Evidence map›Paper›PMID 42852090›Full record

ArticleFrontiers in endocrinology2026

Social network characteristics, self-management behavior, and the mediating role of self-efficacy among diabetes patients: a multicenter cross-sectional study.

Xixuan Cai, JianJiang Pan, Gang Li, Tao Chen, Zhou Fang, Zhangqing Ren, LongMeng Peng, JingJing Huang, XiuHua Gong, QingXia Chen and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Xixuan CaiDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
JianJiang PanDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Gang LiDepartment of General Practice, Shaoxing People's Hospital, Shaoxing, Zhejiang, China.
Tao ChenJianqiao Community Health Service Center, Hangzhou, Zhejiang, China.
Zhou FangShaoxing Second Hospital Lizhu Branch, Shaoxing, Zhejiang, China.
Zhangqing RenDepartment of General Practice, Shaoxing People's Hospital, Shaoxing, Zhejiang, China.
LongMeng PengDepartment of General Medicine, Chengdong Community Health Service Center, Chengdu, Sichuan, China.
JingJing HuangCommunity Health Service Center of Xiasha Street, Hangzhou, Zhejiang, China.
XiuHua GongYangliuxue Town Health Center, Binzhou, Shandong, China.
QingXia ChenShibali Town Health Center, Bozhou, Anhui, China.
BaoJi WangXinhe Community Health Service Center, Xi'an, Shaanxi, China.
LuSha LiDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
LiYing ChenDepartment of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Backgroud: Social isolation (structural social network deficit) is closely linked to poor health outcomes in patients with diabetes. Existing studies often focus on broad isolation or single-dimensional factors, lacking targeted exploration in the Chinese population. Objectives: To explore the associations between social network characteristics and self-management behavior in patients with diabetes, and assess the mediating role of self-efficacy in this association. Methods: A multi-center cross-sectional study was used to recruit 2, 358 patients with diabetes. The assessments included social network characteristics, self-efficacy, and self-management behavior. Pearson's correlation analysis was employed to examine the relationships between these variables. Regression models were utilized to assess the mediating effect of self-efficacy, with the bootstrap method applied to confirm the significance of the mediation pathways. Results: Among the 2, 358 participants, the average diabetes management score was 36.51. Regression models indicated that both family network size ( Conclusions: This study highlights the significant influence of social network characteristics, particularly social support, on self-management behavior in diabetic patients. Family and friend support positively impact self-management behaviors, and self-efficacy mediates these relationships.

Indexed as

Diabetes MellitusDiabetes Mellitus, Type 2Self EfficacySelf-ManagementSocial NetworkingSocial SupportAdultAgedChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedChinese populationdiabetes mellitusself-efficacyself-management behaviorsocial networkstype 2

Identifiers

PMID42852090
PMCPMC13647215

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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 OpenQuestion graph.