Enhancing Recommendations Using an Intelligent System for Mothers to Combat Intestinal Parasitic Infections

Background: Intestinal parasitic infection is widespread worldwide and a serious public health problem. It is responsible for enormous morbidity and mortality around the world, particularly in developing countries. Artificial intelligence can create therapeutic suggestions that are individually tailored to each client's unique traits. This study aimed to develop an intelligent system for mothers to provide future recommendations for more effective interventions to combat intestinal parasitic infections. Methods: A quasi-experimental research design (pre/post-test) was utilized to achieve the aim of the current study. The study was conducted at Dar Al Salam Family Health Center in Cairo Governorate, Egypt. A purposive sample of 200 mothers was included in this study. Two tools were used for data collection: First tool: Structured knowledge questionnaire that has four parts: Part I: Demographic data; Part II: Family history for intestinal parasitic infection; Part III: Home environment; Part IV: Mothers' knowledge regarding intestinal parasitic infection. Second tool: Mothers' reported preventive measures checklist. Results: There was a highly significant statistical difference in the mothers' total knowledge level and total preventive measures regarding intestinal parasitic infection between pre and posttest. Moreover, there was highly significant statistical positive correlation between mothers' total knowledge and total preventive measures at pre and post-test. The integration of large language model driven insights, quick engineering, and tailored treatments demonstrated favorable outcomes in enhancing mothers' cleanliness routines. The novelty of this study lies in integrating K-Means clustering, large language models (GPT-4o), and prompt engineering to generate culturally tailored and behavior-specific preventive recommendations for mothers regarding intestinal parasitic infections. Conclusions: Preventive educational programs have a significant positive effect on improving mothers' knowledge and preventive measures to combat intestinal parasitic infections. This study effectively underscores the significance of artificial intelligence-driven analysis and large language models in producing tailored suggestions to enhance mothers' hygiene routines.