Development and Validation of a Mobile Application for Early Childhood Nutrition Monitoring: A Multisensor-Based Non-Contact Anthropometric System

Abstract

The issue of early childhood nutrition in Indonesia, including the high prevalence of stunting, is of critical importance as it can permanently impair children's physical growth and cognitive development. Parents frequently encounter challenges in accurately and consistently monitoring their children's nutritional status, which impedes the early detection of nutritional issues. This study introduces the Multisensor-Based Non-Contact Anthropometric System (MB-NCAS), a mobile application developed to monitor nutritional status and detect stunting in early childhood. The research encompassed five phases using a modified ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. In the Analysis phase, parent questionnaires identified critical nutritional needs and challenges related to stunting. The Design phase focused on setting clear objectives and developing educational content for the app. The Development phase saw the app's creation, which experts in content accuracy, media design, and instructional strategies subsequently validated. During the Implementation phase, the app was tested with parents in Malang City, who participated in pretest and posttest evaluations to assess the app's practicality and effectiveness. The results indicated significant improvements in parental knowledge and skills in monitoring child nutrition and stunting, with expert validation scores averaging 92.6% for media design, 86.25% for material content, and 87.28% for instructional design. The MB-NCAS app is a valid, reliable, and practical tool for early childhood nutrition monitoring. However, challenges such as limited technology access in certain areas may hinder its broader application. Future research should explore the app's effectiveness in diverse settings and focus on improving technology accessibility to enhance its impact on public health.