Evidence map›Paper›PMID 28292740›Full record

ArticleJMIR mHealth and uHealth2017

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, Antonio Nicolucci, Yajie Dong, Joey Kwong, Ling Li, Xin Sun, Haoming Tian, Sheyu Li

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 139 papers, 19 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
139citing papers in PubMed, 19 pooled it
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

139 citing papers in PubMed, 19 syntheses or guidelines pooled it.

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  13. The effectiveness of app-based mobile interventions on nutrition behaviours and nutrition-related health outcomes: A systematic review and meta-analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2019
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79 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yuan WuDepartment of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0003-0952-6132
Xun YaoDepartment of Academic Affairs, West China School of Medicine, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0002-2882-5675
Giacomo VespasianiDiabetes Unit, Madonna del Soccorso Hospital, San Benedetto del Tronto (AP), Italy.ORCID http://orcid.org/0000-0002-6930-485X
Antonio NicolucciCenter for Outcomes Research and Clinical Epidemiology, Pescara, Italy.ORCID http://orcid.org/0000-0002-5939-6850
Yajie DongDepartment of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0003-1038-9075
Joey KwongChinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0002-7473-3827
Ling LiChinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0001-7689-1856
Xin SunChinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0002-6554-7088
Haoming TianDepartment of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0002-1921-4733
Sheyu LiDepartment of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0003-0060-0287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile 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.

objectiveThe 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.

methodsWe 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 A

resultsAcross 12 included trials involving 974 participants, using app-based interventions was associated with a clinically significant reduction of HbA

conclusionsThe use of mobile app-based interventions yields a clinically significant HbA

Indexed as

classificationdiabetes mellitusmHealthmobile applicationsmobile appsmobile health

Identifiers

PMID28292740
PMCPMC5373677

What OpenQuestion holds

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Registered trials

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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.