Min Li, Shiyu Liu, Binyang Yu, Ning Li, Aili Lyu, Haiyan Yang, Haiyan He, Na Zhang, Jingru Ma, Meichen Sun, Hong Du, Rui Gao
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引用次数: 0
Abstract
Background: Various mobile technologies and digital health interventions (DHIs) have been developed for type 2 diabetes mellitus (T2DM) management. Strategies are crucial for ensuring the effectiveness of DHIs. However, there is currently a lack of categorization and summarization of the strategies used in DHIs for T2DM.
Objective: This study aims to (1) identify and categorize the strategies used in DHIs for T2DM management; (2) assess the effectiveness of these DHI strategies; and (3) compare and rank the efficacy of different strategy combinations on glycated hemoglobin A1c (HbA1c) levels, fasting blood glucose (FBG) levels, BMI, and weight loss.
Methods: Relevant randomized controlled trials (RCTs) were extracted from PubMed, Web of Science, and Scopus databases. Three rounds of screening and selection were conducted. The strategies were identified and categorized based on the principles of behavior change techniques and behavior strategies. The synthesis framework for the assessment of health IT was used to structure the evaluation of the DHI strategies qualitatively. A network meta-analysis was performed to compare the efficacy of different strategy combinations. The data quality was assessed using the Cochrane Risk of Bias tool.
Results: A total of 52 RCTs were included, identifying 63 strategies categorized into 19 strategy themes. The most commonly used strategies were guide, monitor, management, and engagement. Most studies reported positive or mixed outcomes for most indicators based on the synthesis framework for the assessment of health IT. Research involving a medium or high number of strategies was found to be more effective than research involving a low number of strategies. Of 52 RCTs, 27 (52%) were included in the network meta-analysis. The strategy combination of communication, engagement, guide, and management was most effective in reducing HbA1c levels (mean difference [MD] -1.04, 95% CI -1.55 to -0.54), while the strategy combination of guide, management, and monitor was effective in reducing FBG levels (MD -0.96, 95% CI -1.86 to -0.06). The strategy combination of communication, engagement, goal setting, management, and support was most effective for BMI (MD -2.30, 95% CI -3.16 to -1.44) and weight management (MD -6.50, 95% CI -8.82 to -4.18).
Conclusions: Several DHI strategy combinations were effective in reducing HbA1c levels, FBG levels, BMI, and weight in T2DM management. Health care professionals should be encouraged to apply these promising strategy combinations in DHIs during clinical care. Future research should further explore and optimize the design and implementation of strategies.
背景:各种移动技术和数字健康干预(DHIs)已经开发用于2型糖尿病(T2DM)的管理。战略对于确保发展战略的有效性至关重要。然而,目前缺乏对T2DM患者DHIs治疗策略的分类和总结。目的:本研究旨在(1)确定和分类DHIs用于T2DM管理的策略;(2)评估这些DHI战略的有效性;(3)比较不同策略组合对糖化血红蛋白(HbA1c)水平、空腹血糖(FBG)水平、BMI和体重减轻的效果并进行排名。方法:从PubMed、Web of Science和Scopus数据库中提取相关随机对照试验(RCTs)。进行了三轮筛选。根据行为改变技术和行为策略的原则对策略进行了识别和分类。利用卫生信息技术评估的综合框架定性地构建了健康健康战略的评估。采用网络元分析比较不同策略组合的疗效。使用Cochrane偏倚风险工具评估数据质量。结果:共纳入52项随机对照试验,确定了分为19个战略主题的63项战略。最常用的策略是指导、监视、管理和参与。大多数研究报告了基于卫生信息技术评估综合框架的大多数指标的积极或混合结果。研究发现,涉及中高数量策略的研究比涉及低数量策略的研究更有效。52项随机对照试验中,有27项(52%)纳入网络荟萃分析。沟通、参与、指导和管理的策略组合在降低HbA1c水平方面最有效(平均差值[MD] -1.04, 95% CI -1.55至-0.54),而指导、管理和监测的策略组合在降低FBG水平方面最有效(MD -0.96, 95% CI -1.86至-0.06)。沟通、参与、目标设定、管理和支持的策略组合对BMI (MD -2.30, 95% CI -3.16至-1.44)和体重管理(MD -6.50, 95% CI -8.82至-4.18)最有效。结论:几种DHI策略组合可有效降低T2DM患者的HbA1c水平、FBG水平、BMI和体重。应鼓励卫生保健专业人员在临床护理期间将这些有前途的策略组合应用于DHIs。未来的研究应进一步探索和优化战略的设计和实施。试验注册:PROSPERO CRD42024544629;https://tinyurl.com/3zp2znxt。
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.