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Updated: Jun 14, 2025

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
Digital health utilization during pregnancy and the likelihood of preterm birth
Alison K Brinson1,2,3, Hannah R Jahnke3, Natalie Henrich3
1Department of Anthropology, University of North Carolina at Chapel Hill, NC, USA.
Objective:
Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth.
Methods:
Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions.
Results:
Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; p < 0.001). For every 1 h of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [adjusted odds ratio (AOR) (95% confidence interval (CI)) = 0.98 (0.95, 0.998), p = 0.04]. Among individuals who developed gestational conditions, every 1 h increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), p = 0.037]. There was no statistically significant association between Maven use and preterm birth in individuals without gestational conditions.
Conclusion:
Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.
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