Artificial Intelligence-Supported Nutrition Guidance and Healthy Dietary Habits among University Students: The Mediating Role of Nutrition Literacy

Artificial intelligence (AI)-supported nutrition guidance is increasingly becoming an accessible source of dietary information for university students; however, its relationship with healthy dietary habits and the potential mediating role of nutrition literacy require further investigation. This study examines the relationship between AI-supported nutrition guidance and healthy dietary habits among university students in Pakistan, with nutrition literacy as a potential mediator. A quantitative, cross-sectional research design was proposed, involving 327 undergraduate and postgraduate students recruited through non-probability convenience sampling. Primary data were planned to be collected through a self-administered structured questionnaire distributed using Google Forms. The questionnaire assessed AI-supported nutrition guidance, nutrition literacy, healthy dietary habits, and demographic characteristics. The proposed statistical analysis included descriptive statistics, Pearson correlation, regression analysis, and mediation analysis using Hayes’ PROCESS Macro Model 4 with 5,000 bootstrap samples and 95% confidence intervals. The illustrative results suggested a positive association between AI-supported nutrition guidance and nutrition literacy (β = 0.463, R² = 0.214), alongside a positive relationship between AI-supported nutrition guidance and healthy dietary habits (r = 0.542). The illustrative mediation analysis indicated an indirect effect through nutrition literacy of 0.246, with a 95% bootstrap confidence interval of [0.159, 0.343]. These numerical values are hypothetical and have not been calculated from actual participant responses. The study emphasizes that access to AI-generated nutrition information alone may not ensure healthier dietary decisions, as students must also be able to understand, evaluate, and apply the guidance they receive. Its proposed findings may inform university health education, digital nutrition literacy initiatives, and the development of more reliable AI-supported dietary resources. The research may also provide a foundation for future investigations into how digital nutrition guidance interacts with students’ knowledge, food choices, and everyday dietary practices. Longitudinal and experimental studies could further examine whether improvements in nutrition literacy are associated with sustained changes in healthy eating behaviors.