Testing Content Delivery Models for MomConnect

Study Overview
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Brief Summary
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The case for mobile health (mHealth) has been gaining traction as a source to improve health outcomes of individuals. mHealth refers to the use of Information and Communication Technologies (ICT) to support health care. The ubiquity and penetration of mobile phones presents the opportunity to deliver health care services directly to citizens, with the greatest potential gains in under-resourced health ecosystems. Operating for 8 years and currently supporting 1.28 million mothers through their pregnancies and early childhood care, MomConnect represents one of the largest maternal health messaging platforms in the world. Implemented at the national level, MomConnect has been credited with being the first national-scale mHealth program of its kind and has won numerous international awards. As a WhatsApp-delivered service, MomConnect has been limited by WhatsApp's historical terms of service. In its current form, MomConnect can only start a conversation with mothers once a week by alerting them of their upcoming antenatal care (ANC) appointment. Recent changes to WhatsApp's terms of service have removed the restriction around push messages for certain programs, including MomConnect. Messages have historically been restricted to weekly conversation starters and carry only generic administrative reminder-style information. As a result, it is possible that many mothers are failing to engage with the content as much as they could. If mothers were more engaged, it could greatly increase exposure and knowledge of reducing the total number of mothers exposed to critical maternal and infant health content. With the updated terms of service, there is an opportunity to test different ways of engaging mothers. This study proposes to evaluate, through a randomized controlled trial (RCT), the relative effect of three new behaviorally-informed program models on key knowledge of and adoption of healthy behaviors.

Official Title
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Testing the Effectiveness of Quality-Based WhatsApp Messaging on Vaccine Hesitancy and Childhood Immunization in a National Maternal Messaging Program

Conditions
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Immunization Coverage, Breastfeeding, Hematological Diseases

Intervention / Treatment
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* Behavioral: Quality-Based Digital Messaging


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Pregnant women above the age of 18 signing up for MomConnect when being between 16-30 weeks pregnant Exclusion Criteria: All others

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Health Services Research
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Appointment Reminder Model<br>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. | Behavioral: Quality-Based Digital Messaging<br>* 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.<br>|
| Experimental: Relevant Content Model (WhatsApp)<br>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. | Behavioral: Quality-Based Digital Messaging<br>* 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.<br>|
| Experimental: Relevant Content Model (SMS)<br>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. | Behavioral: Quality-Based Digital Messaging<br>* 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.<br>|
| Experimental: Relevant Content + Browsable Content Model<br>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. | Behavioral: Quality-Based Digital Messaging<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| ANC visits | Binary indicator measuring whether women attended at least 8 ANC visits during pregnancy as recommended by the WHO | Based on phone survey conducted 7 weeks after expected delivery | 
| Immunisation coverage | Binary indicator measuring whether the newborn child received all 6 vaccinations recommended at birth and 6 weeks after birth | Based on phone survey conducted 7 weeks after expected delivery | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Knowledge/Attitude Index | Includes knowledge of/attitudes towards diet, breastfeeding, and anemia | Based on phone survey conducted 7 weeks after expected delivery | 
| Behaviour Index | Includes behaviour related to ante-natal care visits, diet, pregnancy preparedness, breastfeeding, anemia, and child vaccinations | Based on phone survey conducted 7 weeks after expected delivery | 
| User Experience | Includes WhatsApp back-end data and survey data on how users interacted with MomConnect platform | Backend data is collected throughout users' usage of the platform; survey data based on phone survey conducted 7 weeks after expected delivery |