Corrigendum to: Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.

IF 6.6 1区 医学 Q1 PSYCHIATRY Journal of Behavioral Addictions Pub Date : 2024-11-22 DOI:10.1556/2006.2024.30000
Vasileios Stavropoulos, Daniel Zarate, Maria Prokofieva, Noirin Van de Berg, Leila Karimi, Angela Gorman Alesi, Michaella Richards, Soula Bennet, Mark D Griffiths
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更正:通过用户与头像之间的联系深度学习游戏障碍:使用机器学习的纵向研究。
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来源期刊
CiteScore
12.30
自引率
7.70%
发文量
91
审稿时长
20 weeks
期刊介绍: The aim of Journal of Behavioral Addictions is to create a forum for the scientific information exchange with regard to behavioral addictions. The journal is a broad focused interdisciplinary one that publishes manuscripts on different approaches of non-substance addictions, research reports focusing on the addictive patterns of various behaviors, especially disorders of the impulsive-compulsive spectrum, and also publishes reviews in these topics. Coverage ranges from genetic and neurobiological research through psychological and clinical psychiatric approaches to epidemiological, sociological and anthropological aspects.
期刊最新文献
Corrigendum to: Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning. Machine Learning(s) in gaming disorder through the user-avatar bond: A step towards conceptual and methodological clarity. User-avatar bond as diagnostic indicator for gaming disorder: A word on the side of caution. Long-term changes on behavioral addictions symptoms among adults with attention deficit hyperactivity disorder treated with methylphenidate. Mainland China's 2021 restrictions on under-18s' video game time were imposed when older 2019 restrictions already applied: Omitting the historical regulatory context is misleading.
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