How supernatural and scientific beliefs influence individual cancer prevention behaviors: an empirical study of young Chinese adults

These findings elucidate the underlying factors contributing to both effective and ineffective cancer prevention and identify potential pathways for intervention and education. Both theoretical and practical implications are discussed.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2025-12-04
DOI
https://doi.org/10.3389/fpubh.2025.1711669
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How supernatural and scientific beliefs influence individual cancer prevention behaviors: an empirical study of young Chinese adults

Jia Hao, Qiongming Liu
Frontiers in Public Health
Global Cancer Incidence and Screening
article

How supernatural and scientific beliefs influence individual cancer prevention behaviors: an empirical study of young Chinese adults

Jia Hao, Qiongming Liu
article en

Abstract

These findings elucidate the underlying factors contributing to both effective and ineffective cancer prevention and identify potential pathways for intervention and education. Both theoretical and practical implications are discussed.

Frontiers in Public HealthVol. 13
Soochow University (CN)
Ministry of Education of the People's Republic of China, Jiangsu Provincial Department of Education, National Social Science Fund of China
Openalex Percentile: Top 47%
Global Cancer Incidence and Screening
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.