Evidence map›Paper›PMID 33225982›Full record

ArticleTrials2020

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.

Fansu Huang, Xinyin Wu, Yuting Xie, Fang Liu, Juan Li, Xia Li, Zhiguang Zhou

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04016987 (Automated Structured Education Intervention Based on an App and Artificial Intelligence in Chinese Patients With Type 1 Diabetes), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04016987 naunknown statusnot on this map

Automated Structured Education Intervention Based on an App and Artificial Intelligence in Chinese Patients With Type 1 Diabetes

TypeinterventionalSponsorSecond Xiangya Hospital of Central South UniversityRan2020 to 2023Enrolled138ConditionsType 1 DiabetesArmsAutomated structured education intervention based on an app and artificial intelligence
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Fansu HuangNational Clinical Research Center for Metabolic Diseases and Department of Nutrition, The Second Xiangya Hospital, Central South University, Changsha, 410011, China.
Xinyin WuXiangya School of Public Health, Central South University, Changsha, 410011, China.
Yuting XieNational 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.
Fang LiuNational 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.
Juan LiNational 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.
Xia LiNational 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.ORCID http://orcid.org/0000-0001-8665-7983
Zhiguang ZhouNational 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.
Central South University · CN

Funding

National Key R&D Program of China 2017YFC1309604
6 · The paper itself

Abstract

backgroundAlthough 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 registrationClinicalTrials.gov NCT04016987 . Registered on 29 October 2019.

Indexed as

Diabetes Mellitus, Type 1Diabetes Mellitus, Type 2Mobile ApplicationsChinaHumansQuality of LifeRandomized Controlled Trials as TopicSmartphoneArtificial intelligenceAutomated structured educationInterventionRandomized controlled trialSmartphone application (app)Type 1 diabetes

Identifiers

PMID33225982
PMCPMC7681998
OpenAlexW3109422263

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.