Technology and Serious Gaming for Neurodevelopmental Disorders: A Systematic Literature Review (Preprint)

BACKGROUND Neurological development in children aged 3-11 is highly sensitive and variable. Critical skills for daily and professional life depend on the development of executive functions, and difficulties in this process can manifest as learning disorders such as ADHD, Dyslexia, and Dysgraphia, affecting 5-10% of children worldwide. Early screening is crucial to ensure timely intervention and enhance the quality of life for affected individuals. However, challenges include high costs, lengthy wait times, and logistical barriers, leading to underdiagnosis and delayed intervention. OBJECTIVE To systematically review technological solutions for early screening and improve diagnosis and intervention strategies for neurodevelopmental disorders in children METHODS Relevant studies were selected using specific inclusion and exclusion criteria to assess the effectiveness of various technologies and methodologies. Technologies evaluated included gamified eye-tracking tests and machine learning algorithms. The review employed quality appraisal tools such as the MMAT table and PRISMA flow chart to synthesize findings from the included studies. RESULTS The review highlights the efficacy of technologies such as gamified eye-tracking tests and machine learning algorithms in screening for learning disorders. Despite promising results documented in the literature, there is a significant gap in translating these technologies into clinical practice. Current practices rely heavily on paper-based tests, which are inefficient for continuous monitoring and vary widely across regions. No specific sample sizes, response rates, P values, or Confidence Intervals were detailed in the abstract. CONCLUSIONS Integrating advanced technologies into clinical settings could significantly enhance early diagnosis and intervention for learning disorders. This aligns with the UK NHS Long Term Plan, advocating for digital and personalized healthcare solutions to improve access to services, enhance patient experiences, support clinical decision-making, and optimize care delivery. Future research should focus on bridging the gap between technological advancements and clinical application. CLINICALTRIAL Not applicable (No RCTs involved).