A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application–Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study

Abstract

OBJECTIVE SMART-GDM examined whether Habits-GDM, a smartphone application (app) coaching program, can prevent excessive gestational weight gain (EGWG) and improve glycemic control and maternal and neonatal outcomes in gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS In this randomized controlled trial, women diagnosed with GDM between 12 and 30 weeks were randomly assigned to usual care (control) or to additional support from Habits-GDM that integrated dietary, physical activity, weight, and glucose monitoring (intervention). The primary outcome was the proportion of participants with EGWG. Secondary outcomes included absolute gestational weight gain (GWG), glycemic control, and maternal, delivery, and neonatal outcomes. RESULTS In total, 340 women were randomized (170 intervention, 170 control; mean ± SD age 32.0 ± 4.2 years; mean BMI 25.6 ± 5.6 kg/m 2 ). There were no statistically significant differences in the proportions of women with EGWG, absolute GWG, or maternal and delivery outcomes between experimental groups. Average glucose readings were lower in the intervention group (mean difference −0.15 mmol/L [95% CI −0.26; −0.03], P = 0.011) as were the proportions of glucose above targets (premeal: 17.9% vs. 23.3%, odds ratio 0.68 [95% CI 0.53; 0.87], P = 0.003; 2-h postmeal: 19.9% vs. 50%, 0.54 [0.42; 0.70], P < 0.001). When regarded as a composite (although not prespecified), the overall neonatal complications (including birth trauma, neonatal hypoglycemia, hyperbilirubinemia, respiratory distress, neonatal intensive care unit admission, and perinatal death) were significantly lower in the intervention group (38.1% vs. 53.7%, 0.53 [0.34; 0.84], P = 0.006). CONCLUSIONS When added to usual care, Habits-GDM resulted in better maternal glycemic control and composite neonatal outcomes (nonprespecified) but did not reduce EGWG among women with GDM.

Women’s Usage Behavior and Perceived Usefulness with Using a Mobile Health Application for Gestational Diabetes Mellitus: Mixed-Methods Study

“…GDM affects 20–30% of pregnancies in Singapore, which is way above the global prevalence of 13.8% [ 2 ]. In Singapore, the current care plan for women with GDM includes providing them with information on health, nutrition, and self-care through face-to-face consultations [ 3 ]. These activities are resource-intensive, do not allow for learning to be spaced over time, and lastly, do not let patients revisit the information at their preferred time and pace [ 3 ].…”

“…In Singapore, the current care plan for women with GDM includes providing them with information on health, nutrition, and self-care through face-to-face consultations [ 3 ]. These activities are resource-intensive, do not allow for learning to be spaced over time, and lastly, do not let patients revisit the information at their preferred time and pace [ 3 ]. Moreover, since patient support occurs only during face-to-face consultations, and consultations are typically short and a few months apart, information may not be delivered on time [ 3 ].…”

“…These activities are resource-intensive, do not allow for learning to be spaced over time, and lastly, do not let patients revisit the information at their preferred time and pace [ 3 ]. Moreover, since patient support occurs only during face-to-face consultations, and consultations are typically short and a few months apart, information may not be delivered on time [ 3 ]. Hence, there is a need to explore alternate ways to provide health information to women with GDM.…”

“…Globally, only a few mHealth applications are designed to support self-management of GDM [ 13 , 14 , 15 , 16 , 17 ]. Most of these mHealth applications are resource-intensive, involving large components of proactive manual feedback by the healthcare team [ 3 ]. For example, some applications [ 13 , 14 ] applied a two-way in-application correspondence between the healthcare professionals and the users.…”

“…On the other hand, studies on the effectiveness of largely automated mHealth applications in managing GDM are limited, i.e., an mHealth application consisting of an interactive coaching system with minimal manual intervention from healthcare professionals. One such study is the SMART-GDM study [ 3 ]. This study has shown clinical benefits when using a largely automated lifestyle coaching program for GDM management [ 3 ].…”