Evidence map›Paper›PMID 30760280›Full record

SynthesisBMC endocrine disorders2019

Mobile health in the management of type 1 diabetes: a systematic review and meta-analysis.

Xuemei Wang, Wei Shu, Jian Du, Maolin Du, Peiyu Wang, Mingming Xue, Huiqiu Zheng, Yufeng Jiang, Shaohua Yin, Danyan Liang and 2 more

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC endocrine disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 7 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

45 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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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

12 authors.

Xuemei WangDepartment of Nutrition and Food Hygiene, School of Public Health, Peking University Health Science Center, Beijing, 100191, China.
Wei ShuDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
Jian DuClinical Center on TB Control, Beijing Tuberculosis and Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China.
Maolin DuDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China. dumaolin2016@163.com.
Peiyu WangDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing, 100191, China. wpeiyu138@163.com.
Mingming XueSchool of Basic Medicine, Inner Mongolia Medical University, Hohhot, 010110, China.
Huiqiu ZhengDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
Yufeng JiangDiabetes Centre, The 306th Hospital of PLA, Beijing, 100101, China.
Shaohua YinDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
Danyan LiangDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
Ruiqi WangDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
Lina HouDepartment of Health Statistics, School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.

Funding

Commission of Health and Family Planning of Inner Mongolia Autonomous Region fund project 201302050
6 · The paper itself

Abstract

backgroundAs an insulin-dependent disease, type 1 diabetes requires paying close attention to the glycemic control. Studies have shown that mobile health (mHealth) can improve the management of chronic diseases. However, the effectiveness of mHealth in controlling the glycemic control remains uncertain. The objective of this study was to carry out a systematic review and meta-analysis using the available literature reporting findings on mHealth interventions, which may improve the management of type 1 diabetes.

methodsWe performed a systematic literature review of all studies in the PubMed, Web of Science, and EMbase databases that used mHealth (including mobile phones) in diabetes care and reported glycated hemoglobin (HbA1c) values as a measure of glycemic control. The fixed effects model was used for this meta-analysis.

resultsThis study analyzed eight studies, which involved a total of 602 participants. In the meta-analysis, the fixed effects model showed a statistically significant decrease in the mean of HbA1c in the intervention group: - 0.25 (95% confidence interval: - 0.41, - 0.09; P = 0.003, I

conclusionsMobile health interventions may be effective among patients with type 1 diabetes. A significant reduction in HbA1c levels was associated with adult age, the use of a mobile application, and the long-term duration of the intervention.

Indexed as

Diabetes Mellitus, Type 1HumansSelf-ManagementTelemedicineEffectiveness of mobile healthHbA1c levelMobile health interventionSystematic reviewType 1 diabetes

Identifiers

PMID30760280
PMCPMC6375163

What Socratic 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 Socratic graph.