Developing attention deficits/hyperactivity disorder-virtual reality diagnostic tool with machine learning for children and adolescents - Wiguna, Tjhin; Bahana, Raymond; Dirgantoro, Bayu; Minayati, Kusuma; Teh, Sylvie Dominic; Ismail, Raden Irawati; Kaligis, Fransiska; Wigantara, Ngurah Agung (Frontiers in Psychiatry, 2022)
Virtual reality is a significant technology that can present a virtual immersive environment; it can provide an illusion of participation in an artificial milieu for children with ADHD. This study aimed to develop an ADHD-VR diagnostic tool construct, and using the construct to develop a diagnostic tool with a machine learning application. This was an exploratory qualitative study and consisted of two stages. The first stage of the study applied the Delphi technique, and the goal was to translate ADHD symptoms based on DSM 5 diagnostic criteria into concrete behavior that can be observed among children in a classroom setting. The second stage was to finalize the construct based on the first-stage results through serial focus group discussions. The results were transformed into concrete activities that could be applied in the programming of the ADHD-VR diagnostic tool. First-stage data analysis was performed using Microsoft Excel for Mac. Qualitative data were analyzed using conceptual content analysis. From the first stage of the study, there were 13 examples of student behaviors that received more than 75% totally agreed or agreed from the experts. The construct of the ADHD-VR diagnostic tool consisted of three domains and was divided into six sub-domains, i.e. reward-related processing, emotional lability, inhibitory, sustained attention, specific timing of playing in order, and arousal. In conclusion, the results of this study can be used as a reference for future studies in a similar context and content, that is, the ADHD-VR diagnostic tool with machine learning based on the constructed RDC.