Computerized cognitive retraining (ReadON.ai) among children diagnosed with attention deficit hyperactivity disorder

Area of Science:

• Neuroscience
• Developmental Psychology
• Educational Technology

Background:

• Attention Deficit Hyperactivity Disorder (ADHD) affects 8% of children globally, presenting cognitive deficits that impact emotional and behavioral adjustment.
• Traditional ADHD treatments often fall short in addressing core cognitive domains, necessitating innovative interventions.
• Computerized cognitive retraining, specifically using ReadON.ai, is an emerging technology with potential for ADHD management, though its efficacy requires further study.

Purpose of the Study:

• To assess the feasibility of computerized cognitive retraining (ReadON.ai) for enhancing cognitive abilities in children diagnosed with ADHD.

Main Methods:

• A pre- and post-intervention study involving six children (7-11 years) diagnosed with ADHD.
• Participants completed 30 hours of ReadON.ai cognitive training over ten weeks, targeting attention, working memory, learning, perception, and reasoning.
• Cognitive functions were assessed using Conners' 4 Parent version and ReadON.ai CSA before and after the intervention.

Main Results:

• Significant improvements were observed in attention, concentration, working memory, learning, memory, perception, and reasoning post-intervention (P < 0.001).
• Reductions in hyperactivity, impulsivity, emotional dysregulation, and improvements in schoolwork and peer interactions were noted.
• Effect sizes ranged from medium to large across most assessed cognitive and behavioral domains.

Conclusions:

• Computerized cognitive retraining with ReadON.ai is a feasible and effective method for enhancing key cognitive abilities in children with ADHD.
• This technology offers a promising supplementary approach to traditional ADHD interventions, targeting critical cognitive deficits.