National Clinical Research Center for Metabolic Diseases and Department of Nutrition, The Second Xiangya Hospital, Central South University, Changsha, 410011, China.
National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, China.
Trials. 2020 Nov 23;21(1):944. doi: 10.1186/s13063-020-04835-9.
Although evidence had demonstrated the effectiveness of smartphone apps in diabetes care, the majority of apps had been developed for type 2 diabetes mellitus (T2DM) patients and targeted at populations outside of China. The effects of applying a smartphone app with structured education on glycemic control in type 1 diabetes mellitus (T1DM) are unclear. A digital, culturally tailored structured education program was developed in a smartphone app (Yi tang yun qiao) to provide an automated, individualized education program aimed at improving self-management skills in patients with T1DM in China. This trial aims to investigate the effectiveness of this smartphone app among Chinese T1DM patients.
This single-blinded, 24-week, parallel-group randomized controlled trial of a smartphone app versus routine care will be conducted in Changsha, China. We plan to recruit 138 patients with T1DM who will be randomly allocated into the intervention group (automated, individualized education through an app) or routine care group. The intervention will last for 24 weeks. The primary outcome will be the change in glycated hemoglobin (HbA1c) from baseline to week 24. The secondary outcomes will include time in range, fasting blood glucose, levels of serum triglycerides and cholesterol, blood pressure, body mass index, quality of life, diabetes self-care activities, diabetes self-efficacy, depression, anxiety, and patient satisfaction. Adverse events will be formally documented. Data analysis will be conducted using the intention-to-treat principle with appropriate univariate and multivariate methods. Missing data will be imputed with a multiple imputation method under the "missing at random" assumption.
This trial will investigate the effectiveness of an app-based automated structured education intervention for Chinese patients with T1DM. If the intervention is effective, this study will provide a strategy that satisfies the need for effective lifelong diabetes care to reduce the disease burden and related complications resulting from T1DM.
ClinicalTrials.gov NCT04016987 . Registered on 29 October 2019.
尽管有证据表明智能手机应用在糖尿病护理中的有效性，但大多数应用程序都是为 2 型糖尿病（T2DM）患者开发的，针对的是中国以外的人群。应用具有结构化教育的智能手机应用程序对 1 型糖尿病（T1DM）患者血糖控制的影响尚不清楚。我们开发了一款具有结构化教育的智能手机应用程序（易唐云桥），这是一款数字化的、文化适配的结构化教育程序，旨在为中国 T1DM 患者提供自动化、个体化的教育计划，以提高他们的自我管理技能。本试验旨在研究该智能手机应用程序在中国 T1DM 患者中的有效性。
这是一项在中国长沙进行的为期 24 周、单盲、平行组随机对照试验，比较智能手机应用程序与常规护理。我们计划招募 138 例 T1DM 患者，将其随机分为干预组（通过应用程序进行自动化、个体化教育）或常规护理组。干预将持续 24 周。主要结局指标为从基线到 24 周时糖化血红蛋白（HbA1c）的变化。次要结局指标包括达标时间、空腹血糖、血清甘油三酯和胆固醇水平、血压、体重指数、生活质量、糖尿病自我护理活动、糖尿病自我效能、抑郁、焦虑和患者满意度。不良事件将被正式记录。数据分析将采用意向治疗原则，采用适当的单变量和多变量方法。缺失数据将采用“随机缺失”假设下的多重插补方法进行插补。
本试验将研究基于应用程序的自动化结构化教育干预对中国 T1DM 患者的有效性。如果干预有效，本研究将为满足有效终身糖尿病护理需求提供一种策略，以减轻 T1DM 相关疾病负担和并发症。
ClinicalTrials.gov NCT04016987。于 2019 年 10 月 29 日注册。
