# Associations between text communication engagement and maternal-neonatal outcomes in the Mobile WACh NEO Trial

**Authors:** James Peng, Erica Wetzler, Brenda Wandika, Peninah Kithao, June Moraa, Jenna I. Udren, Olivia Schultes, Esther Akinyi, Lusi Osborn, Anna Hedstrom, Barbra A. Richardson, Manasi Kumar, Dalton Wamalwa, John Kinuthia, Keshet Ronen, Jennifer A. Unger

PMC · DOI: 10.1371/journal.pdig.0000968 · PLOS Digital Health · 2025-08-07

## TL;DR

This study explores how engagement with a mobile health program in Kenya affects maternal and neonatal health outcomes, finding that higher engagement is linked to better knowledge of neonatal danger signs but lower odds of early breastfeeding.

## Contribution

The study identifies demographic patterns of engagement and links messaging behavior to specific maternal-neonatal health outcomes in a mobile health intervention.

## Key findings

- Higher participant messaging was associated with increased neonatal danger sign knowledge.
- Increased messaging was linked to lower odds of early breastfeeding initiation.
- Younger, more educated, and first-time mothers engaged more with the messaging intervention.

## Abstract

Despite a global reduction in neonatal deaths in the last few decades, high neonatal mortality rates persist in low- to middle-income countries. Mobile health interventions offer a promising solution to promote early newborn care (ENC) practices and improve neonatal health. The Mobile WACh NEO randomized controlled trial evaluated the effect of a text messaging communication intervention on neonatal health outcomes in Kenya from 2020 to 2023. Perinatal participants received automated messages from enrollment at 28–36 weeks gestation until six weeks postpartum and could message with a study nurse. This secondary analysis aimed to characterize participant text engagement and examine associations between engagement and maternal-neonatal health outcomes. Among 2,470 intervention participants retained through follow-up, median time in the intervention was 14 weeks. Participants received a median of 58 automated messages (average 0.58 per day), sent a median of 24 messages (average 0.25 per day), and received a median of 14 nurse responses (average 0.14 per day). Younger, more educated, unmarried, unemployed, and first-time mothers sent more messages, while those who had a lower social support score at baseline messaged less. Increased participant messaging was associated with greater increase in neonatal danger sign knowledge from baseline to six-week follow-up (Adj Est: 0.39; 95% CI: 0.09-0.68) and lower odds of early initiation of breastfeeding (aOR: 0.62; 95% CI: 0.45-0.86). Our findings contribute to the understanding of who can benefit from mobile health programs and how these interventions might impact behaviors and outcomes.

In this study, we examined how engagement with a mobile health intervention — designed to support mothers during pregnancy and early motherhood— was related to maternal and infant health outcomes. The intervention provided automated health information and allowed mothers to communicate directly with nurses via text messages. Younger, more educated, unmarried, unemployed, and first-time mothers engaged with messaging more, while those with less social support messaged less. We found that higher levels of engagement were linked to improved knowledge of neonatal danger signs, but also to lower odds of early breastfeeding initiation. Although we are unable to conclude that messaging directly impacted any health outcomes, our findings suggest that mothers who engaged more may have sought additional support. This work contributes to ongoing efforts to optimize mobile health programs, particularly in resource-limited settings, by offering insights into engagement patterns and how they might mediate a program’s effectiveness. Our study provides an example of how engagement in mHealth interventions can be reported in relation to health outcomes. We hope this work inspires other researchers to explore which participants engage with their mobile health programs and who stands to benefit most from these interventions, guiding the design and implementation of more effective programs.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC12331090/full.md

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Source: https://tomesphere.com/paper/PMC12331090