JHU Evaluation of Mobile Phone Surveys - CATI-IVR Reliability
Principal Investigator(s): View help for Principal Investigator(s) George William Pariyo, Johns Hopkins University. Bloomberg School of Public Health
Version: View help for Version V2
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MT7-Open-Access | 01/03/2019 01:09:PM |
Project Citation:
Pariyo, George William. JHU Evaluation of Mobile Phone Surveys - CATI-IVR Reliability. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-03-15. https://doi.org/10.3886/E107284V2
Project Description
Summary:
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Noncommunicable diseases (NCDs) are the leading
cause of death worldwide. Efficient monitoring and surveillance are
cornerstones to track progress of NCD burden, related risk factors and policy
interventions. The systematic monitoring of risk factors to generate accurate
and timely data is essential for a country’s ability to prioritize essential
resources and make sound policy decisions to address the growing NCD burden.
With increasing access and use of mobile phones
globally, opportunities exist to explore the feasibility of using mobile phone
technology as an interim method to collect data and supplement household
surveys. Such technologies have the potential to allow for efficiencies in
producing timely, affordable, and accurate data to monitor trends, and augment
traditional health surveys with new, faster mobile phone surveys.
The Bloomberg Data for Health initiative aims to
strengthen the collection and use of critical public health information. One of
the components of the initiative aims to explore innovative approaches to NCD
surveillance, including the use of mobile phone surveys for NCDs. The main
objectives of this component are to assess the feasibility, quality, and
validity of nationally representative NCD Mobile Phone Surveys and propose a
globally standardized protocol.
Funding Sources:
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Bloomberg Philanthropies (41388.01)
Scope of Project
Subject Terms:
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mobile phone survey;
computer assisted telephone interviews;
interactive voice response;
reliability;
Bangladesh;
Tanzania;
mHealth;
digital health;
noncommunicable diseases;
behavioral risk factors;
surveillance;
low and middle income countries
Geographic Coverage:
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Bangladesh, Tanzania
Time Period(s):
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6/20/2017 – 8/31/2017
Collection Date(s):
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6/20/2017 – 8/31/2017
Universe:
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Mobile phone subscribers and users in Bangladesh and Tanzania for all licensed and operating mobile phone networks
Data Type(s):
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survey data
Collection Notes:
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We used random digit dialling (RDD), delivered calls using CATI followed a week later by IVR or vice-versa. Respondents provided a response to a live interviewer over the mobile phone (CATI) or pressed a key on their mobile phone keypad (IVR).
Methodology
Response Rate:
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Using AAPOR, we calculated response rate #2 as follows:
Bangladesh (BGD) CATI First Contact (CATI-FC) - 6.1%
Bangladesh (BGD) IVR Follow Up (IVR-FU) - 26.0%
Bangladesh (BGD) IVR First Contact (IVR-FC) - 0.9%
Bangladesh (BGD) CATI Follow Up (CATI-FU) - 79.2%
Tanzania (TZA) CATI First Contact (CATI-FC) - 8.7%
Tanzania (TZA) IVR Follow Up (IVR-FU) - 24.0%
Tanzania (TZA) IVR First Contact (IVR-FC) - 1.1%
Tanzania (TZA) CATI Follow Up (CATI-FU) - 84.6%
Bangladesh (BGD) CATI First Contact (CATI-FC) - 6.1%
Bangladesh (BGD) IVR Follow Up (IVR-FU) - 26.0%
Bangladesh (BGD) IVR First Contact (IVR-FC) - 0.9%
Bangladesh (BGD) CATI Follow Up (CATI-FU) - 79.2%
Tanzania (TZA) CATI First Contact (CATI-FC) - 8.7%
Tanzania (TZA) IVR Follow Up (IVR-FU) - 24.0%
Tanzania (TZA) IVR First Contact (IVR-FC) - 1.1%
Tanzania (TZA) CATI Follow Up (CATI-FU) - 84.6%
Sampling:
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We used random digit dialling (RDD) approach.
All of the mobile network operators (MNOs) registered and active in the country and their unique prefixes that lead the ten-digit mobile phone number were identified for each country. Using these unique prefixes, the remaining digits were then randomly generated via a computer to create a random sample of mobile phone numbers to which the surveys were delivered.
All of the mobile network operators (MNOs) registered and active in the country and their unique prefixes that lead the ten-digit mobile phone number were identified for each country. Using these unique prefixes, the remaining digits were then randomly generated via a computer to create a random sample of mobile phone numbers to which the surveys were delivered.
Data Source:
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Respondents aged 18 years and older who answered a mobile phone call.
Collection Mode(s):
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computer-assisted telephone interview (CATI);
other
Scales:
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Categorical
Weights:
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Not weighted
Unit(s) of Observation:
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Individual respondents
Geographic Unit:
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Country
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