Evidence map›Paper›PMID 40873983›Full record

ArticleFrontiers in public health2025

Social support and self-management activation among older adult chronic disease patients in China: the chain mediating role of acceptance of illness and fatigue.

Shi Qing Zhang, Man Deng, Xue Jun Xu, Yue Yang, Shuang Zhao, Jianxin Yue, Yong Xia Chen, Fu Zhi Wang, Xiumu Yang

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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 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Shi Qing ZhangSchool of Nursing, Bengbu Medical University, Bengbu, China.
Man DengSchool of Nursing, Anhui Medical University, Hefei, China.
Xue Jun XuSchool of Nursing, Bengbu Medical University, Bengbu, China.
Yue YangSchool of Nursing, Bengbu Medical University, Bengbu, China.
Shuang ZhaoDepartment of Nursing, Bengbu First People's Hospital, Bengbu, China.
Jianxin YueDepartment of Rehabilitation, The Second Affiliated Hospital, Bengbu Medical University, Bengbu, China.
Yong Xia ChenDepartment of Nursing, First People's Hospital Affiliated with Bengbu Medical University, Bengbu, China.
Fu Zhi WangSchool of Health Management, Bengbu Medical University, Bengbu, China.
Xiumu YangSchool of Nursing, Bengbu Medical University, Bengbu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid aging of the global population and the continuous increase in the incidence of chronic diseases among the older adult, self-management activation has become a key factor in improving patients' quality of life. This study examines the relationship between social support and self-management activation in older adult patients with chronic diseases, with a focus on the mediating roles of illness acceptance and fatigue within this framework. Methods: A convenience sampling method was employed to recruit 317 older adult patients with chronic diseases from three communities in Hefei, Anhui Province, China, between August and November 2023. Data collection involved the use of a general information questionnaire, the Illness Acceptance Scale, the Self-Rating Social Support Scale, the Chinese version of the Multidimensional Fatigue Inventory, and the Public Health Activation Index Scale. The influencing factors were examined through independent t-tests, one-way ANOVA, and Pearson correlation analysis in SPSS 26.0. Additionally, a structural equation model (SEM) in AMOS 26.0 was employed to evaluate the possible mediating roles of acceptance of illness and fatigue in the connection between social support and self-management activation. Results: A strong positive relationship was observed between social support, acceptance of illness, and Self-management activation ( Conclusion: This study demonstrates that the Self-management activation of older adult adults with chronic conditions is generally low and may be influenced by various individual and environmental factors. The findings highlight that enhancing acceptance of illness and alleviating fatigue symptoms are crucial intervention strategies to improve Self-management activation, particularly for patients with low levels of social support.

Indexed as

FatigueSelf-ManagementSocial SupportAgedAged, 80 and overChinaChronic DiseaseFemaleHumansMaleMiddle AgedQuality of LifeSurveys and Questionnairesacceptance of illnessfatiguemediationself-management activationsocial support

Identifiers

PMID40873983
PMCPMC12378324

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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.