Prediction of Snacking Behavior Involving Snacks Having High Levels of Saturated Fats, Salt, or Sugar Using Only Information on Previous Instances of Snacking: Survey- and App-Based Study
The prediction of HFSS snacking using sparse data is possible with reasonable accuracy. Our findings offer a foundation for further exploring how machine learning methods can be used in health psychology and provide directions for further research.
Authors
- Gerasimos Spanakis (ORCID: https://orcid.org/0000-0002-0799-0241)
- Tillman Weyde (ORCID: https://orcid.org/0000-0001-8028-9905)
- Katy Tapper (ORCID: https://orcid.org/0000-0001-9097-6311)
- Emmanuel M. Pothos (ORCID: https://orcid.org/0000-0003-1919-387X)
- Anne Roefs (ORCID: https://orcid.org/0000-0002-9935-1075)
- Shaima Dammas (ORCID: https://orcid.org/0009-0001-0295-2561)
Institutions
- City, University of London (GB)
- King Abdulaziz University (SA)
- Maastricht University (NL)
- King Abdulaziz Hospital (SA)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-03-28
- DOI
- https://doi.org/10.2196/57530
- Primary Topic
- Eating Disorders and Behaviors
- Type
- article
- Field-Weighted Citation Impact
- 0.00