Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic

Modifiable risk factors of vaccine hesitancy: insights from a mixed methods multiple population study combining machine learning and thematic analysis during the COVID-19 pandemic

Abstract Background Vaccine hesitancy, the delay in acceptance or reluctance to vaccinate, ranks among the top threats to global health. Identifying modifiable factors contributing to vaccine hesitancy is crucial for developing targeted interventions to increase vaccination uptake. Methods This mixe...

Full description

Saved in:
Bibliographic Details
Main Authors: Omid V. Ebrahimi, Ella Marie Sandbakken, Sigrun Marie Moss, Sverre Urnes Johnson, Asle Hoffart, Sarah Bauermeister, Ole André Solbakken, Lars T. Westlye, Esten H. Leonardsen
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Medicine
Subjects:
Vaccine hesitancy
Mixed methods study
Machine learning
Extreme Gradient Boosting (XGBoost)
Thematic analysis
General adult population
Online Access:https://doi.org/10.1186/s12916-025-03953-y
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12916-025-03953-y

Similar Items