ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS AND TREATMENT OF CHILDHOOD HANDWRITING DISORDERS: A SCOPING REVIEW

This protocol outlines a scoping review on the use of artificial intelligence (AI) in the diagnosis and treatment of childhood handwriting disorders, such as dysgraphia and difficulties with spelling, grammar, punctuation, or text composition. Handwriting is a complex skill that develops progressively from early childhood and may reflect underlying neurodevelopmental disorders when impaired. Despite advances in traditional interventions, diagnostic and therapeutic challenges persist—particularly in socioeconomically disadvantaged settings. In this context, AI emerges as a promising tool to enhance diagnostic accuracy and personalize interventions. Previous studies have successfully used algorithms to detect graphic behavior patterns and adapt to individual needs through intelligent applications. However, AI use in the field of childhood handwriting remains limited, with many studies still in the experimental phase. The review will follow the methodological framework proposed by Arksey and O’Malley, complemented by the Joanna Briggs Institute and PRISMA-ScR guidelines. Relevant databases such as PubMed, Scopus, and Google Scholar will be searched, including literature without language or date restrictions. Data will be analyzed using narrative synthesis and thematic qualitative analysis. The ultimate aim is to synthesize current knowledge, establish an open-access categorized database, and provide evidence-based recommendations to guide the safe and effective use of AI in addressing these disorders. In addition, expert consultation will be included to integrate clinical and technological perspectives.