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

JHU Theme Issue (2017): Use of mobile technologies for national-scale population surveys (Guest Editors: Rosskam, Hyder) (10) Policy and Policy Proposals (115) Mobile Health (mhealth) (2777) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (792) mHealth for Data Collection and Research (917) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (523) Protocols for Public Health Research and Surveillance (58) Cross-Sectional Studies in Public Health (210) Health Services in Resource-Poor Settings and LMICs (376) Validity, Reliability, and Bias (89)

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

Health Surveys Using Mobile Phones in Developing Countries: Automated Active Strata Monitoring and Other Statistical Considerations for Improving Precision and Reducing Biases

Health Surveys Using Mobile Phones in Developing Countries: Automated Active Strata Monitoring and Other Statistical Considerations for Improving Precision and Reducing Biases

Health Surveys Using Mobile Phones in Developing Countries: Automated Active Strata Monitoring and Other Statistical Considerations for Improving Precision and Reducing Biases

Authors of this article:

Alain Labrique1 Author Orcid Image ;   Emily Blynn1 Author Orcid Image ;   Saifuddin Ahmed2 Author Orcid Image ;   Dustin Gibson1 Author Orcid Image ;   George Pariyo1 Author Orcid Image ;   Adnan A Hyder1 Author Orcid Image
Article Authors Cited by (29) Tweetations (5) Metrics

Journals

  1. Hyder A, Wosu A, Gibson D, Labrique A, Ali J, Pariyo G. Noncommunicable Disease Risk Factors and Mobile Phones: A Proposed Research Agenda. Journal of Medical Internet Research 2017;19(5):e133 View
  2. Gibson D, Pereira A, Farrenkopf B, Labrique A, Pariyo G, Hyder A. Mobile Phone Surveys for Collecting Population-Level Estimates in Low- and Middle-Income Countries: A Literature Review. Journal of Medical Internet Research 2017;19(5):e139 View
  3. Greenleaf A, Gadiaga A, Guiella G, Turke S, Battle N, Ahmed S, Moreau C, Ngure K. Comparability of modern contraceptive use estimates between a face-to-face survey and a cellphone survey among women in Burkina Faso. PLOS ONE 2020;15(5):e0231819 View
  4. Torres-Quintero A, Vega A, Gibson D, Rodriguez-Patarroyo M, Puerto S, Pariyo G, Ali J, Hyder A, Labrique A, Selig H, Peñaloza R, Vecino-Ortiz A. Adaptation of a mobile phone health survey for risk factors for noncommunicable diseases in Colombia: a qualitative study. Global Health Action 2020;13(1):1809841 View
  5. Slater H, Campbell J, Stinson J, Burley M, Briggs A. End User and Implementer Experiences of mHealth Technologies for Noncommunicable Chronic Disease Management in Young Adults: Systematic Review. Journal of Medical Internet Research 2017;19(12):e406 View
  6. Ali J, Labrique A, Gionfriddo K, Pariyo G, Gibson D, Pratt B, Deutsch-Feldman M, Hyder A. Ethics Considerations in Global Mobile Phone-Based Surveys of Noncommunicable Diseases: A Conceptual Exploration. Journal of Medical Internet Research 2017;19(5):e110 View
  7. Jones L, Ballon P. Tracking changes in resilience and recovery after natural hazards: Insights from a high-frequency mobile-phone panel survey. Global Environmental Change 2020;62:102053 View
  8. Lau C, Lombaard A, Baker M, Eyerman J, Thalji L. How Representative Are SMS Surveys in Africa? Experimental Evidence From Four Countries. International Journal of Public Opinion Research 2019;31(2):309 View
  9. Pariyo G, Greenleaf A, Gibson D, Ali J, Selig H, Labrique A, Al Kibria G, Khan I, Masanja H, Flora M, Ahmed S, Hyder A, Maulik P. Does mobile phone survey method matter? Reliability of computer-assisted telephone interviews and interactive voice response non-communicable diseases risk factor surveys in low and middle income countries. PLOS ONE 2019;14(4):e0214450 View
  10. Pariyo G, Wosu A, Gibson D, Labrique A, Ali J, Hyder A. Moving the Agenda on Noncommunicable Diseases: Policy Implications of Mobile Phone Surveys in Low and Middle-Income Countries. Journal of Medical Internet Research 2017;19(5):e115 View
  11. Rosskam E, Hyder A. Using mHealth to Predict Noncommunicable Diseases: A Public Health Opportunity for Low- and Middle-Income Countries. Journal of Medical Internet Research 2017;19(5):e129 View
  12. Clipman S, Wesolowski A, Gibson D, Agarwal S, Lambrou A, Kirk G, Labrique A, Mehta S, Solomon S. Rapid Real-time Tracking of Nonpharmaceutical Interventions and Their Association With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity: The Coronavirus Disease 2019 (COVID-19) Pandemic Pulse Study. Clinical Infectious Diseases 2021;73(7):e1822 View
  13. Hensen B, Mackworth-Young C, Simwinga M, Abdelmagid N, Banda J, Mavodza C, Doyle A, Bonell C, Weiss H. Remote data collection for public health research in a COVID-19 era: ethical implications, challenges and opportunities. Health Policy and Planning 2021;36(3):360 View
  14. Vecino-Ortiz A, Nagarajan M, Katumba K, Akhter S, Tweheyo R, Gibson D, Ali J, Rutebemberwa E, Khan I, Labrique A, Pariyo G. A cost study for mobile phone health surveys using interactive voice response for assessing risk factors of noncommunicable diseases. Population Health Metrics 2021;19(1) View
  15. Suich H, Yap M, Pham T. Coverage bias: the impact of eligibility constraints on mobile phone-based sampling and data collection. International Journal of Social Research Methodology 2022;25(6):849 View
  16. Greenleaf A, Mwima G, Lethoko M, Conkling M, Keefer G, Chang C, McLeod N, Maruyama H, Chen Q, Farley S, Low A. Participatory Surveillance of COVID-19 in Lesotho via Weekly Calls: Protocol for Cell Phone Data Collection. JMIR Research Protocols 2021;10(9):e31236 View
  17. Berry I, Mangtani P, Rahman M, Khan I, Sarkar S, Naureen T, Greer A, Morris S, Fisman D, Flora M. Population Health Surveillance Using Mobile Phone Surveys in Low- and Middle-Income Countries: Methodology and Sample Representativeness of a Cross-sectional Survey of Live Poultry Exposure in Bangladesh. JMIR Public Health and Surveillance 2021;7(11):e29020 View
  18. Gibson D, Wosu A, Pariyo G, Ahmed S, Ali J, Labrique A, Khan I, Rutebemberwa E, Flora M, Hyder A. Effect of airtime incentives on response and cooperation rates in non-communicable disease interactive voice response surveys: randomised controlled trials in Bangladesh and Uganda. BMJ Global Health 2019;4(5):e001604 View
  19. Gibson D, Kibria G, Pariyo G, Ahmed S, Ali J, Labrique A, Khan I, Rutebemberwa E, Flora M, Hyder A. Promised and Lottery Airtime Incentives to Improve Interactive Voice Response Survey Participation Among Adults in Bangladesh and Uganda: Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(5):e36943 View
  20. Chasukwa M, Choko A, Muthema F, Nkhalamba M, Saikolo J, Tlhajoane M, Reniers G, Dulani B, Helleringer S, Hall-Clifford R. Collecting mortality data via mobile phone surveys: A non-inferiority randomized trial in Malawi. PLOS Global Public Health 2022;2(8):e0000852 View
  21. Worges M, Kamala B, Yukich J, Chacky F, Lazaro S, Dismas C, Aroun S, Ibrahim R, Khamis M, Gitanya M, Mwingizi D, Metcalfe H, Bantanuka W, Deku S, Dadi D, Serbantez N, Loll D, Koenker H. Estimation of bed net coverage indicators in Tanzania using mobile phone surveys: a comparison of sampling approaches. Malaria Journal 2022;21(1) View
  22. Ng A, Mohan D, Shah N, Scott K, Ummer O, Chamberlain S, Bhatnagar A, Dhar D, Agarwal S, Ved R, LeFevre A. Assessing the reliability of phone surveys to measure reproductive, maternal and child health knowledge among pregnant women in rural India: a feasibility study. BMJ Open 2022;12(3):e056076 View
  23. Maliwichi P, Mthoko H, Chigona W, Mburu C, Densmore M. Does mobile phone ownership matter? Insights on engagement in mHealth and e-government interventions from Southern Africa. International Journal of Health Promotion and Education 2021:1 View
  24. Pariyo G, Meghani A, Gibson D, Ali J, Labrique A, Khan I, Kibria G, Masanja H, Hyder A, Ahmed S. Effect of the Data Collection Method on Mobile Phone Survey Participation in Bangladesh and Tanzania: Secondary Analyses of a Randomized Crossover Trial. JMIR Formative Research 2023;7:e38774 View
  25. Guzman-Tordecilla D, Vecino-Ortiz A, Torres-Quintero A, Solorzano-Barrera C, Ali J, Peñaloza-Quintero R, Ahmed S, Pariyo G, Maniar V, Gibson D. Examination of the demographic representativeness of a cross-sectional mobile phone survey in collecting health data in Colombia using random digit dialling. BMJ Open 2023;13(6):e073647 View
  26. Ramesh R, Oswald W, Israel G, Aruldas K, Galagan S, Legge H, Puthupalayam Kaliappan S, Walson J, Halliday K, Ajjampur S. Representativeness of a mobile phone-based coverage evaluation survey following mass drug administration for soil-transmitted helminths: a comparison of participation between two cross-sectional surveys. BMJ Open 2023;13(10):e070077 View
  27. Kibria G, Ahmed S, Khan I, Fernández-Niño J, Vecino-Ortiz A, Ali J, Pariyo G, Kaufman M, Sen A, Basu S, Gibson D, Kajungu D. Developing digital tools for health surveys in low- and middle-income countries: Comparing findings of two mobile phone surveys with a nationally representative in-person survey in Bangladesh. PLOS Global Public Health 2023;3(7):e0002053 View
  28. Khan I, Shano S, Islam K, Shahnaz S, Al Kibria G, Pariyo G, Ali J, Gibson D, Rahman M. Understanding community perception and acceptability of interactive voice response survey method: findings from formative research in Bangladesh.. Oxford Open Digital Health 2023;1 View
  29. Mc Kittrick A, Kornhaber R, de Jong A, Allorto N, Vana L, Chong S, Haik J, Cleary M. The role of multiplatform messaging applications in burns care and rehabilitation: A systematic review. Burns 2024;50(6):1424 View