Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis.

Publication date: Dec 01, 2025

Exploring the influencing factors of COVID-19 vaccine hesitancy and summarizing countermeasures is of great significance for effectively addressing potential public health crises. Based on survey data from China, we employed a Gradient Boosting Decision Tree (GBDT) model and conducted SHAP interpretability analysis. The results show that in the primary series of COVID-19 vaccines, the important factors include social norms, vaccine knowledge, anticipated regret, age, vaccine safety, social responsibility, education level, religious belief, vaccine effectiveness, and perceived severity. While for booster shots, the important variables include age, vaccination experience, vaccine knowledge, vaccine effectiveness, gender, perceived severity, concerns about the epidemic, social norms, anticipated regret, and sense of social responsibility. The differences in the composition and significance of these core predictive factors suggest that COVID-19 vaccine hesitancy is dynamically evolving. This pattern of evolution is manifested as a shift in the decision – making basis from social norms to subjective experiences, in the focus of vaccines from safety – first to effectiveness – priority, and in the decision – making mechanism from emotion – dominated to cognition – driven. The research findings inspire us that when formulating vaccination strategies, multiple factors need to be comprehensively considered. Moreover, strategies should be adjusted in a timely manner according to changes in the vaccination stages to align with the shift in public concerns and decision – making mechanisms.

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Concepts Keywords
China Adolescent
Informatics Adult
Regret Aged
Tree China
Vaccine COVID-19
COVID-19 vaccine
COVID-19 Vaccines
COVID-19 Vaccines
Decision Making
dynamic transformation
Female
Humans
Machine Learning
machine learning
Male
Middle Aged
SARS-CoV-2
Surveys and Questionnaires
Vaccination
Vaccination Hesitancy
vaccine hesitancy
Young Adult

Semantics

Type Source Name
drug DRUGBANK Flunarizine
disease MESH education level
disease MESH COVID-19

Original Article

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