A Comparison of Functional Features in Chinese and US Mobile Apps for Diabetes Self-Management: A Systematic Search in App Stores and Content Analysis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Mobile health interventions are widely used for self-management of diabetes, which is one of the most burdensome noncommunicable chronic diseases worldwide. However, little is known about the distribution of characteristics and functions of in-store mobile apps for diabetes.

Objective

This study aimed to investigate the distribution of characteristics and functions of the in-store mobile apps for self-management of diabetes in the United States and China using a predefined functional taxonomy, which was developed and published in our previous study.

Methods

We identified apps by searching diabetes in English or Chinese in the Apple iTunes Store and Android Markets (both in the United States and China) and included apps for diabetes self-management. We examined the validity and reliability of the predefined functional taxonomy with 3 dimensions: clinical module, functional module, and potential risk. We then classified all functions in the included apps according to the predefined taxonomy and compared the differences in the features of these apps between the United States and China.

Results

We included 171 mobile diabetes apps, with 133 from the United States and 38 from China. Apps from both countries faced the challenges of evidence-based information, proper risk assessment, and declaration, especially Chinese apps. More Chinese apps provide app-based communication functions (general communication: Chinese vs US apps, 39%, 15/38 vs 18.0%, 24/133; P=.006 and patient-clinician communication: Chinese vs US apps, 68%, 26/38 vs 6.0%, 8/133; P<.001), whereas more US apps provide the decision-making module (Chinese vs US apps, 0%, 0/38 vs 23.3%, 31/133; P=.001), which is a high-risk module. Both complication prevention (Chinese vs US apps, 8%, 3/38 vs 3.8%, 5/133; P=.50) and psychological care (Chinese vs US apps, 0%, 0/38 vs 0.8%, 1/133; P>.99) are neglected by the 2 countries.

Conclusions

The distribution of characteristics and functions of in-store mobile apps for diabetes self-management in the United States was different from China. The design of in-store diabetes apps needs to be monitored closely.

Related collections

Most cited references 22

Record: found
Abstract: found
Article: found

Is Open Access

Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy

Yuan Wu, Xun Yao, Giacomo Vespasiani … (2017)

Background Mobile health apps for diabetes self-management have different functions. However, the efficacy and safety of each function are not well studied, and no classification is available for these functions. Objective The aims of this study were to (1) develop and validate a taxonomy of apps for diabetes self-management, (2) investigate the glycemic efficacy of mobile app-based interventions among adults with diabetes in a systematic review of randomized controlled trials (RCTs), and (3) explore the contribution of different function to the effectiveness of entire app-based interventions using the taxonomy. Methods We developed a 3-axis taxonomy with columns of clinical modules, rows of functional modules and cells of functions with risk assessments. This taxonomy was validated by reviewing and classifying commercially available diabetes apps. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, the Chinese Biomedical Literature Database, and ClinicalTrials.gov from January 2007 to May 2016. We included RCTs of adult outpatients with diabetes that compared using mobile app-based interventions with usual care alone. The mean differences (MDs) in hemoglobin A1c (HbA1c) concentrations and risk ratios of adverse events were pooled using a random-effects meta-analysis. After taxonomic classification, we performed exploratory subgroup analyses of the presence or absence of each module across the included app-based interventions. Results Across 12 included trials involving 974 participants, using app-based interventions was associated with a clinically significant reduction of HbA1c (MD 0.48%, 95% CI 0.19%-0.77%) without excess adverse events. Larger HbA1c reductions were noted among patients with type 2 diabetes than those with type 1 diabetes (MD 0.67%, 95% CI 0.30%-1.03% vs MD 0.36%, 95% CI 0.08%-0.81%). Having a complication prevention module in app-based interventions was associated with a greater HbA1c reduction (with complication prevention: MD 1.31%, 95% CI 0.66%-1.96% vs without: MD 0.38%, 95% CI 0.09%-0.67%; intersubgroup P=.01), as was having a structured display (with structured display: MD 0.69%, 95% CI 0.32%-1.06% vs without: MD 0.16%, 95% CI 0.16%-0.48%; intersubgroup P=.03). However, having a clinical decision-making function was not associated with a larger HbA1c reduction (with clinical decision making: MD 0.18%, 95% CI 0.21%-0.56% vs without: MD 0.61%, 95% CI 0.27%-0.95%; intersubgroup P=.10). Conclusions The use of mobile app-based interventions yields a clinically significant HbA1c reduction among adult outpatients with diabetes, especially among those with type 2 diabetes. Our study suggests that the clinical decision-making function needs further improvement and evaluation before being added to apps.

0 comments Cited 111 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Update of mortality attributable to diabetes for the IDF Diabetes Atlas: Estimates for the year 2013.

(2015)

Mortality is an important measure of population health and is often used to assign priorities in health interventions. Estimating mortality due to diabetes has been challenging because more than a third of countries of the world have no reliable data available on mortality. Moreover estimating mortality attributable to Diabetes is especially challenging since most people die of a related vascular complication such as cardiovascular disease or renal failure.

0 comments Cited 89 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

FDA regulation of mobile health technologies.

Mary Beth Hamel, Nathan G. Cortez, I. Glenn Cohen … (2014)

0 comments Cited 78 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Sheyu Li:

Department of Endocrinology and MetabolismWest China HospitalSichuan University37# Guoxue RoadWuhou DistrictChengdu, 610041China86 1319487484386 2885422982lisheyu@gmail.com

ORCID: http://orcid.org/0000-0003-0060-0287

Journal

Journal ID (nlm-ta): JMIR Mhealth Uhealth

Journal ID (iso-abbrev): JMIR Mhealth Uhealth

Journal ID (publisher-id): JMU

Title: JMIR mHealth and uHealth

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2291-5222

Publication date Collection: August 2019

Publication date (Electronic): 28 August 2019

Volume: 7

Issue: 8

Electronic Location Identifier: e13971

Affiliations

[1 ] Department of Endocrinology and Metabolism West China Hospital Sichuan University Chengdu China

[2 ] Xi An Jiao Tong University The First Affiliated Hospital of Xi An Jiao Tong University Xi An China

[3 ] Department of Population Health & Genomics Ninewells Hospital and Medical School University of Dundee Dundee United Kingdom

[4 ] Science for Life Laboratory, Department of Medical Cell Biology Uppsala University Uppsala Sweden

[5 ] State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center Sun Yat-sen University Guangzhou China

[6 ] Department of Academic Affairs West China School of Medicine Sichuan University Chengdu China

[7 ] Department of Gastroenterology West China Hospital Sichuan University Chengdu China

[8 ] Medicines Monitoring Unit Ninewells Hospital and Medical School University of Dundee Dundee United Kingdom

[9 ] Department of Biomedical Polymer and Artificial Organs College of Polymer Science and Engineering Sichuan University Chengdu China

Author notes

Corresponding Author: Sheyu Li lisheyu@ 123456gmail.com

Author information

Yuan Wu http://orcid.org/0000-0003-0952-6132

Yiling Zhou http://orcid.org/0000-0001-6729-3627

Xuan Wang http://orcid.org/0000-0002-6672-017X

Qi Zhang http://orcid.org/0000-0001-6625-4060

Xun Yao http://orcid.org/0000-0002-9413-3570

Xiaodan Li http://orcid.org/0000-0002-1231-060X

Jianshu Li http://orcid.org/0000-0002-1522-7326

Haoming Tian http://orcid.org/0000-0002-1921-4733

Sheyu Li http://orcid.org/0000-0003-0060-0287

Article

Publisher ID: v7i8e13971

DOI: 10.2196/13971

PMC ID: 6737884

PubMed ID: 31464191

SO-VID: 858f2e34-13bb-4101-82c9-4e8622b302ba

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/.as well as this copyright and license information must be included.

History

Date received : 11 March 2019

Date revision requested : 11 April 2019

Date revision received : 4 June 2019

Date accepted : 7 July 2019

Comments

Comment on this article

scite_

Cited by 10

See all cited by

Most referenced authors 253

See all reference authors

Submit your digital health research with an established publisher
- celebrating 25 years of open access