Evidence mapPaperPMID 40917433Full record

ArticleFrontiers in public health2025

Why patients' knowledge alone isn't enough: examining behavioral and attitudinal gaps in gestational diabetes management among Chinese women.

Yan Liang, Qingli Liu, Xiaoyun Sun, Yan Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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2 · The registry

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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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Yan LiangEmergency Department, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China.
Qingli LiuEmergency Department, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China.
Xiaoyun SunEmergency Department, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China.
Yan WangEmergency Department, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gestational diabetes mellitus (GDM) prevalence is rising in China, necessitating an understanding of knowledge, attitudes, and practices (KAP) among affected women to inform interventions. Methods: This cross-sectional study (June 2020-June 2024) surveyed 3,426 Chinese women with GDM, aged 20-60 years, from urban and rural prenatal clinics across Qingdao city, China. A validated 25-item KAP questionnaire used a three-option response format (yes, no, maybe). Data were collected via WeChat in urban areas and paper-based surveys in rural regions (89% response rate), analyzed using chi-square tests and binary logistic regression. Results: Significant KAP gaps emerged: 63% recognized GDM's link to complications, but only 50% understood its comprehensive management, with 38% aware of eye exams and 40% of foot care needs. Practice adherence was poor-36% monitored blood glucose, 38% limited alcohol, and 53% practiced foot care, despite 59% adhering to medications. Attitudinally, 64% believed health-focused behavior drives management, yet only 36% viewed personal accountability as key, with 39% feeling providers understood their concerns. Intriguingly, younger women (20-30 years) were more open to education (OR 2.67, 95% CI 1.94-3.69, Conclusion: These findings reveal entrenched KAP barriers in GDM management, underscoring the need for innovative, equity-driven interventions-integrating accessible education, community empowerment, and digital tools-to enhance outcomes and reduce the GDM burden in China.

Indexed as

Diabetes, GestationalHealth Knowledge, Attitudes, PracticeAdultChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMiddle AgedPregnancyRural PopulationSurveys and QuestionnairesYoung AdultattitudesChinese womengestational diabetes mellitusknowledgematernal healthpracticessocioeconomic disparitiesurban–rural differences

Identifiers

PMID40917433
PMCPMC12408640

What Socratic holds

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LicenceCC BY
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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.