Machine Learning(s) in gaming disorder through the user-avatar bond: A step towards conceptual and methodological clarity.

Autor: Stavropoulos V; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Prokofieva M; 2Victoria University, Australia., Zarate D; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Colder Carras M; 3Bloomberg School of Public Health, John Hopkins University, Baltimore, USA., Ratan R; 4Michigan State University, USA., Kowert R; 5Psychology Research Institute, Faculty of Social Studies, Masaryk University, Brno, Czech Republic.; 6Department of Communication, University of Münster, Münster, Germany., Schivinski B; 7School of Media and Communication, RMIT University, Australia., Burleigh TL; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Poulus D; 8Physical Activity, Sport and Exercise Research Theme, Faculty of Health, Southern Cross University, Gold Coast, Australia.; 9Manna Institute, Southern Cross University, Gold Coast, Australia., Karimi L; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Gorman-Alesi A; 10Catholic Care Victoria, Australia., Brown T; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Gomez R; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Hein K; 1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia., Arachchilage N; 11School of Computing, RMIT University, Australia., Griffiths MD; 12International Gaming Research Unit, Psychology Dept, Nottingham Trent University, UK.
Jazyk: angličtina
Zdroj: Journal of behavioral addictions [J Behav Addict] 2024 Nov 22; Vol. 13 (4), pp. 894-900. Date of Electronic Publication: 2024 Nov 22 (Print Publication: 2024).
DOI: 10.1556/2006.2024.00063
Abstrakt: In response to our study, the commentary by Infanti et al. (2024) raised critical points regarding (i) the conceptualization and utility of the user-avatar bond in addressing gaming disorder (GD) risk, and (ii) the optimization of supervised machine learning techniques applied to assess GD risk. To advance the scientific dialogue and progress in these areas, the present paper aims to: (i) enhance the clarity and understanding of the concepts of the avatar, the user-avatar bond, and the digital phenotype concerning gaming disorder (GD) within the broader field of behavioral addictions, and (ii) comparatively assess how the user-avatar bond (UAB) may predict GD risk, by both removing data augmentation before the data split and by implementing alternative data imbalance treatment approaches in programming.
Databáze: MEDLINE