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

Journal: Journal of behavioral addictions
PMID: 39576295

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.

Authors

  • Vasileios Stavropoulos
    College of Health and Biomedicine, Royal Melbourne Institute of Technology (RMIT), Australia; Department of Psychology, University of Athens, Athens, Greece.
  • Maria Prokofieva
    Institute for Health and Sport, Victoria University, Melbourne, Australia.
  • Daniel Zarate
    College of Health and Biomedicine, Royal Melbourne Institute of Technology (RMIT), Australia. Electronic address: Daniel.zarate@live.vu.edu.au.
  • Michelle Colder Carras
    3Bloomberg School of Public Health, John Hopkins University, Baltimore, USA.
  • Rabindra Ratan
    4Michigan State University, USA.
  • Rachel Kowert
    5Psychology Research Institute, Faculty of Social Studies, Masaryk University, Brno, Czech Republic.
  • Bruno Schivinski
    7School of Media and Communication, RMIT University, Australia.
  • Tyrone L Burleigh
    School of Health and Biomedical Sciences, RMIT University, Melbourne, Australia. Electronic address: tyrone.l.burleigh@gmail.com.
  • Dylan Poulus
    Faculty of Health, Southern Cross University, Queensland, Australia.
  • Leila Karimi
    1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia.
  • Angela Gorman-Alesi
    10Catholic Care Victoria, Australia.
  • Taylor Brown
    1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia.
  • Rapson Gomez
    1Department of Psychology, Applied Health, School of Health and Biomedical Sciences, RMIT University, Australia.
  • Kaiden Hein
    School of Health and Biomedical Sciences, RMIT University, Melbourne, Australia.
  • Nalin Arachchilage
    11School of Computing, RMIT University, Australia.
  • Mark D Griffiths
    2International Gaming Research Unit, Psychology Department, Nottingham Trent University, 50 Shakespeare Street, Nottingham, NG1 4FQ UK.

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