Cited by 411Mobile Health and mHealth ApplicationsDiabetes Management and EducationDiabetes Management and Research

Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials

Open access
Hou, Can, Carter, Ben, Hewitt, Jonathan, Francisa, Trevor, Mayor, Sharon·2016·Diabetes Care

Abstract

OBJECTIVE: To investigate the effect of mobile phone applications (apps) on glycemic control (HbA1c) in the self-management of diabetes. RESEARCH DESIGN AND METHODS: Relevant studies that were published between 1 January 1996 and 1 June 2015 were searched from five databases: Medline, CINAHL, Cochrane Library, Web of Science, and Embase. Randomized controlled trials that evaluated diabetes apps were included. We conducted a systematic review with meta-analysis and GRADE (Grading of Recommendations Assessment, Development and Evaluation) of the evidence. RESULTS: Participants from 14 studies (n = 1,360) were included and quality assessed. Although there may have been clinical diversity, all type 2 diabetes studies reported a reduction in HbA1c. The mean reduction in participants using an app compared with control was 0.49% (95% Cl 0.30, 0.68; I2 = 10%), with a moderate GRADE of evidence. Subgroup analyses indicated that younger patients were more likely to benefit from the use of diabetes apps, and the effect size was enhanced with health care professional feedback. There was inadequate data to describe the effectiveness of apps for type 1 diabetes. CONCLUSIONS: Apps may be an effective component to help control HbA1c and could be considered as an adjuvant intervention to the standard self-management for patients with type 2 diabetes. Given the reported clinical effect, access, and nominal cost of this technology, it is likely to be effective at the population level. The functionality and use of this technology need to be standardized, but policy and guidance are anticipated to improve diabetes self-management care.

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 · 10.2337/dc16-0346

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

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?

  • For the few diabetes apps that have been studied, they significantly reduce HbA1c by an average 0.49%.

    “For the few that have, they significantly reduce glycated hemoglobin A1c (HbA1c) by an average 0.49% [4].”

    From One drop | Mobile on iPhone and apple watch: an evaluation of hbA1c improvement associated with tracking self-care (2017) · cites this paper as [4]

    The Results report a mean HbA1c reduction of 0.49% versus control for app users with type 2 diabetes, and the Type 2 Diabetes section reports that this reduction was statistically significant (pages not specified). The claim does not limit its statement to type 2 diabetes; the paper reports inadequate data to establish effectiveness for type 1 diabetes. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

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

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

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Liang X, Wang Q, Yang X, et al. Effect of mo- bile phone intervention for diabetes on glycae- mic control: a meta-analysis. Diabet Med 2011; 28:455-463

Cited by

Sorted by citations

Authors
Hou, C., Carter, B., Hewitt, J., Francisa, T., & Mayor, S.
Affiliations
  • Cardiff University (GB)
  • University of Nottingham (GB)
Corresponding author
Carter, Ben
Venue
Diabetes Care
Published
2016-10-11
Volume
39
Issue
11
Pages
2089-2095
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
OpenAlex
W2536295516
Cited by
411
References
35
Citations by year
2026: 26 · 2025: 37 · 2024: 45 · 2023: 33 · 2022: 45 · 2021: 58 · 2020: 48 · 2019: 49 · 2018: 50 · 2017: 17 · 2016: 1 · 2012: 1
FWCI
7.46
Type
journal article
Language
en
Open access
Locations
  • Diabetes Care (publishedVersion)
  • PubMed (publishedVersion)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • Research Portal (King's College London) (submittedVersion, other-oa)
  • ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
Funders
Cardiff University
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Keywords
mobile application, diabetes self-management, glycemic control, HbA1c, type 2 diabetes, type 1 diabetes, digital health interventions, young patients
MeSH terms
Blood Glucose, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Self Care, Randomized Controlled Trials as Topic, Disease Management, Cell Phone, Mobile Applications

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