Food insecurity is a persistent public health issue linked to poor diet quality and increased risk for chronic conditions. Food-as-medicine programs, such as produce prescriptions and food pharmacies, aim to mitigate these risks by integrating nutrition into clinical care. However, traditional approaches often lack personalization, limiting their effectiveness. This formative research study explored user needs, preferences, and contextual factors to inform the continued development of MyFoodRx , a personalized, AI-driven food-as-medicine smartphone application. Guided by the Information-Motivation-Behavioral Skills (IMB) Model, semi-structured interviews were conducted with 16 participants enrolled in a clinic-based food pharmacy program. Thematic analysis revealed key informational needs (e.g., tailored education, recipes, and eating plans), motivational ifactors (e.g., health improvement, goal tracking, and reducing food waste), and behavioral skill gaps (e.g., portion control, food preparation, and grocery planning). Participants emphasized the importance of personalization based on health conditions, family history, medication use, and available kitchen resources. Findings support the integration of adaptive, real-time personalization features to enhance usability and relevance. This study provides critical insights for the continued development of MyFoodRx , contributing to scalable, equitable, and patient-centered digital food-as-medicine interventions.
DeBate et al. (Sat,) studied this question.