Drivers of herpes zoster vaccine hesitancy in adults aged 50 and above: A machine learning approach
The SHAP-XGBoost model showed strong predictive performance for herpes zoster vaccine hesitancy, with vaccine literacy and the 5C psychological antecedents identified as key predictors. This tool can inform targeted health interventions, and future work may integrate community databases for large-scale identification and tailored group strategies.
Authors
- Yanxia Hu (ORCID: https://orcid.org/0000-0002-1815-6324)
- Tianle Zou (ORCID: https://orcid.org/0000-0002-6548-3424)
- Enming Zhang (ORCID: https://orcid.org/0000-0002-0401-4608)
- Xiaolong Wang (ORCID: https://orcid.org/0000-0002-2376-026X)
- Yuan Li (ORCID: https://orcid.org/0000-0001-7735-9255)
- Jianying Zhou (ORCID: https://orcid.org/0000-0002-7903-6895)
- Q. Fang (ORCID: https://orcid.org/0000-0003-1848-7892)
- Shuhui Shang (ORCID: https://orcid.org/0009-0004-0163-1194)
Institutions
- Shanghai Jiao Tong University (CN)
- Ruijin Hospital (CN)
- Tongren Hospital (CN)
Publication Details
- Journal
- Vaccine
- Published
- 2025-10-12
- DOI
- https://doi.org/10.1016/j.vaccine.2025.127838
- Primary Topic
- Vaccine Coverage and Hesitancy
- Type
- article
- Field-Weighted Citation Impact
- 0.00