Application of cognitive tests of change detection and spatial marking in CogLab software to diagnose children with attention deficit/hyperactivity disorder

Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders and efforts to improve its diagnostic methods continue. In this study, using CogLab software, a diagnostic model was developed and introduced to help psychologists as an auxiliary tool for diagnosing ADHD. In the context of a developmental and case-control project using targeted sampling in Rasht city, 93 children diagnosed with ADHD were selected by a pediatric psychiatry subspecialist. The parents of both groups (case and control) were also interviewed clinically and after completing the CSI-4 version of the Children's Disease Symptoms Questionnaire, their demographic information was collected. The control group consisted of 33 working students from Rasht schools without disorders were selected using the CSI-4 4th version of the Children's Disease Symptoms Questionnaire. Both groups responded to the change detection and spatial marking tests using the attention section of the CogLab software under the same conditions. Data were processed by SPSS-24. In the diagnosis analysis, the results showed that the ratio of the correct response to the detection of change in the so-so mode had the highest predictive power in the separation and differentiation of classes between the case and control groups, and the results of the diagnostic function in the cross-validation section were able to be found in both case and control groups. 80.6 percent of all people in the ADHD group (case) and also 72.7 percent of all people in the control group were correctly grouped; The change detection test and spatial marking in CogLab software platform can be used as an auxiliary tool in the service of psychologists to help the diagnosis process in children with ADHD.