Integrating Artificial Intelligence into Primary Healthcare Communication Systems for Effective Malnutrition Prevention: Insights from KAAP Among Nursing Mothers in Lagos

Abstract

The issue of child malnutrition in Nigeria remains unresolved, with high levels of stunting in children under-five and inconsistent feeding practices, even in urban centers like Lagos. Mothers are the main conduits between nutrition messages and actual child care; however, the messages conveyed at Primary Healthcare Centers (PHCs) have been shown to result in high surface level awareness without the necessary knowledge and practice. Therefore, the purpose of this study is to analyze the involvement of mothers in nutrition messages on malnutrition and identify areas where AI could be used to improve current communication process. The research uses the Knowledge, Attitude and Practice (KAP) model, which was extended by introducing an additional component of Awareness (KAAP) and theoretical approaches from the Social Cognitive Theory and Diffusion of Innovations to examine mothers' responses to malnutrition messages and explore the role of AI in communication improvement. A convergent parallel mixed-method design is used in the study