Optimizing Early Detection of Early Childhood Developmental Disorders: The Role of Artificial Intelligence (AI) and Parental Involvement in Effective Interventions

Abstract

Early detection of developmental anomalies in children is crucial for timely intervention, which can significantly enhance long-term developmental outcomes. This study aims to evaluate the effectiveness of an artificial intelligence (AI)-based detection tool and parental involvement in identifying and managing developmental disorders in children aged 2 to 6 years. A longitudinal research design was employed, involving 300 children exhibiting early signs of developmental disorders and 150 children in a control group. Data were collected through behavioral observation, AI-based analysis of video and audio interactions, and interviews with parents and educators. The findings revealed that the AI tool demonstrated high sensitivity in detecting motor, language, and autism-related disorders. Children who received early interventions showed significant improvements, particularly in motor skills, language development, and social interaction. Parental involvement in the intervention process further accelerated these improvements. This study highlights the potential of AI to enhance early detection and intervention, especially in resource-limited areas, and underscores the importance of engaging parents in the developmental process of their children. These findings contribute to the understanding of how AI can be integrated into early childhood care programs to improve outcomes for children with developmental challenges.