Exploring engagement patterns within a mobile health intervention for women at risk of gestational diabetes.

Abstract

Background: Gestational diabetes mellitus poses a significant global health concern during pregnancy, with behaviour change interventions offering effective risk reduction.

Objectives: Understanding 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.

Design: This 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.

Methods: Principal component analysis reduced data to two dimensions, revealing principal components (PCs). A Gaussian mixture model clustered participants into distinct engagement patterns.

Results: Analysis 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.

Conclusion: This 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.