Data and Data Dictionary from Language Models in Nutrition and Dietetics Scoping Review

Language models are a form of generative artificial intelligence that excel at natural language understanding and generation, with possible applications for providing evidence-based nutrition information in an interactive and personalized manner. However, they also pose risks to public health related to inaccuracy, bias, and data protection. It is unclear what quantity or type of research has been conducted on these models applied within nutrition and dietetics. This data arose from a scoping review that aimed to identify the ways in which language models are being applied to nutrition and dietetics and the associated opportunities and challenges. The review was conducted in accordance with a pre-defined protocol, and included original studies from peer-reviewed journals. The databases Medline, EMBASE, PsycINFO, CINAHL, PubMed, Global Health, Web of Science, Scopus, DBLP, and IEEE Xplore were searched, and forward and backward citation chasing conducted for included articles. This data is the information that was extracted and charted from the studies included in the review. The journal article describing the scoping review, including methods and results, is available at: https://doi.org/10.1016/j.ajcnut.2025.101127.