Effectiveness and acceptability of a digital early warning system for gestational diabetes management: a quasi-experimental study in Lampung Province

Abstract

Despite growing evidence supporting digital health interventions for gestational diabetes mellitus (GDM), no study has evaluated the acceptability and effectiveness of such interventions across geographically heterogeneous healthcare settings in low-resource contexts, where disparities in infrastructure and connectivity may critically influence outcomes. This study addresses this gap by introducing and evaluating the Early Warning System for Gestational Diabetes Mellitus (EWSDMG), a novel digital application uniquely designed to function across diverse geographical conditions. A quasi-experimental one-group pre-test post-test design was employed with 200 GDM-diagnosed pregnant women across four sites in Lampung, Indonesia, representing urban, remote, coastal, and rural settings. Technology acceptability was measured using the System Usability Scale (SUS), while knowledge, adherence, and glycemic profiles were assessed before and after 8 weeks of intervention. The overall SUS score was 77.9 ± 6.4 (Good/Acceptable), with urban settings scoring highest (82.4 ± 5.2). Knowledge and adherence scores increased significantly by 26.27 and 24.35 points, respectively (p < 0.001). Fasting and 2-hour post-prandial glucose decreased by 13.3 mg/dL (p = 0.002) and 22.2 mg/dL (p = 0.001), respectively. SUS scores strongly correlated with glycemic improvement (r = 0.642, p < 0.001). This study provides the first evidence that a single digital GDM intervention can achieve consistent acceptability and clinical effectiveness across heterogeneous geographical settings, offering a scalable model for equitable GDM management in resource-limited regions.