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Published (Version of record)CC BY-NC V4.0, Open Access
Published (Version of record)CC BY-NC V4.0, Open
Journal article
Machine Learning(s) in gaming disorder through the user-avatar bond: A step towards conceptual and methodological clarity: Reply to: User-avatar bond as diagnostic indicator for gaming disorder: A word on the side of caution (2024)
Journal of behavioral addictions, Vol.13(4), pp.894-900
22/11/2024
PMCID: PMC11737409
PMID: 39576295
Appears in Recent Faculty of Health Publications
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Abstract
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.
Details
- Title
- Machine Learning(s) in gaming disorder through the user-avatar bond: A step towards conceptual and methodological clarity
- Creators
- Vasileios Stavropoulos - RMIT UniversityMaria Prokofieva - Victoria UniversityDaniel Zarate - RMIT UniversityMichelle Colder Carras - University of BaltimoreRabindra Ratan - Michigan State UniversityRachel Kowert - Masaryk UniversityBruno Schivinski - RMIT UniversityTyrone L. Burleigh - RMIT UniversityDylan Poulus - Southern Cross UniversityLeila Karimi - RMIT UniversityAngela Gorman-Alesi - Christian Heritage CollegeTaylor Brown - RMIT UniversityRapson Gomez - RMIT UniversityKaiden Hein - RMIT UniversityNalin Arachchilage - School of Computing, RMIT University, AustraliaMark D. Griffiths - Nottingham Trent University
- Publication Details
- Journal of behavioral addictions, Vol.13(4), pp.894-900
- Publisher
- AKJournals
- Number of pages
- 7
- Grant note
- Australian Research Council, Discovery Early Career Researcher Aw; Australian Research Council HDR students office of the School of Health and Biomedical Sciences of RMIT University
- Identifiers
- 991013237912702368
- Copyright
- © 2024 The Author(s) This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permist unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes - if any - are indicated.
- Academic Unit
- Human Sciences; Faculty of Health
- Language
- English
- Resource Type
- Journal article