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).