Promised and Lottery Airtime Incentives to Improve Interactive Voice Response Survey Participation Among Adults in Bangladesh and Uganda: Randomized Controlled Trial

Dustin Garrett Gibson, Gulam Muhammed Al Kibria, George William Pariyo, Saifuddin Ahmed, Joseph Ali, Alain Bernard Labrique, Iqbal Ansary Khan, Elizeus Rutebemberwa, Meerjady Sabrina Flora, Adnan Ali Hyder, Dustin Garrett Gibson, Gulam Muhammed Al Kibria, George William Pariyo, Saifuddin Ahmed, Joseph Ali, Alain Bernard Labrique, Iqbal Ansary Khan, Elizeus Rutebemberwa, Meerjady Sabrina Flora, Adnan Ali Hyder

Abstract

Background: Increased mobile phone penetration allows the interviewing of respondents using interactive voice response surveys in low- and middle-income countries. However, there has been little investigation of the best type of incentive to obtain data from a representative sample in these countries.

Objective: We assessed the effect of different airtime incentives options on cooperation and response rates of an interactive voice response survey in Bangladesh and Uganda.

Methods: The open-label randomized controlled trial had three arms: (1) no incentive (control), (2) promised airtime incentive of 50 Bangladeshi Taka (US $0.60; 1 BDT is approximately equivalent to US $0.012) or 5000 Ugandan Shilling (US $1.35; 1 UGX is approximately equivalent to US $0.00028), and (3) lottery incentive (500 BDT and 100,000 UGX), in which the odds of winning were 1:20. Fully automated random-digit dialing was used to sample eligible participants aged ≥18 years. The risk ratios (RRs) with 95% confidence intervals for primary outcomes of response and cooperation rates were obtained using log-binomial regression.

Results: Between June 14 and July 14, 2017, a total of 546,746 phone calls were made in Bangladesh, with 1165 complete interviews being conducted. Between March 26 and April 22, 2017, a total of 178,572 phone calls were made in Uganda, with 1248 complete interviews being conducted. Cooperation rates were significantly higher for the promised incentive (Bangladesh: 39.3%; RR 1.38, 95% CI 1.24-1.55, P<.001; Uganda: 59.9%; RR 1.47, 95% CI 1.33-1.62, P<.001) and the lottery incentive arms (Bangladesh: 36.6%; RR 1.28, 95% CI 1.15-1.45, P<.001; Uganda: 54.6%; RR 1.34, 95% CI 1.21-1.48, P<.001) than those for the control arm (Bangladesh: 28.4%; Uganda: 40.9%). Similarly, response rates were significantly higher for the promised incentive (Bangladesh: 26.5%%; RR 1.26, 95% CI 1.14-1.39, P<.001; Uganda: 41.2%; RR 1.27, 95% CI 1.16-1.39, P<.001) and lottery incentive arms (Bangladesh: 24.5%%; RR 1.17, 95% CI 1.06-1.29, P=.002; Uganda: 37.9%%; RR 1.17, 95% CI 1.06-1.29, P=.001) than those for the control arm (Bangladesh: 21.0%; Uganda: 32.4%).

Conclusions: Promised or lottery airtime incentives improved survey participation and facilitated a large sample within a short period in 2 countries.

Trial registration: ClinicalTrials.gov NCT03773146; https://ichgcp.net/clinical-trials-registry/NCT03773146.

Keywords: Africa; Bangladesh; LMIC; RCT; Uganda; airtime incentive; communicable disease; cooperation; cooperation rate; incentive; interactive voice response; interactive voice response survey; lottery; low income; middle income; mobile phone survey; non-communicable disease; participation; randomized controlled trial; response rate; surveillance; survey.

Conflict of interest statement

Conflicts of Interest: None declared.

©Dustin Garrett Gibson, Gulam Muhammed Al Kibria, George William Pariyo, Saifuddin Ahmed, Joseph Ali, Alain Bernard Labrique, Iqbal Ansary Khan, Elizeus Rutebemberwa, Meerjady Sabrina Flora, Adnan Ali Hyder. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.05.2022.

Figures

Figure 1
Figure 1
Consolidated Standard of Reporting Trial diagram of study participants in Bangladesh.
Figure 2
Figure 2
Consolidated Standard of Reporting Trial diagram of study participants in Uganda.
Figure 3
Figure 3
Pooled risk ratios for cooperation and response rate by study arm.

References

    1. Boutayeb A. The double burden of communicable and non-communicable diseases in developing countries. Trans R Soc Trop Med Hyg. 2006 Mar;100(3):191–9. doi: 10.1016/j.trstmh.2005.07.021.S0035-9203(05)00317-2
    1. Bygbjerg IC. Double burden of noncommunicable and infectious diseases in developing countries. Science. 2012 Sep 21;337(6101):1499–501. doi: 10.1126/science.1223466.337/6101/1499
    1. Global status report on noncommunicable diseases 2010. World Health Organization Institutional Repository for Information Sharing. [2022-04-19]. .
    1. Global Burden of Disease Collaborators Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Br Dent J. 2015 Oct 9;219(7):329–329. doi: 10.1038/sj.bdj.2015.751.
    1. Global action plan for the prevention and control of noncommunicable diseases 2013-2020. World Health Organization. 2013. [2018-08-24]. .
    1. Calba C, Goutard FL, Hoinville L, Hendrikx P, Lindberg A, Saegerman C, Peyre M. Surveillance systems evaluation: a systematic review of the existing approaches. BMC Public Health. 2015;15:448. doi: 10.1186/s12889-015-1791-5. 10.1186/s12889-015-1791-5
    1. Pickens CM, Pierannunzi C, Garvin W, Town M. Surveillance for certain health behaviors and conditions among states and selected local areas - behavioral risk factor surveillance system, United States, 2015. MMWR Surveill Summ. 2018 Jun 29;67(9):1–90. doi: 10.15585/mmwr.ss6709a1.
    1. Healy J, Rodriguez-Lainz A, Elam-Evans LD, Hill HA, Reagan-Steiner S, Yankey D. Vaccination coverage among foreign-born and U.S.-born adolescents in the United States: successes and gaps - National Immunization Survey-Teen, 2012-2014. Vaccine. 2018 Mar 20;36(13):1743–1750. doi: 10.1016/j.vaccine.2018.02.052. S0264-410X(18)30239-1
    1. Measuring the information society report 2017. International Telecommunication Union. 2017. [2022-01-01]. .
    1. Byonanebye DM, Nabaggala MS, Naggirinya AB, Lamorde M, Oseku E, King R, Owarwo N, Laker E, Orama R, Castelnuovo B, Kiragga A, Parkes-Ratanshi R. An interactive voice response software to improve the quality of life of people living with HIV in Uganda: randomized controlled trial. JMIR Mhealth Uhealth. 2021 Feb 11;9(2):e22229. doi: 10.2196/22229. v9i2e22229
    1. Akhtar Z, Mah-E-Muneer S, Rashid MM, Ahmed MS, Islam MA, Chowdhury S, Khan Z, Hassan MZ, Islam K, Parveen S, Debnath N, Rahman M, Chowdhury F. Antibiotics use and its knowledge in the community: a mobile phone survey during the COVID-19 pandemic in Bangladesh. Antibiotics (Basel) 2021 Aug 29;10(9):1052. doi: 10.3390/antibiotics10091052. antibiotics10091052
    1. Lamichhane A, Rana S, Shrestha K, Paudyal R, Malla P, Upadhyaya S, Uprety D, Gurung J, Satow E. Violence and sexual and reproductive health service disruption among girls and young women during COVID-19 pandemic in Nepal: a cross-sectional study using interactive voice response survey. PLoS One. 2021 Dec 8;16(12):e0260435. doi: 10.1371/journal.pone.0260435. PONE-D-21-21956
    1. Zheng Y, Wang W, Zhong Y, Wu F, Zhu Z, Tham Y, Lamoureux E, Xiao L, Zhu E, Liu H, Jin L, Liang L, Luo L, He M, Morgan I, Congdon N, Liu Y. A peer-to-peer live-streaming intervention for children during COVID-19 homeschooling to promote physical activity and reduce anxiety and eye strain: cluster randomized controlled trial. J Med Internet Res. 2021 Apr 30;23(4):e24316. doi: 10.2196/24316. v23i4e24316
    1. Hyder AA, Wosu AC, Gibson DG, Labrique AB, Ali J, Pariyo GW. Noncommunicable disease risk factors and mobile phones: a proposed research agenda. J Med Internet Res. 2017 May 05;19(5):e133. doi: 10.2196/jmir.7246. v19i5e133
    1. Greenleaf AR, 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 across survey modalities. J Med Internet Res. 2017 May 05;19(5):e140. doi: 10.2196/jmir.7331. v19i5e140
    1. Singer E, Ye C. The use and effects of incentives in surveys. Ann Am Acad Pol Soc Sci. 2012 Nov 26;645(1):112–141. doi: 10.1177/0002716212458082.
    1. Brick J, Montaquila J, Hagedorn M, Roth S, Chapman C. Implications for RDD design from an incentive experiment. J Off Stat. 2005;21(4):571–589.
    1. Smith MG, Witte M, Rocha S, Basner M. Effectiveness of incentives and follow-up on increasing survey response rates and participation in field studies. BMC Med Res Methodol. 2019 Dec 05;19(1):230. doi: 10.1186/s12874-019-0868-8. 10.1186/s12874-019-0868-8
    1. Gjøstein Dagrun Kyte, Huitfeldt A, Løberg Magnus, Adami H, Garborg K, Kalager M, Bretthauer M. Incentives and participation in a medical survey. Tidsskr Nor Laegeforen. 2016 Jul;136(12-13):1082–7. doi: 10.4045/tidsskr.15.1096. 3500377
    1. Pieper D, Kotte N, Ober P. The effect of a voucher incentive on a survey response rate in the clinical setting: a quasi-randomized controlled trial. BMC Med Res Methodol. 2018 Aug 16;18(1):86. doi: 10.1186/s12874-018-0544-4. 10.1186/s12874-018-0544-4
    1. Chamie G, Ndyabakira A, Marson KG, Emperador DM, Kamya MR, Havlir DV, Kwarisiima D, Thirumurthy H. A pilot randomized trial of incentive strategies to promote HIV retesting in rural Uganda. PLoS One. 2020 May 29;15(5):e0233600. doi: 10.1371/journal.pone.0233600. PONE-D-19-27665
    1. Gibson DG, Wosu AC, Pariyo GW, Ahmed S, Ali J, Labrique AB, Khan IA, Rutebemberwa E, Flora MS, Hyder AA. 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 Glob Health. 2019;4(5):e001604. doi: 10.1136/bmjgh-2019-001604. bmjgh-2019-001604
    1. Göritz A. Incentives in web studies: methodological issues and a review. Int J Internet Sci. 2006;1(1):58–70.
    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 May 05;19(5):e139. doi: 10.2196/jmir.7428. v19i5e139
    1. The world factbook. Central Intelligence Agency. 2019. [2019-07-22].
    1. Schulz KF, Altman DG, Moher D, CONSORT Group CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMC Med. 2010 Mar 24;8:18. doi: 10.1186/1741-7015-8-18. 1741-7015-8-18
    1. Waksberg J. Sampling methods for random digit dialing. J Am Stat Assoc. 1978 Mar;73(361):40–46. doi: 10.1080/01621459.1978.10479995.
    1. The STEPS instrument and support materials. World Health Organization. 2018. [2018-08-24]. .
    1. Gibson DG, Farrenkopf BA, Pereira A, Labrique AB, Pariyo GW. The development of an interactive voice response survey for noncommunicable disease risk factor estimation: technical assessment and cognitive testing. J Med Internet Res. 2017 May 05;19(5):e112. doi: 10.2196/jmir.7340. v19i5e112
    1. Gibson DG, Pariyo GW, Wosu AC, Greenleaf AR, Ali J, Ahmed S, Labrique AB, Islam K, Masanja H, Rutebemberwa E, Hyder AA. Evaluation of mechanisms to improve performance of mobile phone surveys in low- and middle-income countries: research protocol. JMIR Res Protoc. 2017 May 05;6(5):e81. doi: 10.2196/resprot.7534. v6i5e81
    1. The American Association for Public Opinion Research Standard definitions: final dispositions of case codes and outcome rates for surveys. Encyclopedia Survey Research Methods. 2016. [2018-01-01]. .
    1. Wacholder S. Binomial regression in GLIM: estimating risk ratios and risk differences. Am J Epidemiol. 1986 Jan;123(1):174–84. doi: 10.1093/oxfordjournals.aje.a114212.
    1. Deeks J, Altman D, Bradburn M. Statistical methods for examining heterogeneity and combining results from several studies in meta-analysis. In: Ingger M, Smith G, Altman D, editors. Systematic Reviews in Health Care: Meta‐Analysis in Context, Second edition. London, United Kingdom: BMJ Publishing Group; 2008. p. 312.
    1. Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990;1(1):43–46. doi: 10.1097/00001648-199001000-00010.
    1. Leo B, Morello R, Mellon J, Piexoto T, Davenport S. Do mobile surveys work in poor countries. International Household Survey Network. 2012. [2018-10-05]. .
    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: Ubiquity Press; 2013.
    1. L'Engle K, Sefa E, Adimazoya EA, Yartey E, Lenzi R, Tarpo C, Heward-Mills NL, Lew K, Ampeh Y. Survey research with a random digit dial national mobile phone sample in Ghana: methods and sample quality. PLoS One. 2018;13(1):e0190902. doi: 10.1371/journal.pone.0190902. PONE-D-17-19642
    1. Lietz H, Lingani M, Sié Ali, Sauerborn R, Souares A, Tozan Y. Measuring population health: costs of alternative survey approaches in the Nouna Health and Demographic Surveillance System in rural Burkina Faso. Glob Health Action. 2015 Aug 07;8(1):28330. doi: 10.3402/gha.v8.28330. 28330
    1. Gajic A, Cameron D, Hurley J. The cost-effectiveness of cash versus lottery incentives for a web-based, stated-preference community survey. Eur J Health Econ. 2012 Dec;13(6):789–99. doi: 10.1007/s10198-011-0332-0.
    1. Ali J, Labrique AB, Gionfriddo K, Pariyo G, Gibson DG, Pratt B, Deutsch-Feldman M, Hyder AA. Ethics considerations in global mobile phone-based surveys of noncommunicable diseases: a conceptual exploration. J Med Internet Res. 2017 May 05;19(5):e110. doi: 10.2196/jmir.7326. v19i5e110
    1. Ali J, DiStefano MJ, Coates McCall I, Gibson DG, Al Kibria GM, Pariyo GW, Labrique AB, Hyder AA. Ethics of mobile phone surveys to monitor non-communicable disease risk factors in low- and middle-income countries: a global stakeholder survey. Glob Public Health. 2019 Aug 10;14(8):1167–1181. doi: 10.1080/17441692.2019.1566482.
    1. Mduluza T, Midzi N, Duruza D, Ndebele P. Study participants incentives, compensation and reimbursement in resource-constrained settings. BMC Med Ethics. 2013;14 Suppl 1:S4. doi: 10.1186/1472-6939-14-S1-S4. 1472-6939-14-S1-S4
    1. Lunze K, Paasche-Orlow MK. Financial incentives for healthy behavior: ethical safeguards for behavioral economics. Am J Prev Med. 2013 Jun;44(6):659–65. doi: 10.1016/j.amepre.2013.01.035.S0749-3797(13)00186-4
    1. Pariyo GW, Greenleaf AR, Gibson DG, Ali J, Selig H, Labrique AB, Al Kibria GM, Khan IA, Masanja H, Flora MS, Ahmed S, Hyder AA. 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 Apr 10;14(4):e0214450. doi: 10.1371/journal.pone.0214450. PONE-D-18-32667
    1. Khatun F, Heywood AE, Hanifi SMA, Rahman MS, Ray PK, Liaw S, Bhuiya A. Gender differentials in readiness and use of mHealth services in a rural area of Bangladesh. BMC Health Serv Res. 2017 Aug 18;17(1):573–11. doi: 10.1186/s12913-017-2523-6. 10.1186/s12913-017-2523-6
    1. Zurovac D, Otieno G, Kigen S, Mbithi AM, Muturi A, Snow RW, Nyandigisi A. Ownership and use of mobile phones among health workers, caregivers of sick children and adult patients in Kenya: cross-sectional national survey. Global Health. 2013 May 14;9:20. doi: 10.1186/1744-8603-9-20. 1744-8603-9-20
    1. Labrique A, Blynn E, Ahmed S, Gibson D, Pariyo G, 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 May 05;19(5):e121. doi: 10.2196/jmir.7329. v19i5e121
    1. Mahfoud Z, Ghandour L, Ghandour B, Mokdad AH, Sibai AM. Cell phone and face-to-face interview responses in population-based surveys. Field Methods. 2014 Jul 01;27(1):39–54. doi: 10.1177/1525822X14540084.
    1. Lau C, di Tada N. Identifying non-working phone numbers in Africa for response rate calculations. Surv Pract. 2017 Dec 28;:1–3. doi: 10.29115/sp-2018-0020.
    1. Guwatudde D, Mutungi G, Wesonga R, Kajjura R, Kasule H, Muwonge J, Ssenono V, Bahendeka SK. The epidemiology of hypertension in Uganda: findings from the National Non-Communicable Diseases Risk Factor Survey. PLoS One. 2015 Sep 25;10(9):e0138991–13. doi: 10.1371/journal.pone.0138991. PONE-D-15-27427

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