme Issue (2017): Use of mobile technologies for national-scale population surveys (Guest Editors: Rosskam, Hyder) (10) Health Services in Resource-Poor Settings and LMICs (372)

Published on in Vol 19, No 5 (2017): May

Using mHealth to Predict Noncommunicable Diseases: A Public Health Opportunity for Low- and Middle-Income Countries

Using mHealth to Predict Noncommunicable Diseases: A Public Health Opportunity for Low- and Middle-Income Countries

Using mHealth to Predict Noncommunicable Diseases: A Public Health Opportunity for Low- and Middle-Income Countries

Authors of this article:

Ellen Rosskam1, 2 Author Orcid Image ;   Adnan A Hyder3, 4 Author Orcid Image
Article Authors Cited by (3) Tweetations (56) Metrics

Journals

  1. Kamal A, Khalid W, Zulfiqar M, Muqeet A, Zaidi F, Gowani A, Virani S. The potential of m-Health-based interventions to improve medication literacy and adherence in non-communicable diseases in Pakistan. International Journal of Stroke 2019;14(3):NP8 View
  2. Lamanna C, Hachhethu K, Chesterman S, Singhal G, Mwongela B, Ng’endo M, Passeri S, Farhikhtah A, Kadiyala S, Bauer J, Rosenstock T, West B. Strengths and limitations of computer assisted telephone interviews (CATI) for nutrition data collection in rural Kenya. PLOS ONE 2019;14(1):e0210050 View
  3. Zhang S, Hu C, Guo Y, Wang X, Meng Y. Polyphenols in fermented apple juice: Beneficial effects on human health. Journal of Functional Foods 2021;76:104294 View