AI in Childhood Development Monitoring: Attitudes, Needs, and Concerns in Dutch Youth Healthcare

Abstract

Traditional methods can miss subtle patterns or abnormalities in movement, speech, and language behavior, which are early signs of developmental disorders in young children. Artificial intelligence (AI) technologies offer a multi-modal approach, capturing a wider range of digital biomarkers. By analyzing video and speech data on child development, AI can detect abnormalities earlier. This study explored the attitudes, needs, and concerns of parents, healthcare (HC) professionals, and youth HC managers regarding AI's use in monitoring children's development as a prerequisite for its potential successful implementation and usage. Semi-structured interviews with 28 participants showed generally positive attitudes towards AI, recognizing its potential to enhance efficiency, support HC professionals, and improve monitoring. Parents and managers appreciated reducing visits for healthy children and allowing more time for those identified through triage, while HC professionals emphasized objective and standardized tests, and maintaining personal interactions. Concerns included AI's accuracy, privacy, consent, and ethical issues.

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