Effectiveness of the Internet of Things for Improving Pregnancy and Postpartum Women's Health in High-Income Countries: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background/Objectives: The Internet of Things (IoT), integrated with application software, has increasingly been used to support health management through monitoring indicators like physical activity, sleep, and heart rate, in pregnant and postpartum women. However, limited evidence exists regarding its effectiveness in improving health outcomes for pregnant and postpartum women. The objective of this systematic review and meta-analysis was to evaluate and synthesize the role of IoT in enhancing the health outcomes of pregnant and postpartum women. Methods: A systematic search was conducted on 13 February 2023, across CENTRAL, CINAHL, ClinicalTrials.gov, Embase, MEDLINE, PsycINFO, PubMed, and WHO ICTRP to identify all randomized controlled trials. Studies were included if they involved pregnant or postpartum women in high-income countries and used sensor-based data collection via smartphones or wearable devices. Two reviewers independently selected the studies, extracted data, and assessed the risk of bias using the Cochrane Collaboration's risk of bias assessment tool 2.0. We performed a pairwise meta-analysis using a random effects model. The findings were reported according to PRISMA guidelines. Results: Seven studies with 1638 pregnant and postpartum women were included in this review. Of the seven included studies, half targeted women with gestational diabetes and the other half targeted obese women. A meta-analysis revealed that IoT interventions may reduce gestational weight gain in women with obesity with a mean difference of -3.35 kg (95% confidence interval (CI): -5.23 to-1.46; I2 = 36%; two studies; 242 women; moderate certainty of evidence). Conclusions: This review suggested that IoT interventions may limit gestational weight gain in pregnant women with obesity. Future studies should evaluate the long-term effects of IoT-based interventions on maternal and neonatal health outcomes.