Redefining Early Childhood Growth and Development Surveillance: A Sustainable, Technology-Integrated Primary Care Ecosystem Linking Maternal Health Literacy, Digital Monitoring, and Predictive Analytics

Purpose of the study: This study aimed to analyze the relationships between maternal health literacy, digital monitoring utilization, growth and development surveillance behavior, and early developmental risk detection among mothers of toddlers. Methodology: A mixed-methods sequential explanatory design was employed at Arosbaya Public Health Center, Bangkalan, Indonesia. The quantitative phase involved a cross-sectional survey of 210 mothers with children under five years old. Data were analyzed using structural equation modeling–partial least squares (SEM-PLS) to examine relationships among variables. The qualitative phase consisted of in-depth interviews with mothers, healthcare workers, and community health volunteers to provide contextual explanations for the quantitative findings. Thematic analysis was used to interpret qualitative data. Main Findings: Maternal health literacy significantly influenced digital monitoring utilization (β = 0.54, p < 0.001) and surveillance behavior (β = 0.32, p = 0.002). Digital monitoring utilization significantly affected surveillance practices (β = 0.41, p < 0.001) and early developmental risk detection (β = 0.29, p = 0.004). Growth and development surveillance behavior demonstrated the strongest association with early risk detection (β = 0.46, p < 0.001). Qualitative findings revealed mothers who possessed higher health literacy were more capable of interpreting child development information and were more likely to utilize digital tools for monitoring their children’s growth. Novelty/Originality of this study: This study integrates maternal health literacy, digital monitoring utilization, and child growth surveillance behavior within a mixed-methods framework, providing a multidimensional understanding of early developmental risk detection in primary healthcare settings.