Evidence mapPaperPMID 41921207Full record

SynthesisJournal of medical Internet research2026

Technology-Based Interventions for Prevention of Type 2 Diabetes Following Gestational Diabetes: Systematic Review and Meta-Analysis.

Claire Eades, Anh Nguyen-Hoang, Louise Hoyle, Dawn Cameron, Josie Mm Evans

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Claire EadesHealth Sciences, Faculty of Health Sciences and Sport, University of Stirling, Stirling, Stirlingshire, United Kingdom.ORCID https://orcid.org/0000-0002-4845-332X
Anh Nguyen-HoangHealth Sciences, Faculty of Health Sciences and Sport, University of Stirling, Stirling, Stirlingshire, United Kingdom.ORCID https://orcid.org/0000-0002-9434-2997
Louise HoyleHealth Sciences, Faculty of Health Sciences and Sport, University of Stirling, Stirling, Stirlingshire, United Kingdom.ORCID https://orcid.org/0000-0001-9900-552X
Dawn CameronSchool of Health Sciences and Life Sciences, University of the West of Scotland, Lanarkshire, South Lanarkshire, United Kingdom.ORCID https://orcid.org/0000-0002-2297-9905
Josie Mm EvansPublic Health Scotland, Edinburgh, Lothian, United Kingdom.ORCID https://orcid.org/0000-0001-6672-7876

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious gestational diabetes incurs an 8-fold risk of developing type 2 diabetes, but lifestyle change can prevent or delay progression. Technology-based interventions may help overcome challenges women face in making postpartum lifestyle changes.

objectiveThis study aimed to assess whether technology-based diabetes prevention interventions improve outcomes related to the onset of type 2 diabetes among women with a previous diagnosis of gestational diabetes.

methodsCochrane Central Register of Controlled Trials, CINAHL, Embase, PsycINFO, and Midwives Information and Resource Service were searched to October 2025 using subject headings and free-text terms. Titles and abstracts were independently screened by 2 authors, as were retrieved full-text articles. Studies were eligible if they examined technology-based diabetes prevention interventions delivered between gestational diabetes diagnosis and any time post partum, assessing anthropometric outcomes, glycemic control, health behavior, or psychological outcomes. Risk of bias was assessed by 1 reviewer using the National Institute for Clinical Excellence checklist, and certainty of evidence was assessed by 2 reviewers using the Grading of Recommendations Assessment, Development, and Evaluation. Data were summarized narratively, and results were pooled, where possible, using a random effects model.

resultsThis review identified 15 studies, including 1257 participants. Pooled analysis of 7 studies showed significantly greater weight loss among those receiving technology-based interventions (mean difference -1.01, SE 0.35, 95% CI -1.86 to -0.16 kg; P=.03). Interventions delivered using technology only showed increased weight loss (mean difference -1.13, 95% CI -3.12 to 0.86 kg) as did those with a longer follow-up (mean difference -1.58, 95% CI -3.93 to 0.76 kg) compared with combined technology and telemedicine approaches (mean difference -0.89, 95% CI -2.51 to 0.73 kg) and studies with shorter follow-up (mean difference -0.7, 95% CI -1.21 to -0.18 kg), but these differences were not significant (mode of delivery: χ

conclusionsTechnology-based interventions may help support women in reducing their risk of type 2 diabetes following gestational diabetes mellitus, but substantial heterogeneity, significant risk of bias, and very low certainty in the evidence mean that the findings should be interpreted cautiously. Trials with larger samples and longer follow-up are required to draw firm conclusions.

trial registrationPROSPERO CRD42024324019; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024324019.

Indexed as

Diabetes, GestationalDiabetes Mellitus, Type 2Digital HealthFemaleHumansPregnancyTelemedicinediabetes preventiongestational diabeteshealth behavior changemHealthtype 2 diabetes

Identifiers

PMID41921207
PMCPMC13085990

What Socratic holds

Textmetadata
LicenceCC BY
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.