Evidence map›Paper›PMID 40893189›Full record

ArticleFrontiers in public health2025

Development of a transtheoretical model for the prevention and treatment of skin disease through ultraviolet protection based on 14,681 samples of outpatient clinics and a cross-sectional survey.

Xiaoyi Liu, Guiling Xu, Weili Yang, Danping Su, Renlong Yin, Pengjie Wan, Dan Deng, Ying Xiang, Li Hong

Abstract read
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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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Xiaoyi Liu *Department of Dermatology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guiling Xu *Nursing Department, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weili Yang *Department of Dermatology, People's Hospital of Ning'er Hani and Yi Autonomous County, Pu'er City, China.
Danping SuDepartment of Clinical Nutrition, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Renlong YinOutpatient Department, People's Hospital of Ning'er Hani and Yi Autonomous County, Pu'er City, China.
Pengjie WanDepartment of Dermatology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Dan DengDepartment of Dermatology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ying XiangDepartment of Laboratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Li HongDepartment of Clinical Nutrition, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Little is known about the association between types of skin and subcutaneous diseases and UV protection literacy. Objective: To assess the burden and treatment of skin diseases in Ninger County, Yunnan Province, and establish a transtheoretical model for optimizing public perceptions and behaviors regarding UV radiation. Methods: Electronic medical records of outpatients from the dermatology department were collected from January 2022 to July 2024, and a self-administered questionnaire assessed the public knowledge about UV exposure risks and behaviors. Multivariable regression models were used to investigate the correlation between UV protection literacy and dermatological situations. Knowledge, Attitude, and Practice (KAP) model was established and re-examined by Structural Equation Modeling (SEM). Results: Significant seasonal trends in skin disease incidence were observed. Each unit increase in UV protection knowledge score was associated with a 59.1% lower risk of pigmented skin disease and a 56.1% lower risk of skin tumors. A KAP model was developed with coefficients of 0.264 ( Conclusion: The negative association between UV protection literacy and certain skin disease occurence revealed the essentiality of UV protection dissemination.

Indexed as

Health Knowledge, Attitudes, PracticeSkin DiseasesUltraviolet RaysAdultAmbulatory Care FacilitiesChinaCross-Sectional StudiesFemaleHealth LiteracyHumansMaleMiddle AgedSurveys and QuestionnairesKAP modelphotoprotectionprotection literacyskin diseaseUV radiation

Identifiers

PMID40893189
PMCPMC12394189

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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.