Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
8867 participants
INTERVENTIONAL
2023-05-30
2024-02-29
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
HEALTH_SERVICES_RESEARCH
SINGLE
Study Groups
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Appointment Reminder Model
This is the current MomConnect WhatsApp model (control). Mothers receive weekly conversation starter messages reminding them about their upcoming clinic appointments, providing more comprehensive and relevant maternal health information only after mothers respond to the appointment reminder.
Quality-Based Digital Messaging
The impact of MomConnect's models will be evaluated using a randomized controlled trial (RCT). Randomization will be at the individual level, where an individual refers to the "unique user", which is defined by the unique phone number used at the time of registration to MomConnect at health facilities. Randomizing control and treatment allocations ensures that the study groups will be comparable in terms of observable and unobservable characteristics in expectation. Therefore, statistical inference can shed light on the likelihood that any differences in outcome variables at the end of the intervention were caused by the intervention as compared to chance. We will also study the treatment effects on different outcomes between the different arms of the experiment - comparing outcomes across different treatment arms or outcomes in the control to outcomes in treatment arms will help us answer the aforementioned research questions.
Relevant Content Model (WhatsApp)
Mothers receive weekly conversation starter messages on WhatsApp, which carry both clinic appointment reminders along with some maternal and infant health information relevant to their pregnancy/postpartum stage. In addition, a list of "frequently asked questions" (FAQs) relevant to the week of pregnancy the mother is in are provided so that mothers can engage further with maternal health information topics relevant to them.
Quality-Based Digital Messaging
The impact of MomConnect's models will be evaluated using a randomized controlled trial (RCT). Randomization will be at the individual level, where an individual refers to the "unique user", which is defined by the unique phone number used at the time of registration to MomConnect at health facilities. Randomizing control and treatment allocations ensures that the study groups will be comparable in terms of observable and unobservable characteristics in expectation. Therefore, statistical inference can shed light on the likelihood that any differences in outcome variables at the end of the intervention were caused by the intervention as compared to chance. We will also study the treatment effects on different outcomes between the different arms of the experiment - comparing outcomes across different treatment arms or outcomes in the control to outcomes in treatment arms will help us answer the aforementioned research questions.
Relevant Content Model (SMS)
Mothers receive twice weekly conversation starter messages of 160 characters each per SMS, which carry both clinic appointment reminders as well as maternal and infant health information, relevant to their stage of pregnancy or the age of their baby. Mothers can access the list of frequently asked questions relevant to their week of pregnancy via USSD.
Quality-Based Digital Messaging
The impact of MomConnect's models will be evaluated using a randomized controlled trial (RCT). Randomization will be at the individual level, where an individual refers to the "unique user", which is defined by the unique phone number used at the time of registration to MomConnect at health facilities. Randomizing control and treatment allocations ensures that the study groups will be comparable in terms of observable and unobservable characteristics in expectation. Therefore, statistical inference can shed light on the likelihood that any differences in outcome variables at the end of the intervention were caused by the intervention as compared to chance. We will also study the treatment effects on different outcomes between the different arms of the experiment - comparing outcomes across different treatment arms or outcomes in the control to outcomes in treatment arms will help us answer the aforementioned research questions.
Relevant Content + Browsable Content Model
This is a combination of the Relevant Content and Browsable Content Models on WhatsApp (RCM+BCM), including appointment reminders, clinical information, a browsable menu and prompts to relevant stage-based topics. Mothers receive weekly conversation starter messages.
Quality-Based Digital Messaging
The impact of MomConnect's models will be evaluated using a randomized controlled trial (RCT). Randomization will be at the individual level, where an individual refers to the "unique user", which is defined by the unique phone number used at the time of registration to MomConnect at health facilities. Randomizing control and treatment allocations ensures that the study groups will be comparable in terms of observable and unobservable characteristics in expectation. Therefore, statistical inference can shed light on the likelihood that any differences in outcome variables at the end of the intervention were caused by the intervention as compared to chance. We will also study the treatment effects on different outcomes between the different arms of the experiment - comparing outcomes across different treatment arms or outcomes in the control to outcomes in treatment arms will help us answer the aforementioned research questions.
Interventions
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Quality-Based Digital Messaging
The impact of MomConnect's models will be evaluated using a randomized controlled trial (RCT). Randomization will be at the individual level, where an individual refers to the "unique user", which is defined by the unique phone number used at the time of registration to MomConnect at health facilities. Randomizing control and treatment allocations ensures that the study groups will be comparable in terms of observable and unobservable characteristics in expectation. Therefore, statistical inference can shed light on the likelihood that any differences in outcome variables at the end of the intervention were caused by the intervention as compared to chance. We will also study the treatment effects on different outcomes between the different arms of the experiment - comparing outcomes across different treatment arms or outcomes in the control to outcomes in treatment arms will help us answer the aforementioned research questions.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
FEMALE
No
Sponsors
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Reach Digital Health (formerly Praekelt.org)
UNKNOWN
IDinsight
OTHER
Responsible Party
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Haijing Huang
Associate Director, Economist
Locations
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Reach Digital Health (formerly Praekelt.org)
Cape Town, , South Africa
Countries
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Central Contacts
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Facility Contacts
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Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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008
Identifier Type: -
Identifier Source: org_study_id
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