Predicting Attrition in a Public Nutrition Education Program: A Machine Learning Approach
Application of machine learning models in nutrition education program settings can uncover previously unknown patterns contributing to attrition, informing targeted interventions and resource allocation to improve retention and maximize program impact.
Authors
- Andrea Leschewski (ORCID: https://orcid.org/0000-0003-0376-6776)
- Andrew Simpson (ORCID: https://orcid.org/0000-0001-6584-6451)
- G. Bastian (ORCID: https://orcid.org/0000-0002-7227-0371)
- Semhar Michael (ORCID: https://orcid.org/0000-0002-9501-9550)
- George Langelett
- Stacey Finkelstein
- Rohini Daraboina
Institutions
- South Dakota State University (US)
- Stony Brook University (US)
Publication Details
- Journal
- Journal of Nutrition Education and Behavior
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1016/j.jneb.2026.01.010
- Primary Topic
- Dietetics, Nutrition, and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Agriculture
- National Institute of Food and Agriculture