PowerMom: A Scalable Digital Health Platform for Maternal Health Research Across Diverse Populations (Preprint)
Authors: Ajayi Toluwalase , Kueper Jacqueline , Ariniello Lauren , Ho Diana , Delgado Felipe , Beal Mathew , Waalen Jill , Baca Motes Katie , Ramos Edward 
Published: December 2024

BACKGROUND

Maternal health research is often limited by challenges in participant recruitment, retention, and data collection, particularly among underrepresented populations. Digital health platforms provide an opportunity to address these barriers by enabling decentralized, real-world data collection and engaging diverse cohorts across wide geographic areas. The PowerMom platform was designed as a scalable, digital research tool to collect longitudinal and episodic data during pregnancy and postpartum stages, leveraging innovative recruitment strategies and multimodal data collection techniques.

OBJECTIVE

This study aimed to evaluate the design, implementation and outcomes of the PowerMom research platform, with a focus on participant recruitment, engagement, and data collection across diverse populations. Secondary objectives included identifying challenges encountered during implementation and deriving lessons to inform future digital maternal health studies.

METHODS

Participants were recruited through digital advertisements, pregnancy apps, and the PowerMom Consortium, a group of over 15 local and national organizations. Data collection included self-reported surveys, wearable devices, and electronic health records (EHR). Anomaly detection measures were implemented to address fraudulent enrollment activity. Recruitment trends and descriptive statistics from survey data were used to summarize participant characteristics and engagement metrics, and missing data were quantified to identify gaps.

RESULTS

A total of 5,617 participants were enrolled from 2021 to 2024, with 69.8% providing demographic data. Of these, 48.5% were younger than 35 years, 14.0% identified as Hispanic or Latinx, and 13.7% identified as Black/African American. Geographic representation spanned all 50 states, Puerto Rico, and Guam, with 58.3% residing in areas with moderate access to maternity care and 16.4% in highly disadvantaged neighborhoods based on the Area Deprivation Index (ADI).
Enrollment rates increased significantly over the study period, from 55 participants in late 2021 to 3,310 in 2024, averaging 99.4 enrollments per week in 2024. Participants completed 17,123 surveys, with 71.8% completing the Intake Survey and 12.4% completing the Postpartum Survey. Wearable device data were shared by 1,168 participants, providing over 378,000 daily biometric measurements, including activity levels, sleep, and heart rate. Additionally, 96 participants connected their EHRs, contributing 276 data points such as diagnoses, medications, and lab results.
Among pregnancy-related characteristics, 28.1% of participants enrolled during the first trimester, while 15.1% reported information about completion of their pregnancies during the study. Delivery outcomes showed that 56.1% of these 913 participants who shared delivery information had spontaneous vaginal deliveries, and 17.9% underwent unplanned cesarean sections.

CONCLUSIONS

The PowerMom platform demonstrates the feasibility of leveraging digital tools to recruit and engage diverse populations in maternal health research. Its capacity to integrate multimodal data sources highlights its potential for generating comprehensive insights into maternal and fetal health. Challenges with data completeness and survey attrition underscore the need for sustained participant engagement strategies. These findings offer valuable lessons for scaling digital health platforms and addressing disparities in maternal health research.

CLINICALTRIAL

ClinicalTrials.gov ID NCT03085875