A Mobile ADHD Screening App for Primary School Children: A Pilot Study in Thai Primary Care

Abstract

Attention-deficit hyperactivity disorder (ADHD) is a common condition affecting children’s learning and behavior, with a high level of prevalence in Thailand. However, early detection remains challenging due to the limited number of screening tools for parents and teachers. The aim of this study was to develop the ADHD Scanning app, a mobile tool for early ADHD screening in primary schools based on the seven-color PBRI model (Traffic Light System). A mixed-methods approach was used in which the SNAP-IV scale was combined with the PBRI model and expert interviews. The completed app enables visual classification of the severity of ADHD symptoms through a seven-color system, educational modules, and pre- and postassessments, and offers a guidebook for ADHD support. It was piloted with 30 parents and teachers of children aged six to 12 and was found to have good content validity (IOC = 0.87) according to expert review. The ADHD Scanning app identified 47% of children as high risk (dark green) for inattention, 17% for hyperactivity/impulsivity (dark green), and 10% for oppositional behavior (dark green). Most children were classified as either normal (white) or at risk (pale green), with none classified as at severe risk. User satisfaction was very high (M = 4.54, SD = 0.50), with the highest scores for content accuracy (M = 4.67, SD = 0.50), design clarity (M = 4.63, SD = 0.56), and usability (M = 4.43, SD = 0.84). The ADHD Scanning app has significant potential as an accessible tool for early ADHD detection and education in schools and homes.