Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder: Protocol for a Nonrandomized Controlled Pilot Study

Abstract

Background Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders during childhood; however, the diagnosis procedure remains challenging, as it is nonstandardized, multiparametric, and highly dependent on subjective evaluation of the perceived behavior. Objective To address the challenges of existing procedures for ADHD diagnosis, the ADHD360 project aims to develop a platform for (1) early detection of ADHD by assessing the user’s likelihood of having ADHD characteristics and (2) providing complementary training for ADHD management. Methods A 2-phase nonrandomized controlled pilot study was designed to evaluate the ADHD360 platform, including ADHD and non-ADHD participants aged 7 to 16 years. At the first stage, an initial neuropsychological evaluation along with an interaction with the serious game developed (“Pizza on Time”) for approximately 30-45 minutes is performed. Subsequently, a 2-week behavior monitoring of the participants through the mADHD360 app is planned after a telephone conversation between the participants’ parents and the psychologist, where the existence of any behaviors characteristic of ADHD that affect daily functioning is assessed. Once behavior monitoring is complete, the research team invites the participants to the second stage, where they play the game for a mean duration of 10 weeks (2 times per week). Once the serious game is finished, a second round of behavior monitoring is performed following the same procedures as the initial one. During the study, gameplay data were collected and preprocessed. The protocol of the pilot trials was initially designed for in-person participation, but after the COVID-19 outbreak, it was adjusted for remote participation. State-of-the-art machine learning (ML) algorithms were used to analyze labeled gameplay data aiming to detect discriminative gameplay patterns among the 2 groups (ADHD and non-ADHD) and estimate a player’s likelihood of having ADHD characteristics. A schema including a train-test splitting with a 75:25 split ratio, k-fold cross-validation with k=3, an ML pipeline, and data evaluation were designed. Results A total of 43 participants were recruited for this study, where 18 were diagnosed with ADHD and the remaining 25 were controls. Initial neuropsychological assessment confirmed that the participants in the ADHD group showed a deviation from the participants without ADHD characteristics. A preliminary analysis of collected data consisting of 30 gameplay sessions showed that the trained ML models achieve high performance (ie, accuracy up to 0.85) in correctly predicting the users’ labels (ADHD or non-ADHD) from their gameplay session on the ADHD360 platform. Conclusions ADHD360 is characterized by its notable capacity to discriminate player gameplay behavior as either ADHD or non-ADHD. Therefore, the ADHD360 platform could be a valuable complementary tool for early ADHD detection. Trial Registration ClinicalTrials.gov NCT04362982; https://clinicaltrials.gov/ct2/show/NCT04362982 International Registered Report Identifier (IRRID) RR1-10.2196/40189

Technology-based solutions for behavior monitoring: lessons learned

“…Moreover, 43 participants were recruited to take part in the pilot study of the ADHD360 project (Pandria et al, 2022) (S5); 18 participants were diagnosed with ADHD while 25 participants were healthy controls. The ADHD360 platform and, in particular, its serious game "Pizza on Time" was explored as a tool for the early detection of ADHD characteristics and management of ADHD behavior.…”

“…The ADHD360 platform was developed in the context of the ADHD360 project funded by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH-CREATE-INNOVATE (grant Τ1ΕΔΚ-01680). The main focus of the project was to build an integrated platform that includes a serious game ("Pizza on Time" game) for the early detection of ADHD characteristics and a mobile application (mADHD360 app) for behavior monitoring (Pandria et al, 2022).…”

“…Within the ADHD360 platform, the mADHD360 application (Pandria et al, 2022), as the rational descendant of the WHAAM app, constitutes a progressive web app designed to run on smartphones, mobile devices, and tablets. It is dedicated to behavioral monitoring providing observation features to HPs, parents, and teachers to conduct FBA in a unified and easy-to-use way.…”

“…However, traditional monitoring tools commonly rely on pen-and-paper methods (Gualtieri and Johnson, 2005;Pandria et al, 2015) using expert observations and/or conducting surveys involving participants who interact with each other (Davila-Montero et al, 2021). Inherent obstacles of those methods include data loss, subjectivity bias, difficulty in synchronous monitoring at different settings, real-time recognition, and interpretation of behavior (Davila-Montero et al, 2021;Pandria et al, 2022). For addressing the limitations of existing approaches, we have designed and implemented a bundle of tools over the past few years, namely, the WHAAM application (Spachos et al, 2014), the ADHD360 (Pandria et al, 2022) platform, and the AffectLecture application (Siouli et al, 2017(Siouli et al, , 2020, in addition to exploiting the commercially available platform BrainHQ (Romanopoulou et al, 2017;Anagnostopoulou et al, 2021;Romanopoulou et al, 2021) setting different goals and targeting different populations.…”

“…Inherent obstacles of those methods include data loss, subjectivity bias, difficulty in synchronous monitoring at different settings, real-time recognition, and interpretation of behavior (Davila-Montero et al, 2021;Pandria et al, 2022). For addressing the limitations of existing approaches, we have designed and implemented a bundle of tools over the past few years, namely, the WHAAM application (Spachos et al, 2014), the ADHD360 (Pandria et al, 2022) platform, and the AffectLecture application (Siouli et al, 2017(Siouli et al, , 2020, in addition to exploiting the commercially available platform BrainHQ (Romanopoulou et al, 2017;Anagnostopoulou et al, 2021;Romanopoulou et al, 2021) setting different goals and targeting different populations. The WHAAM application enables the digital monitoring of Attention Deficit Hyperactivity Disorder (ADHD) behavior as well as the planning of an intervention and the statistical evaluation of its effectiveness (Spachos et al, 2014;Merlo et al, 2018) while the ADHD360 stands for an integrated platform that includes a serious game for early detection of ADHD characteristics and a mobile application for behavior monitoring.…”