Cited by 294Mobile Health and mHealth ApplicationsDiabetes Management and EducationMobile Learning in Education

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Open access
Bonoto, Bráulio Cezar, de Araújo, Vânia Eloisa, Godói, Isabella Piassi, de Lemos, Lívia Lovato Pires, Godman, Brian, Bennie, Marion, Diniz, Leonardo Mauricio, Junior, Augusto Afonso Guerra·2017·JMIR mhealth and uhealth

Abstract

BACKGROUND: Diabetes Mellitus (DM) is a chronic disease that is considered a global public health problem. Education and self-monitoring by diabetic patients help to optimize and make possible a satisfactory metabolic control enabling improved management and reduced morbidity and mortality. The global growth in the use of mobile phones makes them a powerful platform to help provide tailored health, delivered conveniently to patients through health apps. OBJECTIVE: The aim of our study was to evaluate the efficacy of mobile apps through a systematic review and meta-analysis to assist DM patients in treatment. METHODS: We conducted searches in the electronic databases MEDLINE (Pubmed), Cochrane Register of Controlled Trials (CENTRAL), and LILACS (Latin American and Caribbean Health Sciences Literature), including manual search in references of publications that included systematic reviews, specialized journals, and gray literature. We considered eligible randomized controlled trials (RCTs) conducted after 2008 with participants of all ages, patients with DM, and users of apps to help manage the disease. The meta-analysis of glycated hemoglobin (HbA1c) was performed in Review Manager software version 5.3. RESULTS: The literature search identified 1236 publications. Of these, 13 studies were included that evaluated 1263 patients. In 6 RCTs, there were a statistical significant reduction (P<.05) of HbA1c at the end of studies in the intervention group. The HbA1c data were evaluated by meta-analysis with the following results (mean difference, MD -0.44; CI: -0.59 to -0.29; P<.001; I²=32%).The evaluation favored the treatment in patients who used apps without significant heterogeneity. CONCLUSIONS: The use of apps by diabetic patients could help improve the control of HbA1c. In addition, the apps seem to strengthen the perception of self-care by contributing better information and health education to patients. Patients also become more self-confident to deal with their diabetes, mainly by reducing their fear of not knowing how to deal with potential hypoglycemic episodes that may occur.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/mhealth.6309

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Flowchart of selection of references to systematic review.
Figure 1 Flowchart of selection of references to systematic review.CC BY · PubMed Central
Figure 2 Analysis of the risk of bias.
Figure 2 Analysis of the risk of bias.CC BY · PubMed Central
Figure 3 Forest-plot of glycated hemoglobin of diabetes patients who used a health app and have access physically or remotelly to health professionals.
Figure 3 Forest-plot of glycated hemoglobin of diabetes patients who used a health app and have access physically or remotelly to health professionals.CC BY · PubMed Central
Figure 4 Forest plot of glycated hemoglobin of diabetes patients who used a health app according to the number of selected app features.
Figure 4 Forest plot of glycated hemoglobin of diabetes patients who used a health app according to the number of selected app features.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 53 references

Research works printed but not linked: 3

  1. International Diabetes Federation20152016-07-04IDF Diabetes Atlas, Seventh Edition http://www.diabetesatlas.org/resources/2015-atlas.html
  2. Lee, E, 2011, Stud Health Technol Inform, 169, 23
  3. 10.1056/NEJM199309303291401 · DOI · Paper page

Cited by

Sorted by citations

See all 294

Metadata

Authors
Bonoto, B. C., de Araújo, V. E., Godói, I. P., de Lemos, L. L. P., Godman, B., Bennie, M., Diniz, L. M., & Junior, A. A. G.
Affiliations
  • Universidade Federal de Minas Gerais (BR)
  • Karolinska University Hospital (SE)
  • University of Strathclyde (GB)
Corresponding author
Bonoto, Bráulio Cezar
Venue
JMIR mhealth and uhealth
Published
2017-03-01
Volume
5
Issue
3
Pages
e4
ISSN
2291-5222 (ISSN-L)
OpenAlex
W2592184816
Cited by
294
References
53
Citations by year
2026: 19 · 2025: 34 · 2024: 24 · 2023: 32 · 2022: 35 · 2021: 39 · 2020: 33 · 2019: 40 · 2018: 28 · 2017: 10
FWCI
5.35
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Academy of Medical Sciences (AMS-NAF1-GuerraJunior)
  • Universidade Federal de Minas Gerais
  • Medical Research Council (MR/K007017/1)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
diabetes mellitus, mobile health apps, HbA1c, glycemic control, diabetes self-management, patient education, hypoglycemia, diabetes self-care

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review