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新冠疫情爆发前后韩国青少年成瘾性网络游戏使用情况:2018年与2020年潜在概况比较

Addictive Internet Gaming Usage among Korean Adolescents before and after the Outbreak of the COVID-19 Pandemic: A Comparison of the Latent Profiles in 2018 and 2020.

作者信息

Kim Dongil, Lee Junwon

机构信息

Department of Education, College of Education, Seoul National University, Seoul 08826, Korea.

出版信息

Int J Environ Res Public Health. 2021 Jul 7;18(14):7275. doi: 10.3390/ijerph18147275.

DOI:10.3390/ijerph18147275
PMID:34299725
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8305932/
Abstract

Since the outbreak of the COVID-19 pandemic, the heightened risk of school closures and mental disorders has made adolescents particularly vulnerable to developing internet gaming disorder (IGD). There have been reports of increased time spent playing games on the internet among adolescents during the pandemic, and the risk of developing IGD may be higher for adolescents in South Korea as the majority of them play games on the internet. However, to the best of our knowledge, no studies have examined the impact of the pandemic on adolescents' internet gaming behavior in South Korea. This study aimed to explore the different profiles of addictive internet gaming behavior among adolescents before and after the outbreak of the COVID-19 pandemic and examine how the pandemic influenced addictive internet gaming usage and time spent playing games on the internet. Nationally representative survey data from the Ministry of Gender Equality and Family with 3040 and 2906 responses from 2018 and 2020, respectively, were analyzed. Using seven factors of a maladaptive gaming usage scale (tolerance, withdrawal, excessive usage, control impairment, compulsive usage, neglecting daily activity, and gaming despite negative consequence), a four-profile model was selected in both 2018 and 2020 for latent profile analysis: 'casual' gamer, 'moderate' gamer, 'potential-risk' gamer and 'addictive' gamer. The results from the two-way ANCOVA showed significant interaction between the cohorts (2018 cohort vs. 2020 cohort) and the four profiles on addictive internet gaming usage (F = 119.747, < 0.001, η = 0.05), including time spent playing internet games on a PC (F = 22.893, < 0.001, η = 0.013), and time spent playing games on a mobile phone (F = 3.245, < 0.05, η = 0.02). The results indicated that the increase of addictive internet gaming usage and gameplay time differed by profile. The results imply that the increase in gameplay time was higher for profiles with higher scores in addictive internet gaming usage for internet games played on a PC while the relationship was not obvious for games played on a mobile phone. Despite the statistical significance, there was only 1.2% to 4.9% of mean difference in addictive internet gaming usage between the 2018 and 2020 cohorts, which implies little clinical significance. While adolescents of the four profiles showed no significant signs of increased addictive internet gaming usage, the addictive gamer profile demonstrated a significant increase in game time after COVID-19.

摘要

自新冠疫情爆发以来,学校关闭和出现精神障碍的风险增加,这使得青少年特别容易患上网络游戏障碍(IGD)。有报道称,疫情期间青少年上网玩游戏的时间增加,而韩国的青少年患IGD的风险可能更高,因为他们大多数人都在网上玩游戏。然而,据我们所知,尚无研究考察疫情对韩国青少年网络游戏行为的影响。本研究旨在探讨新冠疫情爆发前后青少年成瘾性网络游戏行为的不同特征,并研究疫情如何影响成瘾性网络游戏的使用情况以及上网玩游戏的时间。我们分析了来自性别平等和家庭部的具有全国代表性的调查数据,2018年和2020年分别有3040份和2906份回复。使用适应不良游戏使用量表的七个因素(耐受性、戒断反应、过度使用、控制障碍、强迫性使用、忽视日常活动以及不顾负面后果仍继续游戏),在2018年和2020年都选择了一个四特征模型进行潜在特征分析:“休闲”玩家、“中度”玩家、“潜在风险”玩家和“成瘾”玩家。双向协方差分析的结果显示,不同队列(2018年队列与2020年队列)与成瘾性网络游戏使用的四个特征之间存在显著交互作用(F = 119.747,< 0.001,η = 0.05),包括在电脑上玩网络游戏的时间(F = 22.893,< 0.001,η = 0.013)以及在手机上玩游戏的时间(F = 3.245,< 0.05,η = 0.02)。结果表明,成瘾性网络游戏使用和游戏时长的增加因特征而异。结果意味着,对于在电脑上玩的网络游戏,成瘾性网络游戏使用得分较高的特征,其游戏时长的增加幅度更大,而对于在手机上玩的游戏,这种关系并不明显。尽管具有统计学意义,但2018年和2020年队列之间成瘾性网络游戏使用的平均差异仅为1.2%至4.9%,这意味着临床意义不大。虽然这四个特征的青少年成瘾性网络游戏使用增加没有显著迹象,但“成瘾”玩家特征在新冠疫情后游戏时间有显著增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/f2a28ff9ecb5/ijerph-18-07275-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/fec26aca008b/ijerph-18-07275-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/dad77a3bcd46/ijerph-18-07275-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/6a4c571ed62b/ijerph-18-07275-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/f25f11c4f1d8/ijerph-18-07275-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/0fe3e8a9e22d/ijerph-18-07275-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/f2a28ff9ecb5/ijerph-18-07275-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/fec26aca008b/ijerph-18-07275-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/dad77a3bcd46/ijerph-18-07275-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/6a4c571ed62b/ijerph-18-07275-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/f25f11c4f1d8/ijerph-18-07275-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/0fe3e8a9e22d/ijerph-18-07275-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa88/8305932/f2a28ff9ecb5/ijerph-18-07275-g006.jpg

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