Digital Interventions for Self-Management of Type 2 Diabetes Mellitus: Systematic Literature Review and Meta-Analysis

荟萃分析 心理干预 自我管理 系统回顾 2型糖尿病 医学 梅德林 心理学 糖尿病 计算机科学 内科学 护理部 人工智能 政治学 内分泌学 法学
作者
David Kerr,David Ahn,Kayo Waki,Jing Wang,Boris Breznen,David C. Klonoff
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
卷期号:26: e55757-e55757 被引量:24
标识
DOI:10.2196/55757
摘要

Background The proliferation of digital technology has the potential to transform diabetes management. One of the critical aspects of modern diabetes management remains the achievement of glycemic targets to avoid acute and long-term complications. Objective This study aims to describe the landscape of evidence pertaining to the relative effectiveness or efficacy and safety of various digital interventions for the self-management of type 2 diabetes mellitus (T2DM), with a primary focus on reducing glycated hemoglobin A1c (HbA1c) levels. Methods A systematic literature review (SLR) was conducted by searching Embase, MEDLINE, and CENTRAL on April 5, 2022. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. Eligibility criteria for the SLR included randomized controlled trials (RCTs) and comparative observational studies evaluating interventions containing both human (eg, coaching) and digital components (eg, glucose meter) in adult patients with T2DM. The primary meta-analysis was restricted to studies that reported laboratory-measured HbA1c. In secondary analyses, meta-regression was performed with the intensity of coaching in the digital intervention as a categorical covariate. Results In total, 28 studies were included in this analysis. Most studies (23/28, 82%) used the reduction of HbA1c levels as the primary end point, either directly or as a part of a multicomponent outcome. In total, 21 studies reported statistically significant results with this primary end point. When stratified into 3 intervention categories by the intensity of the intervention supporting the digital health technology (analyzing all 28 studies), the success rate appeared to be proportional to the coaching intensity (ie, higher-intensity studies reported higher success rates). When the analysis was restricted to RCTs using the comparative improvement of HbA1c levels, the effectiveness of the interventions was less clear. Only half (12/23, 52%) of the included RCTs reported statistically significant results. The meta-analyses were broadly aligned with the results of the SLR. The primary analysis estimated a greater reduction in HbA1c associated with digital interventions compared with usual care (–0.31%, 95% CI –0.45% to –0.16%; P<.001). Meta-regression estimated reductions of –0.45% (95% CI –0.81% to –0.09%; P=.02), –0.29% (95% CI –0.48% to –0.11%; P=.003), and –0.28% (95% CI –0.65% to 0.09%; P=.20) associated with high-, medium-, and low-intensity interventions, respectively. Conclusions These findings suggest that reducing HbA1c levels in individuals with T2DM with the help of digital interventions is feasible, effective, and acceptable. One common feature of effective digital health interventions was the availability of timely and responsive personalized coaching by a dedicated health care professional.
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