Evidence map›Paper›PMID 42807057›Full record

ArticleJournal of multidisciplinary healthcare2026

Digital Health Literacy and Supportive Care Needs After Curative Esophagectomy: A Cross-Sectional Study.

Yan Qian, Lin Zhou, Cuiping Dong, Xianping Li, Na Hu, Qinyun Li, Chun Cai

Abstract read
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Article in Journal of multidisciplinary healthcare, 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

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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.

Yan QianDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.ORCID 0009-0001-0076-1390
Lin ZhouDepartment of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Cuiping DongDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Xianping LiDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Na HuDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Qinyun LiDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Chun CaiDepartment of Nursing, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Recovery after esophagectomy may involve physical, informational, and psychosocial demands. This study examined whether total Digital Health literacy was associated with unmet supportive care needs. Patients and Methods: Here, we conducted a single-center cross-sectional survey of 337 adults attending their first postoperative outpatient review, approximately 1 month after curative esophagectomy. Participants completed the 34-item Supportive Care Needs Survey Short Form and the Chinese Digital Health Literacy Instrument. SCNS-SF34 domain scores were standardized to 0-100. Pearson correlation and a prespecified hierarchical linear regression were used; HC3 and bootstrap estimates assessed the stability of the findings. Results: Mean total supportive care needs and digital health literacy scores were 110.27 (SD 11.52) and 59.50 (SD 11.94), respectively. Patient care and support (74.44) and physical and daily living (72.08) had the highest standardized domain scores. Total digital health literacy was inversely correlated with total supportive care needs (r = -0.856, 95% CI -0.882 to -0.825; P < 0.001; Spearman rho = -0.941). In the complete model, each 1-point higher digital health literacy score was associated with a 0.824-point lower supportive care needs score (B = -0.824, 95% CI -0.917 to -0.732; P < 0.001). The complete model explained 78.4% of outcome variance (adjusted Conclusion: Among digital-device users attending early postoperative follow-up after curative esophagectomy, higher total digital health literacy was associated with fewer reported supportive care needs. Together, these findings support considering digital capability in postoperative needs assessment, but the association should not be interpreted causally because the sample was digitally selected and cross-sectional. Longitudinal studies should include patients with limited digital access and collect relevant clinical and psychosocial covariates.

Indexed as

cross-sectional studydigital health literacyesophageal canceresophagectomysupportive care needs

Identifiers

PMID42807057
PMCPMC13616999

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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.