Accepted for/Published in: JMIR Formative Research
Date Submitted: Sep 12, 2024
Date Accepted: Jun 9, 2025
Design of an Automated Mobile Phone-Based Reminder and Incentive System (mParis): Application in a Quasi-Randomized Controlled Trial to Improve Childhood Vaccination Timeliness in Tanzania
ABSTRACT
Background:
The global, nearly universal penetration of mobile phones has offered novel opportunities for delivering health services and communicating health-related information to individuals. A low-cost system that facilitates autonomous communication with individuals via mobile phones holds potential for expanding the reach of health messaging and service delivery in settings with human resource and infrastructure limitations.
Objective:
We sought to design a flexible, low-code system using open-source software that could be adapted to different contexts and technical environments and accommodate a wide range of automation needs. We report on key details of the mobile phone-based appointment reminder and incentive system (mParis), document its use, review implementation challenges and adaptations to address these challenges in the context of a quasi-randomized trial of mobile phone-based reminders and incentives as means of increasing the timeliness of routine childhood vaccinations in Tanzania, and outline other use cases that highlight the versatility of the system.
Methods:
The mParis instance described in this manuscript, which is hosted in Tanzania, sent automated, individualized vaccination reminders to the mobile phones of mothers of young children. Process workflows, based on the national childhood vaccination schedule of Tanzania, were programmed into mParis. Reminders for vaccinations due at ages 6, 10, and 14 weeks were sent 7 days and 1 day prior to and 14 days after each vaccination due date. A subset of messages included financial incentive offers to mothers for the timely vaccination of their children. We report on implementation outcomes, challenges, and adaptations to address these challenges.
Results:
Between August and December 2017, 412 pregnant women were enrolled into the trial. After mothers reported the birth of their children, individualized vaccination reminder messages were sent for vaccination due dates between January and July 2018. From March 2018, messages contained financial incentive offers. Of 1,397 messages sent, 1,122 SMS (80.3%) were recorded as delivered, 249 (18.8%) as expired and resent, 23 (1.6%) as failed, and 3 (0.2%) as sent but lacking delivery confirmation. 633 messages (45.3%) contained tiered incentive offers. Of 173 women who received at least one message, 67 (38.7%) were sent reminders only; 106 women (61.3%) were sent at least one incentivized message. Numerous challenges were encountered during the system’s implementation, despite its deliberate design to accommodate basic problems such as intermittent internet access and power failures. Continuous adaptation to increase the resilience of the system, complemented by limited backstops, resulted in a successful deployment.
Conclusions:
mParis’ open-source nature, auditability, and ability to autonomously execute algorithms in a low-resource setting with frequent infrastructure challenges suggest favorable prospects to automate health communication in a wide range of settings. mParis’ use in multiple other health-related research studies demonstrates its versatility and ability to accommodate challenges that may be encountered in diverse other contexts. Clinical Trial: ClinicalTrials.gov: NCT03252288
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.