Developing and validating machine learning models to predict vaccine hesitancy and literacy among adults in the United States
This study demonstrated the effectiveness of machine learning approaches in analyzing robust survey data. These models identified key determinants of vaccine hesitancy and literacy, offering valuable insights into the behavioral and informational factors influencing vaccination decisions among US adults.
Authors
- Paula M. Frew (ORCID: https://orcid.org/0000-0002-3078-9124)
- Amanda L Eiden (ORCID: https://orcid.org/0000-0001-9422-1215)
- Oscar Patterson-Lomba
- Yi Zheng (ORCID: https://orcid.org/0000-0001-8356-2655)
- Arshya Feizi
- Tayler Li
- Dong Wang
- Yan Song
Institutions
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2026-03-11
- DOI
- https://doi.org/10.3389/fpubh.2026.1669058
- Primary Topic
- Vaccine Coverage and Hesitancy
- Type
- article
- Field-Weighted Citation Impact
- 0.00