PMID- 33225982 OWN - NLM STAT- MEDLINE DCOM- 20210617 LR - 20220418 IS - 1745-6215 (Electronic) IS - 1745-6215 (Linking) VI - 21 IP - 1 DP - 2020 Nov 23 TI - An automated structured education intervention based on a smartphone app in Chinese patients with type 1 diabetes: a protocol for a single-blinded randomized controlled trial. PG - 944 LID - 10.1186/s13063-020-04835-9 [doi] LID - 944 AB - BACKGROUND: 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. METHODS AND ANALYSIS: 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. DISCUSSION: 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. TRIAL REGISTRATION: ClinicalTrials.gov NCT04016987 . Registered on 29 October 2019. FAU - Huang, Fansu AU - Huang F AD - National Clinical Research Center for Metabolic Diseases and Department of Nutrition, The Second Xiangya Hospital, Central South University, Changsha, 410011, China. AD - 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. FAU - Wu, Xinyin AU - Wu X AD - Xiangya School of Public Health, Central South University, Changsha, 410011, China. FAU - Xie, Yuting AU - Xie Y AD - 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. FAU - Liu, Fang AU - Liu F AD - 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. AD - Clinic Nursing Teaching and Research Section, The Second Xiangya Hospital, Central South University, Changsha, 410011, China. FAU - Li, Juan AU - Li J AD - 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. FAU - Li, Xia AU - Li X AUID- ORCID: 0000-0001-8665-7983 AD - 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. lixia@csu.edu.cn. FAU - Zhou, Zhiguang AU - Zhou Z AD - 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. LA - eng SI - ClinicalTrials.gov/NCT04016987 GR - 2017YFC1309604/National Key R&D Program of China/ PT - Clinical Trial Protocol PT - Journal Article DEP - 20201123 PL - England TA - Trials JT - Trials JID - 101263253 SB - IM MH - China MH - *Diabetes Mellitus, Type 1/diagnosis/therapy MH - *Diabetes Mellitus, Type 2/diagnosis/therapy MH - Humans MH - *Mobile Applications MH - Quality of Life MH - Randomized Controlled Trials as Topic MH - Smartphone PMC - PMC7681998 OTO - NOTNLM OT - Artificial intelligence OT - Automated structured education OT - Intervention OT - Randomized controlled trial OT - Smartphone application (app) OT - Type 1 diabetes COIS- The authors declare that they have no competing interests. EDAT- 2020/11/24 06:00 MHDA- 2021/06/22 06:00 PMCR- 2020/11/23 CRDT- 2020/11/23 08:43 PHST- 2019/10/30 00:00 [received] PHST- 2020/10/22 00:00 [accepted] PHST- 2020/11/23 08:43 [entrez] PHST- 2020/11/24 06:00 [pubmed] PHST- 2021/06/22 06:00 [medline] PHST- 2020/11/23 00:00 [pmc-release] AID - 10.1186/s13063-020-04835-9 [pii] AID - 4835 [pii] AID - 10.1186/s13063-020-04835-9 [doi] PST - epublish SO - Trials. 2020 Nov 23;21(1):944. doi: 10.1186/s13063-020-04835-9.