Noncommunicable Disease Risk Factors and Mobile Phones: A Proposed Research Agenda

Adnan A Hyder, Adaeze C Wosu, Dustin G Gibson, Alain B Labrique, Joseph Ali, George W Pariyo, Adnan A Hyder, Adaeze C Wosu, Dustin G Gibson, Alain B Labrique, Joseph Ali, George W Pariyo

Abstract

Noncommunicable diseases (NCDs) account for two-thirds of all deaths globally, with 75% of these occurring in low- and middle-income countries (LMICs). Many LMICs seek cost-effective methods to obtain timely and quality NCD risk factor data that could inform resource allocation, policy development, and assist evaluation of NCD trends over time. Over the last decade, there has been a proliferation of mobile phone ownership and access in LMICs, which, if properly harnessed, has great potential to support risk factor data collection. As a supplement to traditional face-to-face surveys, the ubiquity of phone ownership has made large proportions of most populations reachable through cellular networks. However, critical gaps remain in understanding the ways by which mobile phone surveys (MPS) could aid in collection of NCD data in LMICs. Specifically, limited information exists on the optimization of these surveys with regard to incentives and structure, comparative effectiveness of different MPS modalities, and key ethical, legal, and societal issues (ELSI) in the development, conduct, and analysis of these surveys in LMIC settings. We propose a research agenda that could address important knowledge gaps in optimizing MPS for the collection of NCD risk factor data in LMICs and provide an example of a multicountry project where elements of that agenda aim to be integrated over the next two years.

Keywords: mHealth; mobile phone; noncommunicable disease; research agenda; survey.

Conflict of interest statement

Conflicts of Interest: None declared.

©Adnan A Hyder, Adaeze C Wosu, Dustin G Gibson, Alain B Labrique, Joseph Ali, George W Pariyo. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.05.2017.

References

    1. Global status report on noncommunicable diseases 2014. Geneva, Switzerland: World Health Organization; 2014.
    1. Global action plan for the prevention and control of noncommunicable diseases 2013 - 2020. Geneva, Switzerland: World Health Organization; 2013.
    1. Alwan A, Maclean DR, Riley LM, d'Espaignet ET, Mathers CD, Stevens GA, Bettcher D. Monitoring and surveillance of chronic non-communicable diseases: progress and capacity in high-burden countries. Lancet. 2010 Nov 27;376(9755):1861–8. doi: 10.1016/S0140-6736(10)61853-3.
    1. Global status report on noncommunicable diseases 2010. Geneva, Switzerland: World Health Organization; 2011. Apr,
    1. Bloom D, Cafiero E, Jane-Llopis E, Abrahams-Gessel S, Bloom L, Fathima S, Feigl A, Gaziano T, Mowafi M, Pandya A, Prettner K, Rosenberg L, Seligman B, Stein A, Weinstein C. The global economic burden of noncommunicable diseases. Geneva, Switzerland: World Economic Forum; 2011.
    1. WHO. Geneva, Switzerland: World Health Organization; 2003. [2017-03-24]. STEPS: A framework for surveillance .
    1. NCD global monitoring framework: Ensuring progress on noncommunicable diseases in countries. Geneva, Switzerland: World Health Organization; 2013. [2017-03-16].
    1. mHealth: New horizons for health through mobile technologies. Geneva, Switzerland: World Health Organization; 2011. Jun 07,
    1. Mehl G, Labrique A. Prioritizing integrated mHealth strategies for universal health coverage. Science. 2014 Sep 12;345(6202):1284–7. doi: 10.1126/science.1258926.
    1. International Telecommunication Union. 2016. [2016-12-12]. Statistics .
    1. The World Bank. [2016-11-12]. Mobile cellular subscriptions (per 100 people) .
    1. Labrique AB, Vasudevan L, Kochi E, Fabricant R, Mehl G. mHealth innovations as health system strengthening tools: 12 common applications and a visual framework. Glob Health Sci Pract. 2013 Aug;1(2):160–71. doi: 10.9745/GHSP-D-13-00031.
    1. Brinkel J, Krämer A, Krumkamp R, May J, Fobil J. Mobile phone-based mHealth approaches for public health surveillance in sub-Saharan Africa: a systematic review. Int J Environ Res Public Health. 2014 Nov 12;11(11):11559–82. doi: 10.3390/ijerph111111559.
    1. Labrique A, Vasudevan L, Chang LW, Mehl G. H_pe for mHealth: more “y” or “o” on the horizon? Int J Med Inform. 2013 May;82(5):467–9. doi: 10.1016/j.ijmedinf.2012.11.016.
    1. The MAPS toolkit: mHealth assessment planning for scale. Geneva, Switzerland: World Health Organization; 2015.
    1. Ballivian A, Azevedo J, Durbin W. Using mobile phones for high-frequency data collection. In: Toninelli D, Pinter R, de Pedraza P, editors. Mobile Research Methods: Opportunities and challenges of mobile research methodologies. London, England: Ubiquity Press; 2015.
    1. Greenleaf A, Gibson DG, Khattar C, Labrique AB, Pariyo GW. Building the evidence base for remote data collection in low- and middle-income countries: comparing reliability and accuracy. J Med Internet Res. 2017;19(5):e140. doi: 10.2196/jmir.7331.
    1. Gibson DG, Pereira A, Farrenkopf BA, Labrique AB, Pariyo GW, Hyder AA. Mobile phone surveys for collecting population-level estimates in low- and middle-income countries: a literature review. J Med Internet Res. 2017;19(5):e139. doi: 10.2196/jmir.7428.
    1. Mahfoud Z, Ghandour L, Ghandour B, Mokdad A, Sibai A. Cell phone and face-to-face interview responses in population-based surveys: how do they compare? Field Methods. 2015;27(1):39–54.
    1. Higgs E, Goldberg A, Labrique A, Cook S, Schmid C, Cole C, Obregon R. Understanding the role of mHealth and other media interventions for behavior change to enhance child survival and development in low- and middle-income countries: an evidence review. J Health Commun. 2014;19(Suppl 1):164–89. doi: 10.1080/10810730.2014.929763.
    1. Free C, Phillips G, Watson L, Galli L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Med. 2013;10(1):e1001363. doi: 10.1371/journal.pmed.1001363.
    1. Déglise C, Suggs LS, Odermatt P. Short message service (SMS) applications for disease prevention in developing countries. J Med Internet Res. 2012;14(1):e3. doi: 10.2196/jmir.1823.
    1. Peiris D, Praveen D, Johnson C, Mogulluru K. Use of mHealth systems and tools for non-communicable diseases in low- and middle-income countries: a systematic review. J Cardiovasc Transl Res. 2014 Nov;7(8):677–91. doi: 10.1007/s12265-014-9581-5.
    1. Principles for Digital Development. [2016-12-12]. The Principles
    1. American Association for Public Opinion Research. 2016. [2017-03-16]. Standard definitions: final dispositions of case codesoutcome rates for surveys .
    1. Labrique AB, Blynn E, Ahmed S, Gibson DG, Pariyo GW, Hyder AA. Health surveys using mobile phones in developing countries: automated active strata monitoring and other statistical considerations for improving precision and reducing biases. J Med Internet Res. 2017;19(5):e121. doi: 10.2196/jmir.7329.
    1. Bloomberg MR, Bishop J. Understanding death, extending life. Lancet. 2015 Oct 17;386(10003):e18–9. doi: 10.1016/S0140-6736(15)00400-6.
    1. Pan American Health Organization. 2016. Noncommunicable Diseases Surveillance .
    1. Pariyo GW, Wosu AC, Gibson DG, Labrique AB, Ali J, Hyder A. Moving the agenda on noncommunicable diseases: policy implications of mobile phone surveys in low- and middle-income countries. J Med Internet Res. 2017;19(5):e115. doi: 10.2196/jmir.7302.
    1. Thacker SB, Stroup DF, Rothenberg RB. Public health surveillance for chronic conditions: a scientific basis for decisions. Stat Med. 1995;14(5-7):629–41.

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