Measuring attention of ADHD patients by means of a computer game featuring biometrical data gathering

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Título: Measuring attention of ADHD patients by means of a computer game featuring biometrical data gathering
Autor/es: Teruel, Miguel A. | Sanchis, Javier | Ruiz-Robledillo, Nicolás | Albaladejo-Blázquez, Natalia | Ferrer-Cascales, Rosario | Trujillo, Juan
Grupo/s de investigación o GITE: Lucentia | Psicología Aplicada a la Salud y Comportamiento Humano (PSYBHE)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Universidad de Alicante. Departamento de Psicología de la Salud
Palabras clave: ADHD | Serious game | Attention | Assessment | Neuropsychology | Experiment | Children
Fecha de publicación: 23-feb-2024
Editor: Elsevier
Cita bibliográfica: Heliyon. 2024, 10(5): e26555. https://doi.org/10.1016/j.heliyon.2024.e26555
Resumen: ADHD is a neurodevelopmental disorder diagnosed mainly in children, marked by inattention and hyperactivity-impulsivity. The symptoms are highly variable, such as different ages of onset and potential comorbidities, contributing to frequent misdiagnoses. Professionals note a gap in modern diagnostic tools, making accurate identification challenging. To address this, recent studies recommend gamification for better ADHD diagnosis and treatment, though further research is essential to confirm its efficacy. This work aims to create a serious game, namely “Attention Slackline", to assess attention levels. The game, designed with expert input, requires players to concentrate on a specific point to recognize specific patterns while managing distractions. A controlled experiment tested its precision, and results were compared with established attention tests by a correlation analysis. Statistical analysis confirmed the game's validity, especially in tracking attention through correct responses and errors. Preliminary evidence suggests that “Attention Slackline" may serve as a credible instrument for the assessment of attentional capacities in individuals with ADHD, given that its outcomes have been empirically shown to correlate with those derived from a well-established attention assessment methodology.
Patrocinador/es: This work has been co-funded by the BALLADEER (PROMETEO/2021/088) project, a Big Data analytical plat-form for the diagnosis and treatment of Attention Deficit Hyperactivity Disorder (ADHD) featuring extended reality, funded by the ,Conselleria de Innovación, Universidades Ciencia y Sociedad Digital (Generalitat Valenciana), Grant RED2022-134656-T funded by MCIN/AEI/10.13039/501100011033 and Program for the Promotion of R + D + I (UAIND20-03B) by Vicerrectorado de Investigación y Transferencia de Conocimiento de la Universidad de Alicante, and by the AETHER-UA project (PID2020-112540RB-C43), a smart data holistic approach for context-aware data analytics: smarter machine learning for business modelling and analytics, funded by Spanish Ministry of Science and Innovation.
URI: http://hdl.handle.net/10045/141026
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e26555
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Revisión científica: si
Versión del editor: https://doi.org/10.1016/j.heliyon.2024.e26555
Aparece en las colecciones:INV - LUCENTIA - Artículos de Revistas
INV - PSYBHE - Artículos de Revistas

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