Evidence map›Paper›PMID 40796841›Full record

ArticleBMC public health2025

Modeling health literacy intentions: a structural equation analysis of community residents' willingness to acquire infectious disease specific health literacy.

Junfang Chen, Kening Liu, Qinglin Cheng, Liuxi Wang

Abstract readMulticenter Study
In one paragraph

Article in BMC 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.

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

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Junfang Chen *Division of Public Health, Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), No.568 Mingshi Road, Hangzhou, 310021, China.
Kening Liu *School of Public Health, Hangzhou Normal University, Hangzhou, 310026, China.
Qinglin Cheng *Division of Public Health, Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), No.568 Mingshi Road, Hangzhou, 310021, China. chenghzcdc@sina.com.
Liuxi WangSchool of Public Health, Hangzhou Normal University, Hangzhou, 310026, China.

Funding

Basic Public Welfare Research Project of Zhejiang Province LGF21H260007 and LGF21H19000Hangzhou City Science and Technology Bureau Project 20220919Y059Health Science and Technology Project of Hangzhou Municipality 0020190783Medical Science and Technology Project of Zhejiang Province 2020PY064, 2020KY238, and 2021PY065
6 · The paper itself

Abstract

backgroundHow the willingness to acquire infectious-disease-specific health literacy (IDSHL) can be promoted is unknown among community residents. Community residents' willingness to acquire IDSHL (CRWAI) and its impact on health status is a multifaceted phenomenon that encompasses many factors, including socio-demographic characteristics, cognition, attitude, health behavior, perceived-efficacy, and knowledge needs related to infectious diseases. Early identification of associated-factors for CRWAI is essential. The objective of this research is to construct analytical models and examine the influencing factors relevant to CRWAI.

methodsIn this multi-center cross-sectional study, we included 3,921 subjects from Hangzhou City using the method of stratified cluster sampling. We applied a structural equation modeling (SEM) to examine the factors that affect the CRWAI.

resultsThe findings from the SEM indicated that socio-demographic factors (SDF) (β =0.017, p =0.021), infectious disease cognition (IDC) (β =0.105, p <0.001), infectious disease perceived-efficacy (IDPE) (β =0.109, p <0.001), and infectious disease knowledge needs (IDKN) (β =0.097, p <0.001) was positively correlated with CRWAI. There was no significant association between the attitude and health behavior regarding infectious disease and CRWAI (p>0.05). The results indicated that IDC and IDKN served as mediators in the connection between SDF and CRWAI. Moreover, it was found that IDPE played a mediating part in the relationship of IDC and CRWAI. IDKN functioned as a mediator in the link between IDPE and CRWAI.

conclusionOur findings have indicated potential mechanistic pathways and intervention targets for CRWAI. We have introduced the SEM to analyze the CRWAI. Given that SDF, IDC, IDPE, and IDKN demonstrate direct and interactive associations with CRWAI, strategic interventions targeting these determinants are critical for enhancing population health outcomes in community settings.

Indexed as

Communicable DiseasesHealth Knowledge, Attitudes, PracticeHealth LiteracyIntentionAdultAgedChinaCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedSurveys and QuestionnairesYoung AdultAnalysisInfectious diseaseSpecific health literacyStructural equation modeling

Identifiers

PMID40796841
PMCPMC12341289

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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.