Trial reportWomen's health (London, England)
Exploring engagement patterns within a mobile health intervention for women at risk of gestational diabetes.
Trial report in Women's health (London, England). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Patient Engagement Strategies for Women with Gestational Diabetes Mellitus in Low-Resource Community Health Settings: A Narrative Review and Clinical Principles.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGestational diabetes mellitus poses a significant global health concern during pregnancy, with behaviour change interventions offering effective risk reduction.
objectivesUnderstanding diverse engagement patterns of pregnant women within mobile health (mHealth) interventions is vital for personalised healthcare. Tailoring interventions based on participant engagement types can enhance program effectiveness. This study aimed to explore engagement patterns among pregnant women at risk of gestational diabetes using the Liva app.
designThis retrospective study serves as a secondary analysis of a randomised controlled trial, focusing on engagement patterns among participants in the intervention arm who received digital health coaching. The intervention group comprised participants enrolled in the Liva app, receiving mHealth lifestyle coaching. Our analysis concentrated on app usage data from 328 participants within the intervention group during the first phase of the study.
methodsPrincipal component analysis reduced data to two dimensions, revealing principal components (PCs). A Gaussian mixture model clustered participants into distinct engagement patterns.
resultsAnalysis of data from 328 pregnant women using the Liva app identified 3 distinct engagement clusters: Cluster 1, "Averagers"; Cluster 2, "Goalers"; and Cluster 3, "Immersers." These clusters correlated with two PCs. "Averagers" engaged moderately with both "Coach Features" and "Goal Features." "Goalers" predominantly used "Goal Features," while "Immersers" engaged with both "Coach Features" and "Goal Features." Notably, 82% of participants fell into the "Averagers" category.
conclusionThis study reveals that individuals, despite similar program participation under uniform conditions, engage with the program differently. Understanding these differences is essential to provide personalised support during pregnancy and has implications for tailored medicine, digital health, and intervention development. Further research is needed to validate these findings across diverse healthcare settings, exploring engagement patterns throughout different pregnancy phases and their impact on health outcomes.
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