Evidence mapPaperPMID 41362599Full record

ArticleAsia-Pacific journal of oncology nursing2025

Exploring the eHealth literacy and related influencing factors in patients after lung cancer surgery: A latent profile analysis.

Yuna Cheng, Yiqing Luo, Xinxing Ju, Jie Yang, Xiaoxin Liu

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Article in Asia-Pacific journal of oncology nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yuna ChengDepartment of Oncology Surgery, Shanghai Chest Hospital, School of Nursing Shanghai Jiao Tong University, Shanghai, China.
Yiqing LuoDepartment of Oncology Surgery, Shanghai Chest Hospital, School of Nursing Shanghai Jiao Tong University, Shanghai, China.
Xinxing JuNursing Department, Shanghai Chest Hospital, School of Nursing Shanghai Jiao Tong University, Shanghai, China.
Jie YangDepartment of Intensive Care Unit, Shanghai Chest Hospital, School of Nursing Shanghai Jiao Tong University, Shanghai, China.
Xiaoxin LiuNursing Department, Shanghai Chest Hospital, School of Nursing Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to clarify the subtypes of electronic health literacy among patients with lung cancer surgery and explore the factors affecting profile membership. Methods: A cross-sectional study utilizing surveys among patients who underwent lung cancer surgery ( Results: A total of 354 valid questionnaires were collected and categorized into three latent classes based on eHealth literacy levels among post-operative patients with lung cancer: "Low eHealth Literacy," "Moderate eHealth Literacy," and "High eHealth Literacy". Each profile exhibited distinct characteristics representative of the different levels of eHealth literacy among these patients. Factors such as age, educational attainment, occupation type, monthly household income, presence of chronic diseases, daily use of smart devices, frequency of health information searches, variety of eHealth information sources, self-management efficacy, and levels of social support were identified as influencing the eHealth literacy of postoperative patients with lung cancer across these categories. Conclusions: eHealth literacy among postoperative patients with lung cancer exhibits distinct classification characteristics, with over half falling into low or moderate levels. Identifying the sociodemographic factors and influences affecting different patient groups is crucial for developing internet-based continuity of care measures tailored to the specific needs of these patients.

Indexed as

Electronic health literacyLatent profile analysisPatients with lung cancerSelf-managementSocial supportThe transactional model of eHealth literacy

Identifiers

PMID41362599
PMCPMC12681969

What Socratic holds

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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.