Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder among children resulting in disturbances in their daily functioning. Virtual reality (VR) and machine learning technologies, such as deep learning (DL) application, are promising diagnostic tools for ADHD in the near future because VR provides stimuli to replace real stimuli and recreate experiences with high realism. It also creates a playful virtual environment and reduces stress in children. The DL model is a subset of machine learning that can transform input and output data into diagnostic values using convolutional neural network systems. By using a sensitive and specific ADHD-VR diagnostic tool prototype for children with DL model, ADHD can be diagnosed more easily and accurately, especially in places with few mental health resources or where teleconsultation is possible. To date, several virtual reality-continuous performance test (VR-CPT) diagnostic tools have been developed for ADHD; however, they do not include a machine learning or deep learning application. A diagnostic tool development study needs a trustworthy and applicable study design and conduct to ensure the completeness and transparency of the report of the accuracy of the diagnostic tool. The proposed four-step method is a mixed-method research design that combines qualitative and quantitative approaches to reduce bias and collect essential information to ensure the trustworthiness and relevance of the study findings. Therefore, this study aimed to present a brief review of a ADHD-VR digital game diagnostic tool prototype with a DL model for children and the proposed four-step method for its development.

The aim of this study was to develop an Indonesian computer-based game prototype, including feasibility testing, targeted on attention deficit/hypersensitivity disorder (ADHD) clinical symptoms and executive function. The study comprised five steps. The first to third steps used an exploratory qualitative research design. The Delphi technique with FGD was applied to collect qualitative data. During the study, seven experts participated in ten FGDs. Feasibility testing was conducted as a one group pre- and post-test design that included ten children with drug-naïve ADHD without other mental or physical disorders. Feasibility data were collected before and after 20 training sessions with the Indonesian computer-based game prototype. The framework analysis was performed for qualitative data. Quantitative data were analyzed using the paired t-test, Pearson's correlation and Spearman's rank-order correlation. Outputs of the exploratory qualitative study were the Indonesian computer-based game prototype constructs and general agreements of the prototype,. The Indonesian computer-based game prototype construct comprised six components: reward-related processing, control inhibition, improved sustained attention, specific timing, increased arousal, and improved emotional regulation. After 20 sessions of training, several indicators decreased significantly, such as CATPRS-teacher rating (18.5 [5.31] vs. 12.9 [5.51], p = 0.047), BRIEF-GEC (64.80 [10.21] vs. 57.50 [7.51], p = 0.02), BRIEF-MI (66.1 [7.61] vs. 58.4 [7.56], p = 0.014), BRIEF-Initiate (66.6 [10.15] vs. 54.1 [6.49], p = 0.008), BRIEF-Working Memory (68.0 [6.89] vs. 60.9 [10.05], p = 0.02), and BRIEF-Organization of Material (60.7 [12.88] vs. 49.3 [11.79], p = 0.04). There was a low to moderate correlation between CATPRS-teacher and -parent rating and several BRIEF domains. Feasibility testing output also included the training procedure guideline. The present study indicated that the Indonesian computer-based game prototype could be used as a framework to develop a fixed computer-based game intervention for children with ADHD. However, further randomized controlled studies need to be conducted to show its effectiveness.

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