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Utilizing AI to Generate Culinary Medicine Resources for Migrant Workers with Chronic Diseases
Caculba, Marican Nagle, Rebecca Doucet, Julia
Caculba, Marican
Nagle, Rebecca
Doucet, Julia
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Abstract
Latin American migrant workers in Vermont face a critical paradox: they provide essential labor to sustain the state's agricultural economy yet encounter food insecurity and healthcare barriers. This quality improvement (QI) project explored the intersection of social determinants of health (SDOH), chronic disease disparities, and culturally relevant interventions among this population. Latin Americans in the US experience disproportionate rates of chronic diseases compared to average US adult. This QI project aimed to enhance chronic disease self-management among Latin American migrant workers in Vermont by integrating Culinary Medicine (CM), an evidence-based, patient-centered approach that combines nutritional science with traditional medicine. Artificial Intelligence (AI) was used to generate CM resources, which were translated to Spanish for accessibility. This QI project resulted in an n=4, all identifying as Mexican. Chronic diseases reported were T2DM, dyslipidemia, HTN, and fatty liver disease. 75% reported food insecurity. Prior to the intervention, 100% of the participants agreed with the statement of I know the nutritional recommendations to help manage my chronic disease. Post intervention, 50% maintained the same level of confidence, and the remaining 50% either increased or decreased by one point. Notably, 100% of the participants agreed or strongly agreed on feeling more supported with the resources. There is a positive association between perceived levels of social support and treatment adherence. These findings suggest the importance of culturally tailored health interventions for health promotion among Vermont migrant workers.
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Date
2025-01-01