Evidence map›Paper›PMID 41668010›Full record

ArticleBMC nephrology2026

Influential factors of benefit finding in hemodialysis patients: a qualitative study using the social-ecological model.

Xinyue Gao, Yanlin Gong, Lijing Chen, Jing Chen, Lingling Liu, Jing Wu, Jing Chu

Abstract read
In one paragraph

Article in BMC nephrology, 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

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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xinyue Gao *Naval Medical University School of Nursing, Shanghai, China.
Yanlin Gong *Naval Medical University School of Nursing, Shanghai, China.
Lijing Chen *Naval Medical University School of Nursing, Shanghai, China.
Jing ChenShanghai Changzheng Hospital, Shanghai, China.
Lingling LiuShanghai Changzheng Hospital, Shanghai, China.
Jing WuNaval Medical University School of Nursing, Shanghai, China. qingqing20030511@163.com.
Jing ChuNaval Medical University School of Nursing, Shanghai, China. chujing1999@smmu.edu.cn.

Funding

Naval Medical University 2021MS02The Medical Logistical Support Department 22BJZ09
6 · The paper itself

Abstract

backgroundThe ability to find benefits in adverse situations has been shown to foster a positive outlook and enhance quality of life among patients undergoing medical treatment. However, factors influencing benefit finding in hemodialysis patients remain underexplored from a multi-level perspective. This study explores the perspectives of hemodialysis patients regarding the factors influencing benefit finding, framed within the social-ecological model.

methodsThis qualitative study is part of a longitudinal mixed-methods project that was conducted between June and December of 2023 across five hemodialysis centers in Shanghai, China. Twenty-five hemodialysis patients participated. Data were analyzed using directed content analysis guided by the Social Ecological Model, incorporating both synchronic and diachronic methods to explore patterns and the evolution of benefit finding over time.

resultsFour levels were identified as factors influencing benefit finding: (i) Intrapersonal Initiative, including experiences related to hemodialysis diagnosis and treatment, physical condition, optimistic mindset, and self-care competence; (ii) Relational Bonds, including support from family, healthcare professionals, and social contacts; (iii) Surrounding Support, including resources from medical institutions, communities, and interest groups; and (iv) Societal Scaffolding, including public policies and technological advances. Three representative case vignettes illustrated how variations in factors affect benefit finding.

conclusionsThe study highlights the utility of the social-ecological model in understanding multi-level factors that promote benefit finding in hemodialysis patients. Findings emphasize the need for integrated, multi-level interventions to improve well-being and quality of life in future studies. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Kidney Failure, ChronicQuality of LifeRenal DialysisAdultAgedChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedQualitative ResearchSocial SupportBenefit findingHemodialysisInfluential factorsQualitative studySocial-ecological model

Identifiers

PMID41668010
PMCPMC12997918

What Socratic holds

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LicenceCC BY-NC-ND
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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.