Understanding Patient Perceptions of Genetic Testing to Predict Type 2 Diabetes Risk After Gestational Diabetes

Women with GDM were receptive to genetic risk-prediction for T2DM, with low concerns around data usage. Demographic differences in acceptability and motivation highlight the need for inclusive, targeted communications and lifestyle support alongside integration testing into postnatal-GDM care.

Authors

Institutions

Publication Details

Journal
Endocrinology Diabetes & Metabolism
Published
2026-03-27
DOI
https://doi.org/10.1002/edm2.70206
Primary Topic
BRCA gene mutations in cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Understanding Patient Perceptions of Genetic Testing to Predict Type 2 Diabetes Risk After Gestational Diabetes

Julia Zöllner, Zoe Taylor, P. S. Shetty, M. Christodoulou et al.
Endocrinology Diabetes & Metabolism
BRCA gene mutations in cancer
article

Understanding Patient Perceptions of Genetic Testing to Predict Type 2 Diabetes Risk After Gestational Diabetes

Julia Zöllner, Zoe Taylor, P. S. Shetty, M. Christodoulou, Ria Patel
article en

Abstract

Women with GDM were receptive to genetic risk-prediction for T2DM, with low concerns around data usage. Demographic differences in acceptability and motivation highlight the need for inclusive, targeted communications and lifestyle support alongside integration testing into postnatal-GDM care.

Endocrinology Diabetes & MetabolismVol. 9(3)
London Women's Clinic (GB), University College London (GB)
Openalex Percentile: Top 6%
BRCA gene mutations in cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.