Comparison of SMS and IVR Surveys in Tanzania
Study Details
Study Description
Brief Summary
This study focuses on mechanisms to adapt the performance of interactive voice response (IVR) and short message service (SMS) surveys conducted in low-and middle-income (LMIC) setting (Tanzania) and evaluates how the two survey modalities (IVR and SMS) affect survey metrics, including response, completion and attrition rates.
Condition or Disease | Intervention/Treatment | Phase |
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|
N/A |
Detailed Description
Using random digit dialing (RDD) sampling technique, participants will be randomized to one of two arms : 1) IVR or 2) SMS. Participants in the first study arm will receive an IVR survey. Participants in the second study arm will receive a SMS survey. The IVR and SMS questionnaires contain a set of demographic questions and one non-communicable disease (NCD) module (alcohol, or tobacco, or diet, or physical activity, or blood pressure and diabetes). We will examine contact, response, refusal and cooperation rates and demographic representativeness by each study arm.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Experimental: IVR survey Participants will receive an IVR survey |
Other: IVR survey
Participants will receive an IVR survey
|
Experimental: SMS survey Participants will receive an SMS survey |
Other: SMS survey
Participants will receive a SMS survey
|
Outcome Measures
Primary Outcome Measures
- Cooperation Rate #1 [Through study completion, an average of one month]
As defined by American Association for Public Opinion Research, cooperation rate is defined as I/(I+P+R) where I is the number of participants with complete interviews, P is the number of participants with partial interviews, and R is the number of participants with refusals and breakoffs.
- Response Rate #4 [Through study completion, an average of one month]
As defined by American Association for Public Opinion Research, response rate is defined as (I+P)/(I+P+R+eU) where I is the number of participants with complete interviews, P is the number of participants with partial interviews, R is the number of participants with refusals and breakoffs, and eU is the estimated eligible proportion of unknowns
Secondary Outcome Measures
- Refusal Rate #2 [Through study completion, an average of one month]
As defined by American Association for Public Opinion Research, refusal rate is defined as (R)/(I+P+R+eU) where R is the number of participants with refusals and breakoffs, I is the number of participants with complete interviews, P is the number of participants with partial interviews, and eU is the estimated eligible proportion of unknowns
- Contact Rate #2 [Through study completion, an average of one month]
As defined by American Association for Public Opinion Research, contact rate is defined as (I+P+R)/(I+P+R+eU) where I is the number of participants with complete interviews, P is the number of participants with partial interviews, R is the number of participants with refusals and breakoffs, and eU is the estimated eligible proportion of unknowns
Eligibility Criteria
Criteria
Inclusion Criteria:
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Access to a mobile phone
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Greater or equal to 18 years of age
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Conversant in the Swahili language
Exclusion Criteria:
- Less than 18 years of age
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | Ifakara Health Institute | Dar Es Salaam | Tanzania |
Sponsors and Collaborators
- Johns Hopkins Bloomberg School of Public Health
- Ifakara Health Institute
Investigators
- Principal Investigator: Dustin Gibson, PhD, Johns Hopkins University Bloomberg School of Public Health
- Principal Investigator: Honorati Masanja, PhD, Ifakara Health Institute
Study Documents (Full-Text)
None provided.More Information
Publications
- 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 5;19(5):e112. doi: 10.2196/jmir.7340.
- 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 5;6(5):e81. doi: 10.2196/resprot.7534.
- 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 5;19(5):e139. doi: 10.2196/jmir.7428. Review.
- 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 5;19(5):e133. doi: 10.2196/jmir.7246.
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