RECENT ADVANCEMENTS IN THE EARLY DETECTION OF NEURODEVELOPMENTAL DISORDERS AMONG CHILDREN: SYSTEMATIC REVIEW

Abstract

Background: Early detection of neurodevelopmental disorders (NDDs) in children is crucial to ensure timely intervention and improve long-term outcomes. Recent years have seen a surge in innovative diagnostic technologies, ranging from digital tools and artificial intelligence (AI) to genetic and biochemical markers.

Objective: To systematically review recent advancements (2023–2025) in the early detection of neurodevelopmental disorders among children aged 0–12 years, and evaluate their methodologies, target populations, and diagnostic utility.

Methods: A comprehensive search was conducted across scholarly databases from January 2023 to April 2025. Eligible studies were selected based on PRISMA 2020 criteria. Inclusion criteria focused on peer-reviewed studies describing digital, molecular, or community-based screening tools for early NDD detection in children. Data were synthesized narratively due to heterogeneity in study design.

Results: Twenty studies met the inclusion criteria, covering digital diagnostic tools (n=6), genetic diagnostics (n=6), biomarker-based methods (n=4), clinical assessments (n=3), and population-based programs (n=2). Sample sizes ranged from 1 to 240 families. Digital platforms and AI achieved >80% accuracy in identifying children at risk for ASD and ADHD. Genetic testing detected syndromes like Witteveen-Kolk and THRA-related delays. Biomarker findings included low vitamin D and elevated ghrelin in ASD and Prader-Willi syndrome, respectively. Community-led programs in LMICs demonstrated feasibility and equity impact.

Conclusion: Early detection of NDDs is shifting toward multi-modal, tech-enhanced approaches. Digital, genetic, and biochemical innovations show great potential in improving diagnostic timeliness and reach. Broader integration into health systems is needed to ensure equitable access and longitudinal follow-up.