Evidence map›Paper›PMID 36992773›Full record

SynthesisFrontiers in clinical diabetes and healthcare2022

The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review.

Sebastian Stevens, Susan Gallagher, Tim Andrews, Liz Ashall-Payne, Lloyd Humphreys, Simon Leigh

Open access · goldFull text readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Frontiers in clinical diabetes and healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 2 pooled it
19.2field-weighted citation impact, top 1% of its field
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

50 citing papers in PubMed, 2 syntheses or guidelines pooled it, 76 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Sebastian StevensResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
Susan GallagherResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
Tim AndrewsResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
Liz Ashall-PayneResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
Lloyd HumphreysResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
Simon LeighResearch Department, Organisation for the Review of Care and Health Applications, Daresbury, United Kingdom.
University of Warwick · GBUniversity of Plymouth · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Diabetes mellitus (DM) is a leading cause of morbidity and mortality worldwide. At the same time, digital health technologies (DHTs), which include mobile health apps (mHealth) have been rapidly gaining popularity in the self-management of chronic diseases, particularly following the COVID-19 pandemic. However, while a great variety of DM-specific mHealth apps exist on the market, the evidence supporting their clinical effectiveness is still limited. Methods: A systematic review was performed. A systematic search was conducted in a major electronic database to identify randomized controlled trials (RCTs) of mHealth interventions in DM published between June 2010 and June 2020. The studies were categorized by the type of DM and impact of DM-specific mHealth apps on the management of glycated haemoglobin (HbA1c) was analysed. Results: In total, 25 studies comprising 3,360 patients were included. The methodological quality of included trials was mixed. Overall, participants diagnosed with T1DM, T2DM and Prediabetes all demonstrated greater improvements in HbA1c as a result of using a DHT compared with those who experienced usual care. The analysis revealed an overall improvement in HbA1c compared with usual care, with a mean difference of -0.56% for T1DM, -0.90% for T2DM and -0.26% for Prediabetes. Conclusion: DM-specific mHealth apps may reduce HbA1c levels in patients with T1DM, T2DM and Prediabetes. The review highlights a need for further research on the wider clinical effectiveness of diabetes-specific mHealth specifically within T1DM and Prediabetes. These should include measures which go beyond HbA1c, capturing outcomes including short-term glycemic variability or hypoglycemic events.

Indexed as

diabetes mellitusglycemic controlHbA1cmhealthmobile apps

Identifiers

PMID36992773
PMCPMC10012107
OpenAlexW4307269944

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read29
Read underepoch 390

Registered trials

None linked

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.