The Role of Digital Health Technology Interventions in the Prevention of Type 2 Diabetes Mellitus: A Systematic Review.

Vivien Nguyen, Paige Ara,David Simmons,Uchechukwu Levi Osuagwu

Clinical medicine insights. Endocrinology and diabetes(2024)

引用 0|浏览1
暂无评分
摘要
Objectives:Diabetes in the 21st century presents one of the greatest burdens of disease on the global population. Digitally mediated interventions have become imperative in alleviating this disease epidemic. We aimed to systematically review randomized controlled trials (RCTs) on different health technologies for preventing Type 2 diabetes mellitus, and their efficacy in decreasing diabetes risk-related outcomes in at-risk patients in comparison to standard care. Methods:Five electronic databases were searched between October 2021 and December 2022. Studies including digital health technology interventions used for preventing diabetes development by reducing diabetes risk-related outcomes in at-risk adults (⩾18 years) were identified. Data on glycemic levels, incidence of T2DM, weight, and intervention descriptions were extracted, and the risk of bias (ROB) was assessed. Results:Nine studies met the inclusion criteria and 5 studies (56%) achieved clinically significant outcomes in at least one of the following: decreased weight (22%), glycemic levels (22%), or incidence of T2DM (11%). Two of the 3 (67%) computer-based interventions effectively reduced the HbA1c levels and mean weight of their study population, and 3 of 6 (50%) mobile based interventions (text messages, mobile app, and telehealth) decreased the incidence of T2DM and HbA1c levels. Four studies each had an overall low ROB and one had a high ROB due to attrition. Conclusion:Preliminary evidence identified in our review demonstrated that health technologies for diabetes prevention are effective for improving diabetes risk-related outcomes. Future research into digital technology protocol and studies of longer duration and more diverse populations are needed for clinical feasibility.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要