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The Role of Context in Online Gaming Excess and Addiction: Some Case Study Evidence

  • Published: 07 July 2009
  • Volume 8 , pages 119–125, ( 2010 )

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  • Mark D. Griffiths 1  

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Research into online gaming addiction is a relatively new area of psychological study. Furthermore, there are studies that have claimed that online gaming addiction may be addictive because of self-report accounts of very excessive use of up to 80 h a week. This study uses data from two case studies to highlight the role of context in distinguishing excessive gaming from addictive gaming. Both of the gamers in this study claimed to be playing for up to 14 h a day yet and although they were behaviorally identical in terms of their game playing, they were very different in terms of psychological motivation and the meaning and experience of gaming within their lives. It is argued that one of the players appears to be genuinely addicted to online gaming but that the other player is not based on context and consequences. The two cases outlined highlight the importance of context in the life of a gamer and demonstrates that excessive gaming does not necessarily mean that a person is addicted. It is argued that online gaming addiction should be characterized by the extent to which excessive gaming impacts negatively on other areas of the gamers’ lives rather than the amount of time spent playing. It is also concluded that an activity cannot be described as an addiction if there are few (or no) negative consequences in the player’s life even if the gamer is playing 14 h a day.

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Allison, S. E., von Wahlde, L., Shockley, T., & Gabbard, G. O. (2006). The development of the self in the era of the Internet and role-playing fantasy games. American Journal of Psychiatry, 163 , 381–385.

Article   PubMed   Google Scholar  

Block, J (2007). Pathological computer game use. Psychiatric Times , 24(3). Located at: http://www.psychiatrictimes.com/display/article/10168/55406?pageNumber=2 (Last accessed March 5, 2009)

Chappell, D., Eatough, V. E., Davies, M. N. O., & Griffiths, M. D. (2006). EverQuest —It’s just a computer game right? An interpretative phenomenological analysis of online gaming addiction. International Journal of Mental Health and Addiction, 4 , 205–216.

Article   Google Scholar  

Chen, V. H., Duh, H. B., Phuah, P. S. K., & Lam, D. Z. Y. (2006). Enjoyment or engagement? Role of social interaction in playing massively multiplayer online role-playing games (MMORPGS). Lecture Notes in Computer Science, 4161 , 262–267.

Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers. CyberPsychology and Behavior, 10 , 575–583.

Griffiths, M. D. (1991). Amusement machine playing in childhood and adolescence: a comparative analysis of video games and fruit machines. Journal of Adolescence, 14 , 53–73.

Article   CAS   PubMed   Google Scholar  

Griffiths, M. D. (2000). Does internet and computer “addiction” exist? Some case study evidence. CyberPsychology and Behavior, 3 , 211–218.

Griffiths, M. D. (2005a). A “components” model of addiction within a biopsychosocial framework. Journal of Substance Use, 10 , 191–197.

Griffiths, M. D. (2005b). The relationship between gambling and videogame playing: a response to Johansson and Gotestam. Psychological Reports, 96 , 644–646.

Griffiths, M. D. (2008). Diagnosis and management of video game addiction. New Directions in Addiction Treatment and Prevention, 12 , 27–41.

Google Scholar  

Griffiths, M. D., & Hunt, N. (1998). Dependence on computer games by adolescents. Psychological Reports, 82 , 475–480.

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004a). Demographic factors and playing variables in online computer gaming. CyberPsychology and Behavior, 7 , 479–487.

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004b). Online computer gaming: a comparison of adolescent and adult gamers. Journal of Adolescence, 27 , 87–96.

Grüsser, S. M., Thalemann, R., & Griffiths, M. D. (2007). Excessive computer game playing: evidence for addiction and aggression? Cyberpsychology and Behavior, 10 , 290–292.

Hussain, Z. & Griffiths, M.D. (2009). Excessive use of Massively Multi-Player Online Role-Playing Games: A pilot study. International Journal of Mental Health and Addiction , in press.

Keepers, G. A. (1990). Pathologicical preoccupation with video games. Journal of the American Academy of Child and Adolescent Psychiatry, 29 , 49–50.

Kuczmierczyk, A. R., Walley, P. B., & Calhoun, K. S. (1987). Relaxation training, in vivo exposure and response-prevention in the treatment of compulsive video-game playing. Scandinavian Journal of Behaviour Therapy, 16 , 185–190.

Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2009). Development and validation of a game addiction scale for adolescents. Media Psychology, 12 , 77–95.

Ng, B. D., & Wiemer-Hastings, P. (2005). Addiction to the internet and online gaming. CyberPsychology and Behavior, 8 , 110–113.

Smahel, D., Blinka, L., & Ledabyl, O. (2008). Playing MMORPGs: connections between addiction and identifying with a character. CyberPsychology and Behavior, 11 , 1–4.

Wan, C., & Chiou, W. (2006a). Psychological motives and online games addiction: a test of flow theory and humanistic needs theory for Taiwanese adolescents. CyberPsychology and Behavior, 9 , 317–324.

Wan, C., & Chiou, W. (2006b). Why are adolescents addicted to online gaming? An interview study in Taiwan. CyberPsychology and Behavior, 9 , 762–766.

Wang, C., & Wang, C. (2008). Helping others in online games: prosocial behavior in cyberspace. CyberPsychology and Behavior, 11 , 344–346.

Wood, R. T. A., Griffiths, M. D., & Parke, A. (2007). Experiences of time loss among videogame players: an empirical study. CyberPsychology and Behavior, 10 , 45–56.

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Griffiths, M.D. The Role of Context in Online Gaming Excess and Addiction: Some Case Study Evidence. Int J Ment Health Addiction 8 , 119–125 (2010). https://doi.org/10.1007/s11469-009-9229-x

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Published : 07 July 2009

Issue Date : January 2010

DOI : https://doi.org/10.1007/s11469-009-9229-x

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Video Gaming Addiction: A Case Study of China and South Korea

Posted by Ryan, Amanda | Dec 13, 2021 | American Politics(B) , Asia(B) , China(B) , U.S.(B) | 0 |

Video Gaming Addiction: A Case Study of China and South Korea

To wrap up summer vacation, the two leading countries combating internet and gaming addiction—China and South Korea—took a step in diverging directions. This raises the issue of which country serves as a better model for the U.S. government and American gaming companies. With both countries entering the year enforcing similar policies of reducing the amount of play time available to minors, it came as a surprise when China’s increase in limitations was met alongside South Korea’s plan to abolish the harsh restraints. Ultimately, South Korea recognized the flaws in their previous law and is modifying their game plan to include less restrictions and encourage more self-regulation. After reviewing scholarship and research studies which analyzed the previous laws enacted by China and South Korea, the latter’s new, more flexible approach appears to be most promising for the U.S. to take into consideration.

Douglas Gentile, developmental psychologist and the Director of Research for the National Institute on Media and the Family, estimated that over 8.5 percent of children and teenagers—roughly 3 million Americans—exhibit multiple signs of gaming addiction [1]. Currently in the Western world, video game-related regulations are limited to rating systems which evaluate content and maturity-levels rather than the overuse of gaming [2]. As video game addiction becomes increasingly prevalent, understanding, and ultimately comparing, the different prevention approaches is vital in protecting the health and development of younger generations.

What is Gaming Addiction?

Video gaming has beneficial and adverse effects on the cultural attitudes, psychological development, and lifestyle choices of young gamers [3]. For instance, a 2009 study in the Annual Review of Cybertherapy and Telemedicine found gaming can alleviate stress and depression; Dr. Daphen Maurer of the Visual Development Lab discovered gaming can improve eyesight and increase dopamine levels; and cognitive neuroscientists at the University of Rochester found video games can enhance decision-making skills [4]. Especially during the recent pandemic, where isolation and a lack of social interaction was prominent, the ability to engage with others via gaming provided much needed “social connection, escapism and relief for millions of kids and teens” [5].

Although the evolution of technology and the internet has brought numerous benefits, many negative ramifications have been uncovered as well. One of the most significant impacts of problematic internet-use gaining momentum is the onslaught of video gaming addiction. As a subset of internet addiction, video gaming addiction is often when gaming is taken to the extreme—ultimately impairing an individual’s ability to function either socially, academically, or financially [6]. In 2014, a study by Zhejiang Normal University discovered that gaming addiction can lead to “lower volumes of gray and white brain matter,” which can cause impairment in decision-making, regulating emotions, and impulse control [7]. Likewise, the comorbidity rate of the gaming disorder with depression, anxiety, and ADHD is significantly high, as many young gamers use gaming as a coping mechanism [8].

While the classification of video gaming addiction as a mental illness is somewhat controversial, organizations have recently spoken up about the issue. In 2013, the American Psychiatric Association (APA) included an Internet Gaming Disorder in the DSM-5 , and, in 2018, the World Health Organization (WHO) stated Gaming Disorder (GD) will be listed in the 11 th addition of the International Classification of Diseases [9]. With nearly three billion people playing video games worldwide, 3-4 percent of them—more than 60 million gamers—are likely to be suffering from gaming disorder [10].

In China, problematic video gaming has been recognized as a public health crisis [11]. In 2007, around 14 percent of Chinese adolescent internet users—about 10 million teenagers—met the diagnostic criteria for internet addiction [12]. According to the China Internet Network Information Center, this number increased 16 percent by 2018, with over 30 percent of minors suffering from gaming disorder [13]. With the issue growing in severity, China placed video gaming addiction on par with substance-abuse and drug addictions, labeling the activity as “spiritual opium” [14].

Similarly, South Korea considers internet addiction as one of the country’s most critical health issues [15]. By 2015, internet usage in South Korean households rose to 85.1 percent across all ages [16]. Comparable to the duration of a part-time job, the average South Korean teen spends over 23 hours per week playing video games [17]. In Seoul, the capital of South Korea, a common leisure activity for youths is to stop by a ‘PC bang’—an internet gaming room or cafe, typically open 24 hours, where players have access to comfortable seating and fast computers for a dollar an hour [18].

Following trend lines for the addiction in South Korea, in 2012, an estimated 2.55 million people were addicted to their smartphones and the internet [19]. For adolescents in particular, around 12.5 percent of teenagers were at risk for internet addiction disorder in 2014 [20]. And in 2019, the latest government-issued survey revealed over 20 percent of South Korea’s population—nearly 10 million citizens—were now at risk for the addiction [21]. Due to the isolating nature of the COVID-19 pandemic, many countries have reported an uptake in the amount of time minors spent gaming, suggesting a probable increase in problematic gaming for South Korean adolescents [22].

Initial Prevention Response Plans

International response and prevention plans vary, with some countries authorizing harsher, more hands-on restrictions than others. But how effective are these various responses in curbing behavioral addictions? China and South Korea provide case studies of possible responses and their likely consequences.

From 2000 until 2015, China banned the production and sale of popular gaming consoles—including Xbox and PlayStation—in an attempt to reduce the likelihood of children developing addictions [23]. However, many players worked around this obstacle by illegally purchasing consoles, or simply turning towards PC and mobile games instead. Shortly after the ban was lifted, their government placed restrictions and censors on the “harmful attributes” in video games, including the addictive qualities of in-game rewards and achievements, as well as the portrayal of violence [24]. Specifically, China introduced an Online Game Addiction Prevention System (Fatigue System) in 2007, which targeted the addictive qualities of games [25]. In this system, as the time a person spent gaming increased, the number of rewards they could obtain decreased and pop-up warnings of unhealthy playtime appeared in an effort to limit the gamer’s desire to keep playing. However, as mentioned in sections below, this system proved largely ineffective and was ultimately discarded [26].

As for treatment measures, China established centers aimed at rehabilitation to address problematic gaming, such as at the General Hospital of Beijing Military Region’s Internet Addiction Treatment Center [27]. Likewise, to further reduce the negative impact of the internet on minors, China passed the Minors Internet Protection Ordinance in 2016, which limited nighttime gaming, provided education to guide players, and required gaming companies to adhere to anti-addiction parameters [28]. Yet, with more minors continuing down a path towards addiction, a revision for the law was required [29]. In 2019, China went a step further and created tighter time restraints on how long minors were allowed to play video games—limiting players to 1.5 hours on weekdays, 3 hours on weekends and holidays, and only during daytime hours [30].

With over 720 million gamers by 2021, gaming culture prospered in China, leading the country towards becoming the largest market in the video gaming industry [31]. By having such a substantial portion of the population active in gaming, and with many of the previous restrictions easily circumvented, the need for an effective method in China to stop addiction became even more crucial.

South Korea:

In response to the rise in internet-related addictions, South Korea established the Internet Addiction Prevention & Resolution Comprehensive Plan in 2010 [32]. Led by the National Safety Administration-affiliated agency of the MSIP, the primary goal was to establish intervention systems for problematic game and internet use before addiction manifested [33]. Although, while posing many benefits for minors at risk, these approaches were also criticized for the lack of “inter-agencies collaboration and clinical conceptualization” [34].

To assist those already effected, many treatment centers were founded to support the recovery of youths suffering from gaming addiction [35]. One of these programs is the Jump Up Internet Rescue School, where internet or online gaming addicted children are sent to a camp designed for rehabilitation—guiding minors in their journey through adapting healthier hobbies and learning new coping mechanisms [36].

In 2011, South Korea passed the Youth Protection Act, also known as the Shutdown Law or “Cinderella Law,” restricting the hours minors could play video games [37]. Under this law, those under the age of 16 were unable to access online games between midnight and 6am in an effort to promote healthy sleeping habits, increase productivity and attentiveness in the classroom, and prevent the likelihood of addictions to develop [38].

2021 Modifications in Gaming Prevention

Although both countries enforced strict video gaming strictions in the past, their policies deviated in 2021: China pushing for even stricter regimens on gaming, while South Korea is tearing down their shutdown law in favor of more flexible moderating and a stronger emphasis on health services. For China, authorities claim that rolling out firmer measures to limit minors’ gaming exposure come from a desire to safeguard their physical and mental health—as well as to satisfy a concern from parents that the old policy was insufficient [39]. On the other hand, South Korea is moving in the opposite direction in hopes of “respecting the rights of the youth and encourage[ing] healthy home education,” and to break away from the shutdown law’s ineffectiveness [40].

Released by the National Press and Publication Association (NPPA), China tightened the 2019 restrictions of online gaming for minors to one hour per day—8 PM to 9 PM—on Friday, weekends, and public holidays [41]. In addition to strict time restrictions, identification systems were installed to ensure the rules are followed, essentially forcing minors to enter identification—such as real names, government-issued ID documents, or identification numbers—before playing [42]. However, since many gamers under 18 attempt to bypass this limitation by acquiring fake ID numbers or using VPNs, the policy also requires gamers to register their ID number for fact-checking in the national citizen database [43]. Following suit, gaming companies have launched new methods to increase the likelihood of player cooperation. Tencent, one of China’s major gaming companies, recently introduced “facial recognition technology and an algorithm that identifies underage players” [44].

Issues with China’s 2021 Modification

China is asserting a strong association of high playing time with addiction—where more hours spent gaming equals addiction. However, China’s emphasis on time as the determining factor leading to addiction is misguided [45]. In 2018, a study published in the Journal of Behavioral Addictions by Kiraly et al., analyzed the effectiveness of policy responses on problematic video game use. The study argued that the strict policy and regulation approaches limiting playtime “were not sufficiently effective” and henceforth called for more “integrative approaches” for improvement [46]. Additionally, another data set found that gaming time is “weakly associated with negative psychological factors” often found in problematic use [47].

According to WHO, the diagnostic criteria for the “gaming disorder” does not include a specific amount of playtime [48]. Rather, that gaming must cause distress, impairment in the gamer’s life and ability to function, and typically last for at least one year [49]. Like with many behaviors, there is a substantial difference between those who are simply enthusiastic about the activity and want to dedicate time towards it with those who are addicted to it. Ultimately, all behaviors exist on a continuum, and the point where an individual falls isn’t fully decided according to the amount of time allotted to the behavior.

Instead, the threshold differentiating regular gaming (unproblematic behavior) from a gaming disorder (problematic behavior) resides with the effect the activity has on the gamer—as well as the gamer’s response to those outcomes [50]. In other words, the amount of time a person spends breaking blocks in Minecraft , farming crops in Stardew Valley , or leading revolutions in Homefront doesn’t guarantee the development of an addictive behavioral disorder. Alternatively, if a person is so absorbed in their gaming that they repeatedly forget to pick up their kids from daycare, sneak in round after round of solitaire in the office instead of finishing a report, or demonstrate their gaming is negatively impacting their life on another significant level—and continue to game regardless—then that behavior can enter the realm of addiction. By itself, the amount of time spent gaming isn’t a reliable predictor of problematic use; therefore, for China to implement harsher time restraints as the primary driver of their response plan to video gaming addiction demonstrates their shortcomings in addressing the heart of this issue.

Another failure with China’s law is that it only effects the gameplay of minors. However, recent data has proven that the median age of gamers is 24, and a growing demographic in gaming addiction is people in their 20s and 30s [51]. According to a specialist in gaming addiction, adults often turn to video gaming for the same reason teens do: to escape the harshness of reality—unemployment, isolation, and relationship issues [52]. Hence, to properly address all vulnerable groups susceptible to gaming addiction, an approach geared towards more than just minors is needed.

Similar Issues with South Korea’s 2011 Law

Regarding South Korea’s shutdown law, Jiyun Choi et al. in the Journal of Adolescent Health analyzed data collected from the Korea Youth Risk Behavior Web-based survey from 2011 to 2015, concluding the “shutdown policy had practically insignificant effects in reducing Internet use for target adolescents” [53]. Among middle school students, the effects of the initiative were null on internet abuse, and only increased sleep duration by a mere 2 minutes [54]. In fact, the shutdown law’s strategy was indicated to have an overall damaging effect—both on the average player’s experience and leaving “the players wanting more,”—consequently raising the potential for addiction [55].

Mainly, as explained with China’s new law, the shortcomings may be linked to the fact that the policies outlined “only address or influence specific aspects of the problem” and fail to recognize the individual differences between gamers [56]. For instance, the forementioned 2018 study by Kiraly et al. revealed that the policies by China and South Korea tended to focus on only one of the following: (i) reducing time spent gaming, (ii) changing the addictive potential, (iii) trying to help gamers by looking at psychological and motivation factors behind their desire to game [57]. Tackling video gaming addiction through only one of the forementioned approaches isn’t sufficient to properly address the issue, rather the most efficient mode of attack requires a cohesive regulation approach that targets multiple aspects. Additionally, according to the study, another method to solve this issue is through a targeted prevention approach: where warnings can be customized to target problem behaviors without encroaching on the “non-problematic gamers’ enjoyment of a largely healthy pastime activity” [58].

South Korea’s 2021 Plan

Ten years after the controversial shutdown law, South Korea is removing government-controlled time restraints in gaming to stay up to date on digital trends, respect young people’s rights, and allow households to enforce limitations themselves [59]. By the end of the year, following the modification of the Youth Protection Act, South Korea will be relying on the “choice permit system,” where parents and underage gamers can request a permit to designate their own playing hours [60]. The Korea Association of Game Industry is in favor of the decision, expecting the new plan to release the hold the previous law held over their gaming industry and children’s rights, as well as reducing the likelihood for addiction to significantly manifest [61].

Notably, one of China’s concerns and motivators behind their aforementioned time restrictions revolve around the misdirection of priorities. It is true that children repeatedly opting to game over completing their algebra homework, or game late into the night instead of getting a full eight hours of sleep, can hinder their ability to learn and satisfy academic responsibilities—as studies in China have shown that problematic video gaming interferes with “sleep, mood, and social learning in children and adolescents” [62].

However, forcibly removing gamers from the gaming environment ‘cold turkey’ can cause considerable distress and negate the benefits that games have demonstrated [63]. It’s important to acknowledge that gaming can generate positive impacts as well. In a study exploring the benefits of gaming, published by the National Center for Biotechnology Information, it was discovered that children who regularly play video games in healthy doses develop an improvement in cognitive abilities—such as deductive reasoning, processing speeds, mathematical intelligence, and skills pertaining analogy—over those who do not game [64].

The notion of time constraints isn’t completely invalid, but should be executed on a moderate level according to each case—and in combination with education and treatment programs—to keep individuals focused on their priorities while demonstrating safe ways to game. To achieve this goal, South Korea’s abolishment of the restriction is paired with a shift in attention: one that focuses on “strengthening the monitoring of harmful game content,” supporting “media and game-use education,” and increasing the implementation of prevention and recovery methods—such as counseling and rehabilitation camps [65]. Moreover, with an aim to raise awareness of problematic gaming habits, outreach programs pertaining the nature of gaming culture, media literacy, and the risks for addiction are included in this renewed focus on education [66].

Hwang Hee, Minister of Culture, Sports and Tourism in South Korea, expressed that gaming is an important avenue for youths to release stress and connect with others; therefore, the new measures strive to encourage these benefits by “establish[ing] a healthy culture of gaming and leisure for teenagers in a flexible manner” [67]. This revised system is more permissive than China’s reinforced gaming restrictions, subsequently leaving “China as the only nation to restrict gaming hours by law” [68].

Technology will only continue to evolve and integrate into our daily routines. There’s no going back to an age where smart phones and online platforms aren’t essential to everything we do, whether that be flaunting vacation pictures on social media, calculating a tip at the end of a meal, buying the latest Barbie on Amazon for Christmas, or paying taxes at the touch of a button. We have the world at our fingertips; however, as with every device or tool at our disposal, there is a potential for abuse.

And with the gaming industry booming, there’s no denying video gaming addiction is becoming an increasingly significant threat—especially amidst the youngest generation. By identifying the best ways to approach the issue, backed by relevant strategies that don’t take away from the benefits and experience of gaming, the ramifications can be better contained and predicted in the United States. Particularly in the wake of the recent pandemic, where gaming, streaming, and other forms of content consumption on the internet have risen exponentially to fill the void of stimulus in people’s lives.

With South Korea’s newfound direction in their efforts against video gaming addiction, and WHO adding the problematic behavior on the list of addictions, the international awareness regarding the consequences of overusing technology can receive the attention it deserves. Additionally, by analyzing these two contrasting policies, the United States can determine which aspects are most effective and gear similar techniques towards their own prevention plans. While political and cultural differences may limit the capacity for the U.S. government to fully implement all of the policies previously mentioned, gaming companies have more control on a self-regulatory basis. This could include providing built-in parental controls, warning messages for high levels of playtime, and rating systems to evaluate the addictive potential of games.

Above all, there’s a collective responsibility for parents, educators, clinicians, game developers, and the U.S. government to recognize the issue for what it is and work towards protecting all vulnerable demographics. For policymakers and community members to pay attention, take this addiction seriously, identify addict-risk teens, introduce the necessary information, and provide effective treatment programs for those in recovery.

[1] Spajic, Damjan. (December 30, 2019). Video Gaming Addiction Statistics: Real Problem or Phony Panic? Retrieved from: https://kommandotech.com/statistics/video-gaming-addiction-statistics-real-problem-or-phony-panic/

[2] Kiraly, O., et al. (September 2018). Policy responses to problematic video game use: A systematic review of current measures and future possibilities. NCBI: Journal of Behavioral Addictions. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426392/

[3] Watkins, M. (October 26, 2021). Video Game Addiction Symptoms and Treatment. American Addiction Centers. Retrieved from https://americanaddictioncenters.org/video-gaming-addiction

[4] Lange, J. (August 31, 2021). Let the Kids Play Video Games. The Week. Retrieved from https://theweek.com/culture/1004360/1-hour-of-video-games-isnt-enough

[5] Goodfellow, J. (August 31, 2021). How Will Marleters Adapt to China’s Video-Game Restrictions for Kids? U.S.: Campaign. Retrieved from https://www.campaignlive.com/article/will-marketers-adapt-chinas-video-game-restrictions-kids/1726000

[6] (n.d.). Internet Gaming. American Psychiatric Association. Retrieved from https://www.psychiatry.org/patients-families/internet-gaming

[7] Staff. (June 10, 2020). Are video games and screens another addiction? Mayo Clinic Health System. Retrieved from https://www.mayoclinichealthsystem.org/hometown-health/speaking-of-health/are-video-games-and-screens-another-addiction

[8] Kuss, D. J. (October 1, 2018). Policy, prevention, and regulation for Internet Gaming Disorder Commentary on: Policy responses to problematic video game use: A systematic review of current measures and future possibilities. Journal of Behavioral Addictions. V. 7, Issue 3. Pages 553-555. Retrieved from https://akjournals.com/view/journals/2006/7/3/article-p553.xml

[9] Lopez-Fernandez, O., and Kuss, D. (May 2020). Preventing Harmful Internet Use-Related Addiction Problems in Europe: A Literature Review and Policy Options. Research Gate. Retrieved from https://www.researchgate.net/publication/341684121_Preventing_Harmful_Internet_Use-Related_Addiction_Problems_in_Europe_A_Literature_Review_and_Policy_Options

[10] Adair, C. (n.d.). Video Game Addiction Statistics 2021—How Many Addicted Gamers Are There? Game Quitters. Retrieved from https://gamequitters.com/video-game-addiction-statistics/

[11] Ibid .

[12] Block, J. (March 1, 2008). Issues for DSM-V: Internet Addiction. The American Journal of Psychiatry. Retrieved from https://ajp.psychiatryonline.org/doi/full/10.1176/appi.ajp.2007.07101556

[13] Xing, D. (September 3, 2021). China steps up its war on underage online video gaming and not everyone is happy. News. Retrieved from https://www.abc.net.au/news/2021-09-04/china-cracks-down-on-children-online-video-gaming/100428138

[18] Sullivan, M. (July 30, 2019). South Korea Says About 20 Percent of its Population is at Risk For Internet Addiction. NPR. Retrieved from https://www.npr.org/2019/07/30/746687204/south-korea-says-about-20-percent-of-its-population-is-at-risk-for-internet-addi

[19] (November 28, 2012). Wired South Korea to Stem Digital Addiction from Age 3. Retrieved from: https://www.usatoday.com/story/tech/2012/11/28/wired-south-korea-to-stem-digital-addiction-from-age-3/1731371/

[20] Lee, Claire. (April 22, 2015). More Teenagers at Risk of Internet Addiction. The Korean Herald. Retrieved from: http://www.koreaherald.com/view.php?ud=20150422001211

[23] McGregor, G. (September 3, 2021). China’s gaming market was built on free and addictive games. Can Beijing stop kids from playing them? Fortune. Retrieved from https://fortune.com/2021/09/03/china-video-gaming-mobile-smartphone-addiction-free-to-play/

[25] Davies, B., and Blake, E. (March 4, 2016). Evaluating Existing Strategies to Limit Video Game Playing Time. IEEE Xplore. Retrieved from https://ieeexplore.ieee.org/document/7426249

[27] Stone, R. (June 26, 2009). China Reins in Wilder Impulses in Treatment of ‘Internet Addiction.’ Science. Retrieved from https://www.science.org/doi/10.1126/science.324_1630

[31] Hanson, L. (March 8, 2018). The Biggest Market By Far: Video Gaming in China. USC: US-China Annenberg Institute. Retrieved from https://china.usc.edu/calendar/biggest-market-far-video-gaming-china

[35] Choi, J., et al. (February 2018). Effect of the Online Game Shutdown Policy on Internet Use, Internet Addiction, and Sleeping Hours in Korean Adolescents. ResearchGate. Retrieved from https://www.researchgate.net/publication/323098593_Effect_of_the_Online_Game_Shutdown_Policy_on_Internet_Use_Internet_Addiction_and_Sleeping_Hours_in_Korean_Adolescents

[36] Koo, C., et al. (June 23, 2011). Internet-Addicted Kids and South Korean Government Efforts: Boot-Camp Case. Liebert Publishers. Retrieved from https://www.liebertpub.com/doi/10.1089/cyber.2009.0331

[41] Letzing, J. (September 6, 2021). What’s behind China’s video game restrictions? World Economic Forum. Retrieved from https://www.weforum.org/agenda/2021/09/what-s-behind-china-s-video-game-restrictions/

[45] Plavevski, A. (August 31, 2021). China’s new rules allow kids on video games just 3 hours a week—but gaming addiction isn’t about time, it’s about attitude. United States: The Conversation. Retrieved from https://theconversation.com/chinas-new-rules-allow-kids-on-video-games-just-3-hours-a-week-but-gaming-addiction-isnt-about-time-its-about-attitude-167104#:~:text=It’s%20clear%20China%20is%20associating,person%20brings%20to%20the%20gaming .

[47] Király, O., Tóth, D., Urbán, R., Demetrovics, Z., & Maraz, A. (2017). Intense video gaming is not essentially problematic. Psychology of Addictive Behaviors, 31(7), 807–817. Retrieved from https://doi.org/10.1037/adb0000316

[48] Kamenetz, A. (May 28, 2019). Is ‘Gaming Disorder’ An Illness? WHO Says Yes, Adding it to its List of Diseases. NPR. Retrieved from https://www.npr.org/2019/05/28/727585904/is-gaming-disorder-an-illness-the-who-says-yes-adding-it-to-its-list-of-diseases

[51] (March 7, 2014). Gaming Addiction a Serious Problem in Asia. The Cabin. Retrieved from https://www.thecabinchiangmai.com/blog/gaming-addiction-a-serious-problem-in-asia/

[59] (August 25, 2021). Changed gaming environment pushes South Korean government to terminate ‘shutdown law.’ Yonhap News Agency. Retrieved from  https://en.yna.co.kr/view/AEN20210825006000315

[60] Batchelor, J. (August 27, 2021). South Korea plans to abolish gaming curfew. Games Industry. Retrieved from https://www.gamesindustry.biz/articles/2021-08-27-south-korea-plans-to-abolish-gaming-curfew

[64] Hisam, A., et al. Does playing video games effect cognitive abilities in Pakistani Children? NCBI: Pakistan Journal of Medical Sciences. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290198/

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ORIGINAL RESEARCH article

The effects of online game addiction on reduced academic achievement motivation among chinese college students: the mediating role of learning engagement.

Rui-Qi Sun&#x;

  • 1 BinZhou College of Science and Technology, Binzhou, China
  • 2 Binzhou Polytechnic, Binzhou, China
  • 3 Faculty of Education, Beijing Normal University, Beijing, China
  • 4 National Institute of Vocational Education, Beijing Normal University, Beijing, China

Introduction: The present study aimed to examine the effects of online game addiction on reduced academic achievement motivation, and the mediating role of learning engagement among Chinese college students to investigate the relationships between the three variables.

Methods: The study used convenience sampling to recruit Chinese university students to participate voluntarily. A total of 443 valid questionnaires were collected through the Questionnaire Star application. The average age of the participants was 18.77 years old, with 157 males and 286 females. Statistical analysis was conducted using SPSS and AMOS.

Results: (1) Chinese college students’ online game addiction negatively affected their behavioral, emotional, and cognitive engagement (the three dimensions of learning engagement); (2) behavioral, emotional, and cognitive engagement negatively affected their reduced academic achievement motivation; (3) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

1. Introduction

Online games, along with improvements in technology, have entered the daily life of college students through the popularity of computers, smartphones, PSPs (PlayStation Portable), and other gaming devices. Online game addiction has recently become a critical problem affecting college students’ studies and lives. As early as 2018, online game addiction was officially included in the category of “addictive mental disorders” by the World Health Organization (WHO), and the International Classification of Diseases (ICD) was updated specifically to include the category of “Internet Gaming Disorder” (IGD). Prior research investigating Chinese college students’ online game addiction status mostly comprised regional small-scale studies. For example, a study on 394 college students in Chengde City, Hebei province, China showed that the rate of online game addiction was about 9% ( Cui et al., 2021 ). According to the results of an online game survey conducted by China Youth Network (2019) on 682 Chinese college students who played online games, nearly 60% of participants played games for more than 1 h a day, over 30% stayed up late because of playing games, over 40% thought that playing games had affected their physical health, over 70% claimed that games did not affect their studies, and over 60% had spent money on online games. This phenomenon has been exacerbated by the fact that smartphones and various portable gaming devices have become new vehicles for gaming with the development of technology. The increase in the frequency or time spent on daily gaming among adolescents implies a growth in the probability of gaming addiction, while an increase in the level of education decreases the probability of gaming addiction ( Esposito et al., 2020 ; Kesici, 2020 ). Moreover, during the COVID-19 pandemic, adolescents’ video game use and the severity of online gaming disorders increased significantly ( Teng et al., 2021 ).

A large body of literature on the relationship between problematic smartphone use and academic performance has illustrated the varying adverse effects of excessive smartphone obsession ( Durak, 2018 ; Mendoza et al., 2018 ; Rozgonjuk et al., 2018 ). These effects are manifested in three critical ways: first, the more frequently cell phones are used during study, the greater the negative impact on academic performance and achievement; second, students are required to master the basic skills and cognitive abilities to succeed academically, which are negatively affected by excessive cell phone use and addiction ( Sunday et al., 2021 ); third, online game addiction negatively affects students’ learning motivation ( Demir and Kutlu, 2018 ; Eliyani and Sari, 2021 ). However, there is currently a lack of scientifically objective means of effective data collection regarding online game addiction among college students in China, such as big data. Hong R. Z. et al. (2021) and Nong et al. (2023) suggested that the impact of addiction on students’ learning should be explored more deeply.

Since the 1990s, learning engagement has been regarded as a positive behavioral practice in learning in Europe and the United States, and plays an important role in the field of higher education research ( Axelson and Flick, 2010 ). Recently, studies on learning engagement among college students have also been a hot topic in various countries ( Guo et al., 2021 ). According to Fredricks et al. (2004) , learning engagement includes three dimensions: behavioral, emotional, and cognitive.

The concept of behavioral engagement encompasses three aspects: first, positive behavior in the classroom, such as following school rules and regulations and classroom norms; second, engagement in learning; and third, active participation in school activities ( Finn et al., 1995 ). Emotional engagement refers to students’ responses to their academic content and learning environment. The emotional responses to academic content include students’ emotional responses such as interest or disinterest in learning during academic activities ( Kahu and Nelson, 2018 ), while the emotional responses to the learning environment refer to students’ identification with their peers, teachers, and the school environment ( Stipek, 2002 ). Cognitive engagement is often associated with internal processes such as deep processing, using cognitive strategies, self-regulation, investment in learning, the ability to think reflectively, and making connections in daily life ( Khan et al., 2017 ). Cognitive engagement emphasizes the student’s investment in learning and self-regulation or strategies.

According to Yang X. et al. (2021) , learning engagement refers to students’ socialization, behavioral intensity, affective qualities, and use of cognitive strategies in performing learning activities. Besides, Kuh et al. (2007) argued that learning engagement was “the amount of time and effort students devote to instructional goals and meaningful educational practices.” Learning engagement is not only an important indicator of students’ learning process, but also a significant predictor of students’ academic achievement ( Zhang, 2012 ). It is also an essential factor in promoting college students’ academic success and improving education quality.

As one of the crucial components of students’ learning motivation ( Han and Lu, 2018 ), achievement motivation is the driving force behind an individual’s efforts to put energy into what he or she perceives to be valuable and meaningful to achieve a desired outcome ( Story et al., 2009 ). It can be considered as achievement motivation when an individual’s behavior involves “competing at a standard of excellence” ( Brunstein and Heckhausen, 2018 ). Students’ achievement motivation ensures the continuity of learning activities, achieving academic excellence and desired goals ( Sopiah, 2021 ). Based on the concept of achievement motivation, academic achievement motivation refers to the mental perceptions or intentions that students carry out regarding their academic achievement, a cognitive structure by which students perceive success or failure and determine their behavior ( Elliot and Church, 1997 ). Related research also suggests that motivation is one variable that significantly predicts learning engagement ( Xiong et al., 2015 ).

Therefore, it is worthwhile to investigate the internal influence mechanism of college students’ online game addiction on their reduced academic achievement motivation and the role of learning engagement, which is also an issue that cannot be ignored in higher education research. The present study explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation among college students by establishing a structural equation model (SEM) to shed light on the problem of online game addiction among college students.

2. Research model and hypotheses

2.1. research model.

Previous research usually regarded learning engagement as a variable of one or two dimensions, and scholars tend to favor the dimension of behavioral engagement. However, other ignored dimensions are inseparable parts of learning engagement ( Dincer et al., 2019 ). In a multi-dimensional model, the mutual terms of each dimension form a single composite structure. Therefore, the present study took the structure proposed by Fredricks et al. (2004) as a reference, divided learning engagement into behavioral, emotional, and cognitive dimensions as mediating variables, and explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation. The research frame diagram is shown in Figure 1 .

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Figure 1 . The research model.

2.2. Research questions

2.2.1. the relationship between online game addiction and learning engagement.

Learning engagement has been viewed as a multidimensional concept in previous studies. Finn (1989) proposed the participation-identification model to make pioneering progress in learning engagement study. Schaufeli et al. (2002) suggested that learning engagement was an active, fulfilling mental state associated with learning. Chapman (2002) pointed out affective, behavioral, and cognitive criteria for assessing students’ learning engagement based on previous research. Fredricks et al. (2004) systematically outlined learning engagement as an integration of behavioral, emotional, and cognitive engagement. The updated International Classification of Diseases [ World Health Organization (WHO), 2018a , b ] specifies several diagnostic criteria for gaming addiction, including the abandonment of other activities, the loss of interest in other previous hobbies, and the loss or potential loss of work and social interaction because of gaming. Past studies have shown the adverse effects of excessive Internet usage on students’ learning. Short video addiction negatively affects intrinsic and extrinsic learning motivation ( Ye et al., 2022 ). Students’ cell phone addiction negatively affects academic commitment, academic performance, and relationship facilitation, all of which negatively affect their academic achievement ( Tian et al., 2021 ). The amount of time spent surfing the Internet and playing games has been identified to negatively affect students’ cognitive ability ( Pan et al., 2022 ). College students’ cell phone addiction, mainly reflected in cell phone social addiction and game entertainment addiction, has also been noted to impact learning engagement; specifically, the higher the level of addiction, the lower the learning engagement ( Qi et al., 2020 ). Gao et al. (2021) also showed that cell phone addiction among college students could negatively affect their learning engagement. Choi (2019) showed that excessive use of cell phones might contribute to smartphone addiction, which also affects students’ learning engagement. Accordingly, the following three research hypotheses were proposed.

H1 : Online game addiction negatively affects behavioral engagement.
H2 : Online game addiction negatively affects emotional engagement.
H3 : Online game addiction negatively affects cognitive engagement.

2.2.2. The relationship between learning engagement and reduced academic achievement motivation

Achievement motivation is people’s pursuit of maximizing individual value, which embodies an innate drive, including the need for achievement, and can be divided into two parts: the intention to succeed and the intention to avoid failure ( McClelland et al., 1976 ). On this basis, Weiner (1985) proposed the attributional theory of achievement motivation, suggesting that individuals’ personality differences, as well as the experience of success and failure, could influence their achievement attributions and that an individual’s previous achievement attributions would affect his or her expectations and emotions for the subsequent achievement behavior while expectations and emotions could guide motivated behavior. Birch and Ladd (1997) indicated that behavioral engagement involved positive behavioral attitudes such as hard work, persistence, concentration, willingness to ask questions, and active participation in class discussions to complete class assignments. Students’ attitudes toward learning are positively related to achievement motivation ( Bakar et al., 2010 ). Emotional engagement involves students’ sense of identity with their peers, teachers, and the school environment ( Stipek, 2002 ). Students’ perceptions of the school environment influence their achievement motivation ( Wang and Eccles, 2013 ). Cognitive engagement encompasses the ability to use cognitive strategies, self-regulation, investment in learning, and reflective thinking ( Khan et al., 2017 ). Learning independence and problem-solving abilities predict student motivation ( Saeid and Eslaminejad, 2017 ). Hu et al. (2021) indicated that cognitive engagement had the most significant effect on students’ academic achievement among the learning engagement dimensions, and that emotional engagement was also an important factor influencing students’ academic achievement. Therefore, the following three research hypotheses were proposed:

H4 : Behavioral engagement significantly and negatively affects the reduced academic achievement motivation.
H5 : Emotional engagement significantly and negatively affects the reduced academic achievement motivation.
H6 : Cognitive engagement significantly and negatively affects the reduced academic achievement motivation.

2.2.3. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation

Past studies have demonstrated the relationship between online game addiction and students’ achievement motivation. For example, a significant negative correlation between social network addiction and students’ motivation to progress has been reported ( Haji Anzehai, 2020 ), and a significant negative correlation between Internet addiction and students’ achievement motivation has been reported ( Cao et al., 2008 ). Students addicted to online games generally have lower academic achievement motivation because they lack precise academic planning and motivation ( Chen and Gu, 2019 ). Yayman and Bilgin (2020) pointed out a correlation between social media addiction and online game addiction. Accordingly, there might be a negative correlation between online game addiction and academic achievement motivation among college students.

Students addicted to online games generally have lower motivation for academic achievement because they lack precise academic planning and learning motivation ( Chen and Gu, 2019 ). Similarly, Haji Anzehai (2020) reported a significant negative correlation between social network addiction and students’ motivation to progress.

Learning engagement is often explored as a mediating variable in education research. Zhang et al. (2018) found that learning engagement was an essential mediator of the negative effect of internet addiction on academic achievement in late adolescence and is a key factor in the decline in academic achievement due to students’ internet addiction. Li et al. (2019) noted that college students’ social networking site addiction significantly negatively affected their learning engagement, and learning engagement mediated the relationship between social networking addiction and academic achievement. Accordingly, the following research hypothesis was proposed.

H7 : Learning engagement mediates the relationship between online game addiction and reduced academic achievement motivation.

3. Research methodology and design

3.1. survey implementation.

The present study employed the Questionnaire Star application for online questionnaire distribution. Convenience sampling was adopted to recruit Chinese college students to participate voluntarily. The data were collected from October 2021 to January 2022 from a higher vocational college in Shandong province, China. Participants were first-and second-year students. According to Shumacker and Lomax (2016) , the number of participants in SEM studies should be approximately between 100 and 500 or more. In the present study, 500 questionnaires were returned, and 443 were valid after excluding invalid responses. The mean age of the participants was 18.77 years. There were 157 male students, accounting for 35.4% of the total sample, and 286 female students, accounting for 64.6%.

3.2. Measurement instruments

The present empirical study employed quantitative research methods by collecting questionnaires for data analysis. The items of questionnaires were adapted from research findings based on corresponding theories and were reviewed by experts to confirm the content validity of the instruments. The distributed questionnaire was a Likert 5-point scale (1 for strongly disagree , 2 for disagree , 3 for average , 4 for agree , and 5 for strongly agree ). After the questionnaire was collected, item analysis was conducted first, followed by reliability and validity analysis of the questionnaire constructs using SPSS23 to test whether the scale met the criteria. Finally, research model validation was conducted.

3.2.1. Online game addiction

In the present study, online game addiction referred to the addictive behavior of college students in online games, including mobile games and online games. The present study adopted a game addiction scale compiled by Wu et al. (2021) and adapted the items based on the definition of online game addiction. The adapted scale had 10 items. Two examples of the adapted items in the scale were: “I will put down what should be done and spend my time playing online games” and “My excitement or expectation of playing an online game is far better than other interpersonal interactions.”

3.2.2. Learning engagement

In the present study, learning engagement included students’ academic engagement in three dimensions: behavioral, emotional, and cognitive. The learning engagement scale compiled by Luan et al. (2020) was adapted based on its definition. The adapted scale had 26 questions in three dimensions: behavioral, emotional, and cognitive engagement. Two examples of the adapted items in the scale are: “I like to actively explore unfamiliar things when I am doing my homework” and “I will remind myself to double-check the places where I tend to make mistakes in my homework.”

3.2.3. Reduced academic achievement motivation

Reduced academic achievement motivation in the present study refers to the reduction in college students’ intrinsic tendency to enjoy challenges and achieve academic goals and academic success. The achievement motivation scale developed by Ye et al. (2020) was adapted to measure reduced academic achievement motivation. The adapted scale had 10 items. Two examples of the adapted items in the scale are: “Since playing online games, I do not believe that the effectiveness of learning is up to me, but that it depends on other people or the environment” and “Since I often play online games, I am satisfied with my current academic performance or achievement and do not seek higher academic challenges.”

4. Results and discussion

4.1. internal validity analysis of the measurement instruments.

In the present study, item analysis was conducted using first-order confirmatory factor analysis (CFA), which can reflect the degree of measured variables’ performance within a smaller construct ( Hafiz and Shaari, 2013 ). The first-order CFA is based on the streamlined model and the principle of independence of residuals. According to Hair et al. (2010) and Kenny et al. (2015) , it is recommended that the value of χ 2 / df in the model fitness indices should be less than 5; the root mean square error of approximation (RMSEA) value should be greater than 0.100; the values of the goodness of fit index (GFI) and adjusted goodness of fit index (AGFI) should not be lower than 0.800; the factor loading (FL) values of the constructs should also be greater than 0.500. Based on the criteria above, the items measuring the online game addiction construct were reduced from 10 to seven; the items measuring the behavioral engagement construct were reduced from nine to six; the items measuring the emotional engagement construct were reduced from nine to six; the items measuring the cognitive engagement construct were reduced from eight to six; and the items measuring the reduced academic achievement motivation construct was reduced from 10 to six, as shown in Table 1 .

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Table 1 . First-order confirmatory factor analysis.

4.2. Construct reliability and validity analysis

In order to determine the internal consistency of the constructs, the reliability of the questionnaire was tested using Cronbach’ s α value. According to Hair et al. (2010) , a Cronbach’ s α value greater than 0.700 indicates an excellent internal consistency among the items, and the constructs’ composite reliability (CR) values should exceed 0.700 to meet the criteria. In the present study, the Cronbach’ s α values for the constructs ranged from 0.911 to 0.960, and the CR values ranged from 0.913 to 0.916, which met the criteria, as shown in Table 2 .

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Table 2 . Construct reliability and validity of constructs.

In the present study, convergent validity was confirmed by two types of indicators, FL and average variance extracted (AVE). According to Hair et al. (2011) , an FL value should be greater than 0.500, and items with an FL value less than 0.500 should be removed; and AVE values should be greater than 0.500. In the present study, the FL values of the constructs ranged from 0.526 to 0.932, and the AVE values ranged from 0.600 to 0.805; all dimensions met the recommended criteria, as shown in Table 2 .

According to Awang (2015) and Hair et al. (2011) , the square root of the AVE of each construct (latent variable) should be greater than its correlation coefficient values with other constructs to indicate the ideal discriminant validity. The results of the present study showed that the three constructs of online game addiction, learning engagement, and reduced academic achievement motivation had good discriminant validity in the present study, as shown in Table 3 .

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Table 3 . Discriminant validity analysis.

4.3. Correlation analysis

Pearson’s correlation coefficient is usually used to determine the closeness of the relationship between variables. A correlation coefficient greater than 0.8 indicates a high correlation between variables; a correlation coefficient between 0.3 and 0.8 indicates a moderate correlation between variables; while a correlation of less than 0.3 indicates a low correlation. Table 4 shows the Correlation Analysis results. Online game addiction was moderately negatively correlated with behavioral engagement ( r  = −0.402, p  < 0.001), moderately negatively correlated with emotional engagement ( r  = −0.352, p  < 0.001), slightly negatively correlated with cognitive engagement ( r  = −0.288, p  < 0.001), and slightly positively correlated with reduced academic achievement motivation ( r  = 0.295, p  < 0.001). Behavioral engagement was moderately positively correlated with emotional engagement ( r  = 0.696, p  < 0.001), moderately positively correlated with cognitive engagement ( r  = 0.601, p  < 0.001), and moderately negatively correlated with reduced academic achievement motivation ( r  = −0.497, p  < 0.001). Emotional engagement was moderately positively correlated with cognitive engagement ( r  = 0.787, p  < 0.001) and moderately negatively correlated with reduced academic achievement motivation ( r  = −0.528, p  < 0.001). Cognitive engagement was moderately negatively correlated with reduced motivation for academic achievement ( r  = −0.528, p  < 0.001).

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Table 4 . Correlation analysis.

4.4. Analysis of fitness of the measurement model

According to Hair et al. (2010) and Abedi et al. (2015) , the following criteria should be met in the analysis for measurement model fitness: the ratio of chi-squared and degree of freedom ( χ 2 / df ) should be less than 5; the root mean square error of approximation (RMSEA) should not exceed 0.100; the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), non-normed fit index (NNFI), comparative fit index (CFI), incremental fit index (IFI) and relative fit index (RFI) should be higher than 0.800; and the parsimonious normed fit index (PNFI) and the parsimonious fitness of fit index (PGFI) should be higher than 0.500. The model fitness indices in the present study were χ 2  = 1434.8, df  = 428, χ 2 / df  = 3.352, RMSEA = 0.073, GFI = 0.837, AGFI = 0.811, NFI = 0.899, NNFI = 0.920, CFI = 0.927, IFI = 0.927, RFI = 0.890, PNFI = 0.827, and PGFI = 0.722. The results were in accordance with the criteria, indicating a good fitness of the model in the present study ( Table 5 ).

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Table 5 . Direct effects analysis.

4.5. Validation of the research model

Online game addiction had a negative effect on behavioral engagement ( β  = −0.486; t  = −9.143; p < 0.001). Online game addiction had a negative effect on emotional engagement ( β  = −0.430; t  = −8.054; p < 0.001). Online game addiction had a negative effect on cognitive engagement ( β  = −0.370; t  = −7.180; p < 0.001). Online game addiction had a positive effect on reduced academic achievement motivation ( β  = 0.19; t = −2.776; p < 0.01). Behavioral engagement had a negative effect on reduced academic achievement motivation ( β  = −0.238; t  = −3.759; p < 0.001). Emotional engagement had a negative effect on reduced academic achievement motivation ( β  = −0.221; t  = −2.687; p < 0.01), and cognitive engagement had a negative effect on reduced academic achievement motivation ( β  = −0.265; t  = −3.581; p < 0.01), as shown in Figure 2 Table 6 .

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Figure 2 . Validation of the research model. *** p  < 0.001.

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Table 6 . Indirect effects analysis.

Cohen’ s f 2 is an uncommon but valuable standardized effect size measure that can be used to assess the size of local effects ( Selya et al., 2012 ). When f 2 reaches 0.02 it represents a small effect size, 0.150 represents a medium effect size, and 0.350 represents a high effect size ( Hair et al., 2014 ). The explanatory power of online game addiction on behavioral engagement was 23.6%, and f 2 was 0.309. The explanatory power of online game addiction on emotional engagement was 18.5%, and f 2 was 0.227. The explanatory power of online game addiction on cognitive engagement was 13.7%, and f 2 was 0.159. The explanatory power of behavioral, emotional, and cognitive engagement on reduced academic achievement motivation was 23.9%, and f 2 was 0.314. Figure 2 illustrates the above findings.

4.6. Indirect effects analysis

Scholars are often interested in whether variables mediate the association between predicting and outcome variables. Therefore, mediating variables can partially or entirely explain the association ( Hwang et al., 2019 ). In research fields such as psychology and behavior, where the research situation is often more complex, multiple mediating variables are often required to clearly explain the effects of the independent variables on the dependent variables ( MacKinnon, 2012 ). Scientific quantitative research requires tests of confidence interval (CI; Thompson, 2002 ), and the standard value of the test numbers is often determined by 95% CI ( Altman and Bland, 2011 ). CI value not containing 0 indicates the statistical significance of the analysis results ( Nakagawa and Cuthill, 2007 ). According to the statistical results shown in Table 4 , behavioral engagement significantly positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.230 and 95% CI ranging from 0.150 to 0.300 (excluding 0), p < 0.01; emotional engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.209, 95% CI ranging from 0.130 to 0.292 (excluding 0), p < 0.01; cognitive engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.170, 95% CI ranging from 0.100 to 0.250 (excluding 0), p < 0.01, as shown in Table 6 .

4.7. Discussion

4.7.1. analysis of the relationship between online game addiction and learning engagement.

Online game addiction is often negatively associated with students’ learning. For example, the problematic use of short videos was reported as negatively affecting students’ behavioral engagement, while behavioral engagement positively affected students’ emotional and cognitive engagement ( Ye et al., 2023 ). Meral (2019) highlighted that students’ learning attitudes and academic performance had a negative relationship with students’ addiction to online games. Demir and Kutlu (2018) found that online game addiction negatively affects students’ learning motivation. As the level of students’ game addiction increased, the level of their communication skills decreased ( Kanat, 2019 ). Furthermore, Tsai et al. (2020) pointed out a negative correlation between online game addiction and peer relationships as well as students’ learning attitudes. According to the results of the research model validation, it can be observed that: online game addiction negatively affected behavioral engagement, emotional engagement, and cognitive engagement. Therefore, it can be stated that online game addiction had significant and negative effects on all dimensions of learning engagement.

Online game addiction in the present study included aspects of computer game addiction and mobile phone game addiction. The results of the present study are consistent with the findings of Gao et al. (2021) , Choi (2019) , and Qi et al. (2020) , who pointed out that college students’ addiction to cell phones negatively affected their learning engagement.

4.7.2. Analysis of the relationship between learning engagement and reduced academic achievement motivation

For technology education in higher education, students’ intrinsic motivation for academic study predicts their learning engagement ( Dunn and Kennedy, 2019 ). In addition, learning engagement is positively correlated with academic achievement ( Fredricks and McColskey, 2012 ). Based on the research model validation results, behavioral, emotional, and cognitive engagement all negatively affected reduced academic achievement motivation. The findings are consistent with Hu et al.’s (2021) study which pointed out that cognitive engagement in the learning engagement dimension had the most significant effect on students’ academic achievement, and that emotional engagement was also an essential factor influencing students’ academic achievement. Lau et al. (2008) showed that achievement motivation positively predicted cognitive engagement in the learning engagement dimension. Mih et al. (2015) noted that achievement motivation positively predicted behavioral and emotional engagement in the learning engagement dimension. The present study supported the above discussion by confirming the association between learning engagement and reduced academic achievement motivation.

4.7.3. Analysis of the mediating role of learning engagement

According to the indirect effects analysis results of the present study, learning engagement negatively mediated the relationship between online game addiction and reduced academic achievement motivation. The findings support Haji Anzehai’s (2020) conclusion that social network addiction negatively correlated with students’ motivation to progress ( Haji Anzehai, 2020 ). It is also consistent with the findings of Chen and Gu (2019) that students addicted to online games generally had lower academic achievement motivation due to a lack of precise academic planning and motivation. Cao et al. (2008) found a significant negative correlation between Internet addiction and students’ achievement motivation. Similarly, Zhang et al. (2018) explored the intrinsic influencing mechanism of students’ Internet addiction on academic achievement decline in their late adolescence by identifying learning engagement as the important mediating variable. Li et al. (2019) proposed that social networking site addiction among college students significantly negatively affected learning engagement and that learning engagement mediated the relationship between social network addiction and students’ academic achievement. The present study findings also support the discussion above.

5. Conclusion and suggestions

5.1. conclusion.

Currently, the problem of online game addiction among college students is increasing. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation still needs to be explored. The present study explored the relationships between the three aforementioned variables by performing SEM. The results of the study indicated that: (1) online game addiction negatively affected behavioral engagement; (2) online game addiction negatively affected emotional engagement; (3) online game addiction negatively affected cognitive engagement; (4) behavioral engagement negatively affected reduced academic achievement motivation; (5) emotional engagement negatively affected reduced academic achievement motivation; (6) cognitive behavioral engagement negatively affected reduced academic achievement motivation; (7) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

According to the research results, when college students are addicted to online games, their learning engagement can be affected, which may decrease their behavioral, emotional, and cognitive engagement; their academic achievement motivation may be further reduced and affect their academic success or even prevent them from completing their studies. The mediating role of learning engagement between online game addiction and reduced academic achievement motivation indicates that reduced academic achievement motivation influenced by online game addiction could be prevented or weakened by enhancing learning engagement.

5.2. Suggestions

Universities and families play a crucial role in preventing online game addiction among college students. One of the main reasons college students play online games may be that they lack an understanding of other leisure methods and can only relieve their psychological pressure through online games ( Fan and Gai, 2022 ). Therefore, universities should enrich college students’ after-school leisure life and help them cultivate healthy hobbies and interests. Besides, a harmonious parent–child relationship positively affects children’s learning engagement ( Shao and Kang, 2022 ). Parents’ stricter demands may aggravate children’s game addiction ( Baturay and Toker, 2019 ). Therefore, parents should assume a proper perspective on the rationality of gaming and adopt the right approach to guide their children.

One key factor influencing the quality of higher education is students’ learning engagement. The integration of educational information technology has disrupted traditional teaching methods. This trend has accelerated in the context of COVID-19. College students’ growth mindset can impact their learning engagement through the role of the perceived COVID-19 event strength and perceived stress ( Zhao et al., 2021 ). Moreover, students’ self-regulated learning and social presence positively affect their learning engagement in online contexts ( Miao and Ma, 2022 ). Students’ liking of the teacher positively affects their learning engagement ( Lu et al., 2022 ). Their perceived teacher support also positively affects their learning engagement ( An et al., 2022 ). Hence, educators should focus on teacher support and care in the teaching and learning process.

Students’ motivation for academic achievement can often be influenced by active interventions. Cheng et al. (2022) noted that the cumulative process of students gaining successful experiences contributed to an increased sense of self-efficacy, motivating them to learn. Zhou (2009) illustrated that cooperative learning motivated students’ academic achievement. In addition, Hong J. C. et al. (2021) showed that poor parent–child relationships (such as the behavior of “mama’ s boy” in adults) had a negative impact on students’ academic achievement motivation, and they concluded that cell phone addiction was more pronounced among students with low academic achievement motivation. Hence, enhancing students’ academic achievement motivation also requires family support.

5.3. Research limitations and suggestions for future research

Most of the past studies on the impact of online game addiction on academics have used quantitative research as the research method. The qualitative research approach regarding students’ online game addiction should not be neglected. By collecting objective factual materials in the form of qualitative research such as interviews a greater understanding of students’ actual views on games and the psychological factors of addiction can be achieved. Therefore, future studies could introduce more qualitative research to study online game addiction.

To pay attention to the problem of students’ online game addiction, universities and families should not wait until they become addicted and try to remedy it, but should start to prevent it before it gets to that stage. In terms of developing students’ personal psychological qualities, students’ sensation-seeking and loneliness can significantly affect their tendency to become addicted to online games ( Batmaz and Çelik, 2021 ). Adolescents’ pain intolerance problems can also contribute to Internet overuse ( Gu, 2022 ). Emotion-regulation methods affect the emotional experience and play a vital role in Internet addiction ( Liang et al., 2021 ). In this regard, it is necessary to pay attention to students’ mental health status and to guide them to establish correct values and pursue goals through psychological guidance and other means.

In addition to individual factors, different parenting can considerably impact adolescents. Adolescents who tend to experience more developmental assets are less likely to develop IGD ( Xiang et al., 2022a ), and external resources can facilitate the development of internal resources, discouraging adolescents from engaging in IGD ( Xiang et al., 2022b ). Relevant research indicates that the most critical factor in adolescents’ game addiction tendency comes from society or their parents rather than being the adolescents’ fault ( Choi et al., 2018 ). Adolescents who tend to be addicted to online games may have discordant parent–child relationships ( Eliseeva and Krieger, 2021 ). Better father-child and mother–child relationships predict lower initial levels of Internet addiction in adolescents ( Shek et al., 2019 ). Family-based approaches such as improved parent–child relationships and increased communication and understanding among family members can be a direction for adolescent Internet addiction prevention ( Yu and Shek, 2013 ).

At the school level, a close teacher-student relationship is one of the main factors influencing students’ psychological state. Students’ participation in and control over the teaching and learning process as well as their closeness to teachers can increase their satisfaction and thus enhance their learning-related well-being ( Yang J. et al., 2021 ). More school resources can lead to higher adolescent self-control, attenuating students’ online gaming disorders ( Xiang et al., 2022c ).

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

R-QS, and J-HY: concept and design and drafting of the manuscript. R-QS, and J-HY: acquisition of data and statistical analysis. G-FS, and J-HY: critical revision of the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by Beijing Normal University First-Class Discipline Cultivation Project for Educational Science (Grant number: YLXKPY-XSDW202211). The Project Name is “Research on Theoretical Innovation and Institutional System of Promoting the Modernization of Vocational Education with Modern Chinese Characteristics”.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abedi, G., Rostami, F., and Nadi, A. (2015). Analyzing the dimensions of the quality of life in hepatitis B patients using confirmatory factor analysis. Global J. Health Sci. 7, 22–31. doi: 10.5539/gjhs.v7n7p22

PubMed Abstract | CrossRef Full Text | Google Scholar

Altman, D. G., and Bland, J. M. (2011). How to obtain the confidence interval from a p value. Br. Med. J. 2011:343. doi: 10.1136/bmj.d2090

CrossRef Full Text | Google Scholar

An, F., Yu, J., and Xi, L. (2022). Relationship between perceived teacher support and learning engagement among adolescents: mediation role of technology acceptance and learning motivation. Front. Psychol. 13:992464. doi: 10.3389/fpsyg.2022.992464

Awang, Z. (2015). SEM made simple, a gentle approach to learning structural equation modeling . MPWS Rich Publication. Bangi.

Google Scholar

Axelson, R. D., and Flick, A. (2010). Defining student engagement. Change 43, 38–43. doi: 10.1080/00091383.2011.533096

Bakar, K. A., Tarmizi, R. A., Mahyuddin, R., Elias, H., Luan, W. S., and Ayub, A. F. M. (2010). Relationships between university students’ achievement motivation, attitude and academic performance in Malaysia. Procedia Soc. Behav. Sci. 2, 4906–4910. doi: 10.1016/j.sbspro.2010.03.793

Batmaz, H., and Çelik, E. (2021). Examining the online game addiction level in terms of sensation seeking and loneliness in university students. Addicta 8, 126–130. doi: 10.5152/ADDICTA.2021.21017

Baturay, M. H., and Toker, S. (2019). Internet addiction among college students: some causes and effects. Educ. Inf. Technol. 24, 2863–2885. doi: 10.1007/s10639-019-09894-3

Birch, S., and Ladd, G. (1997). The teacher-child relationship and children’s early school adjustment. Journal of School Psychology 35, 61–79. doi: 10.1016/S0022-4405(96)00029-5

Brunstein, J. C., and Heckhausen, H. (2018). “Achievement motivation,” in Motivation and action . eds. J. Heckhausen and H. Heckhausen (New York, NY: Springer), 221–304.

Cao, H., Cao, P., Wang, P., and Wang, X. H. (2008). An exploration of the interrelationship between internet addiction and achievement motivation among middle school students. J. Beijing Youth Polit. College 2008, 31–38.

Chapman, E. (2002). Alternative approaches to assessing student engagement rates. Pract. Assess. Res. Eval. 8:13. doi: 10.7275/3e6e-8353

Chen, C. G., and Gu, X. Q. (2019). The impact of online games on students’ subject literacy and social inclusion - an analysis based on PISA 2015 test data from four Chinese provinces and cities. Open Educat. Res. 25, 73–87. doi: 10.13966/j.cnki.kfjyyj.2019.05.008

Cheng, B. J., Chen, P., and Chen, Y. S. (2022). The influence of academic achievement motivation on technical learning engagement of students with specialization in physical education faculty: the mediating role of self-efficacy. J. Southwest Univ. 47, 96–106. doi: 10.13718/j.cnki.xsxb.2022.04.014

China Youth Network (2019). Survey on online hames for college students . Available at: http://edu.youth.cn/jyzx/jyxw/201904/t20190415_11926323.htm

Choi, S. (2019). Relationships between smartphone usage, sleep patterns and nursing students’ learning engagement. J. Korean Biol. Nurs. Sci. 21, 231–238. doi: 10.7586/jkbns.2019.21.3.231

Choi, C., Hums, M. A., and Bum, C. H. (2018). Impact of the family environment on juvenile mental health: eSports online game addiction and delinquency. Int. J. Environ. Res. Public Health 15:2850. doi: 10.3390/ijerph15122850

Cui, J., Yang, K. B., Yang, Q. Y., Liu, Y., Zhao, R. J., Wu, W., et al. (2021). Psychological influences of online game addiction among college students in Chengde City. Chin. J. Drug Depend 30, 296–300+305. doi: 10.13936/j.cnki.cjdd1992.2021.04.011

Demir, Y., and Kutlu, M. (2018). Relationships among Internet addiction, academic motivation, academic procrastination and school attachment in adolescents. Int. Online J. Educat. Sci. 10, 315–332. doi: 10.15345/iojes.2018.05.020

Dincer, A., Yeşilyurt, S., Noels, K. A., and Vargas Lascano, D. I. (2019). Self-determination and classroom engagement of EFL Learners: a mixed-methods study of the self-system model of motivational development. SAGE Open 9:215824401985391. doi: 10.1177/2158244019853913

Dunn, T. J., and Kennedy, M. (2019). Technology enhanced learning in higher education; motivations, engagement and academic achievement. Comput. Educ. 137, 104–113. doi: 10.1016/j.compedu.2019.04.004

Durak, H. Y. (2018). Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: demographic variables and academic performance. Soc. Sci. J. 56, 492–517. doi: 10.1016/j.soscij.2018.09.003

Eliseeva, M. I., and Krieger, E. E. (2021). The peculiarities of parent-child relationship among teenagers who are addicted to online games. Psychol. Educat. Stud. 13, 51–67. doi: 10.17759/psyedu.2021130304

Eliyani, E., and Sari, N. F. (2021). The effect of online game activities on student learn motivation. Jurnal Pelita Pendidikan 9, 65–70. doi: 10.24114/jpp.v9i2.23843

Elliot, A. J., and Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. J. Pers. Soc. Psychol. 72, 218–232. doi: 10.1037/0022-3514.72.1.218

Esposito, M. R., Serra, N., Guillari, A., Simeone, S., Sarracino, F., Continisio, G. I., et al. (2020). An investigation into video game addiction in pre-adolescents and adolescents: a cross-sectional study. Medicina 56:221. doi: 10.3390/medicina56050221

Fan, H., and Gai, X. Y. (2022). A survey study on contemporary college students’ leisure activities and online gaming behavior. Campus Life Mental Health 20, 12–16. doi: 10.19521/j.cnki.1673-1662.2022.01.002

Finn, J. D. (1989). Withdrawing from school. Rev. Educ. Res. 59, 117–142. doi: 10.3102/00346543059002117

Finn, J. D., Pannozzo, G. M., and Voelkl, K. E. (1995). Disruptive and inattentive-withdrawn behavior and achievement among fourth graders. Elem. Sch. J. 95, 421–434. doi: 10.1086/461853

Fredricks, J. A., Blumenfeld, P. C., and Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Rev. Educ. Res. 74, 59–109. doi: 10.3102/00346543074001059

Fredricks, J. A., and McColskey, W. (2012). “The measurement of student engagement: a comparative analysis of various methods and student self-report instruments,” in Handbook of research on student engagement (New York, NY: Springer), 763–782.

Gao, B., Zhu, S. J., and Wu, J. L. (2021). The relationship between cell phone addiction and learning engagement among college students: the mediating role of self-control and the moderating role of core self-evaluation. Psychol. Dev. Educ. 37, 400–406. doi: 10.16187/j.cnki.issn1001-4918.2021.03.11

Gu, M. (2022). Understanding the relationship between distress intolerance and problematic internet use: the mediating role of coping motives and the moderating role of need frustration. J. Adolesc. 94, 497–512. doi: 10.1002/jad.12032

Guo, J. P., Liu, G. Y., and Yang, L. Y. (2021). Mechanisms and models influencing college students’ learning engagement – a survey based on 311 undergraduate higher education schools. Educ. Res. 42, 104–115.

Hafiz, B., and Shaari, J. A. N. (2013). “Confirmatory factor analysis (CFA) of first order factor measurement model-ICT empowerment in Nigeria,” in International Journal of Business Management and Administration . 2, 81–88.

Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate data analysis (7th. New York Pearson Prentice Hall.

Hair, J. F., Hult, T. M., Ringle, C. M., and Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM) . Thousand Oaks, CA SAGE.

Hair, J. F., Ringle, C. M., and Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19, 139–152. doi: 10.2753/MTP1069-6679190202

Haji Anzehai, Z. (2020). Correlation between self-efficacy and addiction to social networks with the motivation of academic achievement in high school students in Tehran. J. Health Promot. Manag. 9, 72–86.

Han, J., and Lu, Q. (2018). “A correlation study among achievement motivation, goal-setting and L2 learning strategy in EFL context,” in English Language Teaching . 11, 5–14.

Hong, J. C., Ye, J. N., Ye, J. H., Wang, C. M., and Cui, Y. T. (2021). Perceived helicopter parenting related to vocational senior high school students’ academic achievement and smartphone addiction. J. Res. Educat. Sci. 66, 1–33. doi: 10.6209/JORIES.202112_66(4).0001

Hong, R. Z., Ye, J. N., Ye, J. H., Wang, C. M., and Cui, Y. T. (2021). A study on the correlation between “mummy’s boys” behavior awareness, academic achievement motivation and cell phone addiction among technology-based high school students. J. Educat. Sci. Res. 66, 1–33. doi: 10.6209/JORIES.202112_66(4).0001

Hu, Q. Z., Wang, L. Y., and Gao, S. B. (2021). The effect of physics teacher trainees’ learning engagement on academic achievement. Higher Educat. Sci. 2021, 53–60.

Hwang, M. Y., Hong, J. C., Ye, J. H., Wu, Y. F., Tai, K. H., and Kiu, M. C. (2019). Practicing abductive reasoning: the correlations between cognitive factors and learning effects. Comput. Educ. 138, 33–45. doi: 10.1016/j.compedu.2019.04.014

Kahu, E. R., and Nelson, K. (2018). Student engagement in the educational interface: understanding the mechanisms of student success. High. Educ. Res. Dev. 37, 58–71. doi: 10.1080/07294360.2017.1344197

Kanat, S. (2019). The relationship between digital game addiction, communication skills and loneliness perception levels of university students. Int. Educ. Stud. 12, 80–93. doi: 10.5539/ies.v12n11p80

Kenny, D. A., Kaniskan, B., and McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociol. Methods Res. 44, 486–507. doi: 10.1177/0049124114543236

Kesici, A. (2020). The effect of conscientiousness and gender on digital game addiction in high school students. J. Educ. Fut. 18, 43–53. doi: 10.30786/jef.543339

Khan, A., Ahmad, F. H., and Malik, M. M. (2017). Use of digital game based learning and gamification in secondary school science: the effect on student engagement, learning and gender difference. Educ. Inf. Technol. 22, 2767–2804. doi: 10.1007/s10639-017-9622-1

Kuh, G. D., Kinzie, J., Cruce, T., Shoup, R., and Gonyea, R. M. (2007). Connecting the dots: multi-faceted analyses of the relationships between student engagement results from the NSSE, and the institutional practices and conditions that foster student success . Bloomington, IN: Indiana University Center for Postsecondary Research.

Lau, S., Liem, A. D., and Nie, Y. (2008). Task-and self-related pathways to deep learning: the mediating role of achievement goals, classroom attentiveness, and group participation. Br. J. Educ. Psychol. 78, 639–662. doi: 10.1348/000709907X270261

Li, Y., Yao, C., Zeng, S., Wang, X., Lu, T., Li, C., et al. (2019). How social networking site addiction drives university students’ academic achievement: the mediating role of learning engagement. J. Pac. Rim Psychol. 13:e19. doi: 10.1017/prp.2019.12

Liang, L., Zhu, M., Dai, J., Li, M., and Zheng, Y. (2021). The mediating roles of emotional regulation on negative emotion and internet addiction among Chinese adolescents from a development perspective. Front. Psych. 12:608317. doi: 10.3389/fpsyt.2021.608317

Lu, L., Zhang, L., and Wang, L. (2022). The relationship between vocational college students’ liking of teachers and learning engagement: a moderated mediation model. Front. Psychol. 13:998806. doi: 10.3389/fpsyg.2022.998806

Luan, L., Hong, J. C., Cao, M., Dong, Y., and Hou, X. (2020). Exploring the role of online EFL learners’ perceived social support in their learning engagement: a structural equation model. Interact. Learn. Environ. 31, 1703–1714. doi: 10.1080/10494820.2020.1855211

MacKinnon, D. P. (2012). Introduction to statistical mediation analysis . New York Routledge.

McClelland, D. C., Atkinson, J. W., Clark, R. A., and Lowell, E. L. (1976). The achievement motive . Appleton-Century-Crofts, New York.

Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., and McDonough, I. M. (2018). The effects of cellphones on attention and learning: the influence of time, distraction, and nomophobia. Comput. Hum. Behav. 86, 52–60. doi: 10.1016/j.chb.2018.04.027

Meral, S. A. (2019). Students’ attitudes towards learning, a study on their academic achievement and internet addiction. World J. Educat. 9, 109–122. doi: 10.5430/wje.v9n4p109

Miao, J., and Ma, L. (2022). Students’ online interaction, self-regulation, and learning engagement in higher education: the importance of social presence to online learning. Front. Psychol. 13:815220. doi: 10.3389/fpsyg.2022.815220

Mih, V., Mih, C., and Dragoş, V. (2015). Achievement goals and behavioral and emotional engagement as precursors of academic adjusting. Procedia Soc. Behav. Sci. 209, 329–336. doi: 10.1016/j.sbspro.2015.11.243

Nakagawa, S., and Cuthill, I. C. (2007). Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. 82, 591–605. doi: 10.1111/j.1469-185X.2007.00027.x

Nong, W., He, Z., Ye, J.-H., Wu, Y.-F., Wu, Y.-T., Ye, J. N., et al. (2023). The relationship between short video flow, addiction, serendipity, and achievement motivation among Chinese vocational school students: the post-epidemic era context. Healthcare 11:462. doi: 10.3390/healthcare11040462

Pan, Y., Zhou, D., and Shek, D. T. L. (2022). Participation in after-school extracurricular activities and cognitive ability among early adolescents in China: moderating effects of gender and family economic status. Front. Pediatr. 10:839473. doi: 10.3389/fped.2022.839473

Qi, H. Y., Liu, J. H., Hou, Y. H., Fan, W. F., Hou, J. P., and Wang, X. Y. (2020). The effect of cell phone addiction types on college students’ learning engagement. Health Prot. Promot. 2020, 88–91. doi: 10.3969/j.issn.1671-0223(x).2020.05.023

Rozgonjuk, D., Saal, K., and That, K. (2018). Problematic smartphone use, deep and surface approaches to learning, and social media use in lectures. Int. J. Environ. Res. Public Health 15:92. doi: 10.3390/ijerph15010092

Saeid, N., and Eslaminejad, T. (2017). Relationship between student’s self-directed-learning readiness and academic self-efficacy and achievement motivation in students. Int. Educ. Stud. 10, 225–232. doi: 10.5539/ies.v10n1p225

Schaufeli, W. B., Martinez, I. M., Pinto, A. M., Salanova, M., and Bakker, A. B. (2002). Burnout and engagement in university students: a cross-national study. J. Cross-Cult. Psychol. 33, 464–481. doi: 10.1177/0022022102033005003

Selya, A. S., Rose, J. S., Dierker, L. C., Hedeker, D., and Mermelstein, R. J. (2012). A practical guide to calculating Cohen’s f 2 , a measure of local effect size, from PROC MIXED. Front. Psychol. 3:111. doi: 10.3389/fpsyg.2012.00111

Shao, Y., and Kang, S. (2022). The link between parent-child relationship and learning engagement among adolescents: the chain mediating roles of learning motivation and academic self-efficacy. Front. Educat. 7:854549. doi: 10.3389/feduc.2022.854549

Shek, D. T., Zhu, X., and Dou, D. (2019). Influence of family processes on internet addiction among late adolescents in Hong Kong. Front. Psych. 10:113. doi: 10.3389/fpsyt.2019.00113

Shumacker, R. E., and Lomax, R. G. (2016). A beginner’s guide to structural equation modeling (4th) New York, NY: Routledge.

Sopiah, C. (2021). The influence of parenting style, achievement motivation and self-regulation on academic achievement. Turk. J. Comput. Math. Educ. 12, 1730–1742. doi: 10.17762/turcomat.v12i10.4635

Stipek, D. (2002). “Good instruction is motivating” in Development of achievement motivation . eds. A. Wigfield and J. Eccles (San Diego, CA: Academic Press)

Story, P. A., Hart, J. W., Stasson, M. F., and Mahoney, J. M. (2009). Using a two-factor theory of achievement motivation to examine performance-based outcomes and self-regulatory processes. Personal. Individ. Differ. 46, 391–395. doi: 10.1016/j.paid.2008.10.023

Sunday, O. J., Adesope, O. O., and Maarhuis, P. L. (2021). The effects of smartphone addiction on learning: a meta-analysis. Comput. Hum. Behav. Rep. 4:100114. doi: 10.1016/j.chbr.2021.100114

Teng, Z., Pontes, H. M., Nie, Q., Griffiths, M. D., and Guo, C. (2021). Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: a longitudinal study. J. Behav. Addict. 10, 169–180. doi: 10.1556/2006.2021.00016

Thompson, B. (2002). What future quantitative social science research could look like: confidence intervals for effect sizes. Educ. Res. 31, 25–32. doi: 10.3102/0013189X031003025

Tian, J., Zhao, J. Y., Xu, J. M., Li, Q. L., Sun, T., Zhao, C. X., et al. (2021). Mobile phone addiction and academic procrastination negatively impact academic achievement among Chinese medical students. Front. Psychol. 12:758303. doi: 10.3389/fpsyg.2021.758303

Tsai, S. M., Wang, Y. Y., and Weng, C. M. (2020). A study on digital games internet addiction, peer relationships and learning attitude of senior grade of children in elementary school of Chiayi county. J. Educat. Learn. 9, 13–26. doi: 10.5539/jel.v9n3p13

Wang, M. T., and Eccles, J. S. (2013). School context, achievement motivation, and academic engagement: a longitudinal study of school engagement using a multidimensional perspective. Learn. Instr. 28, 12–23. doi: 10.1016/j.learninstruc.2013.04.002

Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychol. Rev. 92, 548–573. doi: 10.1037/0033-295X.92.4.548

World Health Organization (WHO) (2018a). Inclusion of “gaming disorder” in ICD-11 . Available at: https://www.who.int/news/item/14-09-2018-inclusion-of-gaming-disorder-in-icd-11

World Health Organization (WHO) (2018b). WHO releases new international classification of diseases (ICD11) . Available at: https://www.who.int/news/item/18-06-2018-who-releases-new-international-classification-of-diseases-(icd-11)

Wu, Y.-T., Hong, J.-C., Wu, Y.-F., and Ye, J.-H. (2021). eSport addiction, purchasing motivation and continuous purchasing intention on eSport peripheral products. Int. J. e-Education e-Business e-Management e-Learning 11, 21–33. doi: 10.17706/ijeeee.2021.11.1.21-33

Xiang, G. X., Gan, X., Jin, X., and Zhang, Y. H. (2022a). The more developmental assets, the less internet gaming disorder? Testing the cumulative effect and longitudinal mechanism during the COVID-19 pandemic. Curr. Psychol. 1–12, 1–12. doi: 10.1007/s12144-022-03790-9

Xiang, G. X., Gan, X., Jin, X., Zhang, Y. H., and Zhu, C. S. (2022b). Developmental assets, self-control and internet gaming disorder in adolescence: testing a moderated mediation model in a longitudinal study. Front. Public Health 10:808264. doi: 10.3389/fpubh.2022.808264

Xiang, G. X., Li, H., Gan, X., Qin, K. N., Jin, X., and Wang, P. Y. (2022c). School resources, self-control and problem behaviors in Chinese adolescents: a longitudinal study in the post-pandemic era. Curr. Psychol. 1-13, 1–13. doi: 10.1007/s12144-022-04178-5

Xiong, Y., Li, H., Kornhaber, M. L., Suen, H. K., Pursel, B., and Goins, D. D. (2015). Examining the relations among student motivation, engagement, and retention in a MOOC: a structural equation modeling approach. Glob. Educ. Rev. 2, 23–33.

Yang, J., Peng, M. Y. P., Wong, S., and Chong, W. (2021). How E-learning environmental stimuli influence determinates of learning engagement in the context of COVID-19? SOR model perspective. Front. Psychol. 12:584976. doi: 10.3389/fpsyg.2021.584976

Yang, X., Zhang, M., Kong, L., Wang, Q., and Hong, J. C. (2021). The effects of scientific self-efficacy and cognitive anxiety on science engagement with the “question-observation-doing-explanation” model during school disruption in COVID-19 pandemic. J. Sci. Educ. Technol. 30, 380–393. doi: 10.30773/pi.2020.0034

Yayman, E., and Bilgin, O. (2020). Relationship between social media addiction, game addiction and family functions. Int. J. Evaluat. Res. Educat. 9, 979–986. doi: 10.11591/ijere.v9i4.20680

Ye, J. H., Wang, C. M., and Ye, J. N. (2020). An analysis of the relationship between achievement motivation, learning engagement and continuous improvement attitudes of technical vocational college students. J. Natl. Taichung Univ. Sci. Technol. 7, 1–20. doi: 10.6902/JNTUST.202012_7(2).0001

Ye, J. H., Wu, Y. F., Nong, W., Wu, Y. T., Ye, J. N., and Sun, Y. (2023). The association of short-video problematic use, learning engagement, and perceived learning ineffectiveness among Chinese vocational students. Healthcare 11:161. doi: 10.3390/healthcare11020161

Ye, J. H., Wu, Y. T., Wu, Y. F., Chen, M. Y., and Ye, J. N. (2022). Effects of short video addiction on the motivation and well-being of Chinese vocational college students. Front. Public Health 10:847672. doi: 10.3389/fpubh.2022.847672

Yu, L., and Shek, D. T. L. (2013). Internet addiction in Hong Kong adolescents: a three-year longitudinal study. J. Pediatr. Adolesc. Gynecol. 26, S10–S17. doi: 10.1016/j.jpag.2013.03.010

Zhang, N. (2012). A review of Chinese domestic and international research on learning engagement and its school influences. Psychol. Res. 5, 83–92.

Zhang, Y., Qin, X., and Ren, P. (2018). Adolescents’ academic engagement mediates the association between internet addiction and academic achievement: the moderating effect of classroom achievement norm. Comput. Hum. Behav. 89, 299–307. doi: 10.1016/j.chb.2018.08.018

Zhao, H., Xiong, J., Zhang, Z., and Qi, C. (2021). Growth mindset and college students’ learning engagement during the COVID-19 pandemic: a serial mediation model. Front. Psychol. 12:621094. doi: 10.3389/fpsyg.2021.621094

Zhou, H. (2009). The effect of cooperative learning in basketball teaching on social behavior and academic achievement motivation. Zhejiang Sport Sci. 31, 109–112.

Keywords: college students, online game addiction, learning engagement, reduced academic achievement motivation, online games

Citation: Sun R-Q, Sun G-F and Ye J-H (2023) The effects of online game addiction on reduced academic achievement motivation among Chinese college students: the mediating role of learning engagement. Front. Psychol . 14:1185353. doi: 10.3389/fpsyg.2023.1185353

Received: 13 March 2023; Accepted: 08 June 2023; Published: 13 July 2023.

Reviewed by:

Copyright © 2023 Sun, Sun and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jian-Hong Ye, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Internet Gaming Addiction: A Technological Hazard

Ankur sachdeva.

1 Department of Psychiatry, ESIC Medical College and Hospital, Faridabad, India

Rohit Verma

2 Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India

Introduction:

The Internet is considered a beneficial tool in research, communication, and information. Still, its excessive and prolonged use has the potential of causing addiction. The presentation of this technological hazard may range from a mild socio-personal distress to a gross disorganization in behavior and self-care. No reported study on Internet gaming addiction is available from India.

Case Presentation:

We reported a case of two brothers, diagnosed with Internet gaming addiction, who showed grossly disorganized behavior and severely compromised self-care. The condition was managed by pharmacological and non-pharmacological therapies, with sustained improvement after 6 months follow up.

Conclusions:

Internet gaming addiction may cause severe personal, social, and occupational problems. Despite the range of severity and various presentations of this disorder, DSM-5 lacks the severity classifier. Early identification and management may result in complete recovery.

1. Introduction

Rapid and extensive proliferation of the Internet has resulted in better opportunities for research, communication, and information. Useful to some extent, this modern day technological wonder has largely caused decline in physical and mental well-being owing to its potential for causing addiction in the form of pornography, excessive gaming, chatting for long hours, gambling, and online shopping.

Goldberg in 1995 introduced the term “Internet addiction” for pathological compulsive Internet use ( 1 ). Excessive Internet gaming has been described as a specific subtype of Internet addiction ( 2 ). According to some reports, up to 90% of American youngsters play video games and about 15% of them may be addicted ( 3 ). Internet gaming disorder has been placed in category III of DSM-5 ( 4 ). Still, it has not been classified under main disorders as adequate research-based evidence is lacking. The presentation of Internet gaming disorder may range from a mild socio-personal distress to a gross disorganization in behavior and self-care. However, the DSM-5 lacks the severity classifier. The understanding of Internet addiction is still in initial stages in Indian subcontinent. No reported studies on Internet gaming addiction are available from India. We report two brothers diagnosed with Internet gaming addiction, with grossly disorganized behavior and severely compromised self-care. We managed their problem with behavior therapy and fluoxetine.

2. Case Presentation

Messrs A and B were two unmarried brothers, belonging to a nuclear family of upper socioeconomic class of urban background of Delhi. Mr A is 19 years old, studying in 12 th standard while Mr B is 22 years old, studying in 2 nd year of engineering in Haryana, India.

Both brothers were brought by their parents with the complaints of insidious onset, gradually progressive excessive online gaming, irritability, decline in studies performance, and impaired self-care for the past 2 years. The problem began when both brothers used to stay together at home and started playing online game with their virtual Internet friends from different countries. Due to difference in GMT (Greenwich mean time) across all countries, they had no specific timing for games and hence the gaming interfered with their sleep and daily routine. The duration of online gaming progressed from 2 - 4 hours per day to 14 - 18 hours per day over the initial few months. The behavior and self-care of these brothers became so compromised and disorganized that while playing the games, they urinated and defecated in their clothes, did not change clothes for days, did not bathe, skipped their meals, did not pick up phones or open doors even to their parents. They were not concerned even when strangers entered the house in their presence and robbed the house. Their home was robbed twice of cash and costly articles in their presence, during the last 2 months while they were preoccupied in playing online games. They both failed in their respective classes last year although they were meritorious students. They shouted at parents, abuse and hit them and even locked in their rooms when stopped from playing game.

The patients were admitted in view of above problems, the severity of gaming addiction. Their general physical examination, systemic examination, and laboratory investigation were within normal limits. On interviewing, irritability, and craving for games was elicited. No psychotic symptoms were reported or elicited. The aim of the treatment was to reduce irritability, improve sleep, daily routine, and self-care along with enhancing motivation and reducing craving for online games to prevent future relapses. Diagnostic psychometric assessment revealed impulse control problems, depressive cognitions, and delinquency in both brothers.

Fluoxetine 20 mg/day was started (increased to 40 mg/day) along with clonazepam 0.5 mg as required for sleep. Non-pharmacological methods were the main stay of management. It included limit setting, motivational interviewing, motivation enhancement therapy, activity scheduling, family and individual therapy, distraction techniques, and positive reinforcement using principles of behavior therapy. During the one month stay in the hospital, both patients improved considerably with reduced irritability and craving for online games, better self-care and hygiene, improved sleep, and interest in studies. The improvement maintained during the 6 months follow up, even after stopping fluoxetine with simple methods of behavior therapy using parents as co-therapists.

3. Discussion

Internet is undoubtedly a remarkable invention. When used properly with good intention, it has great technological value in research, communication, information, leisure activities, business transactions, and learning. However, there is always a dark side to new technologies. In case of Internet, it turns to an addiction which is a recent concept and still under research. Internet gaming addiction is the latest phenomenon in the world of Internet ( 5 ). For many adolescents, spending time on the computer means playing online video games. A market research company has estimated the China’s worth online gaming market as $12 billion in 2013. A recent review article reported prevalence estimates ranging from 0.2% in Germany to 50% in Korean teenagers ( 6 ).

Although Internet gaming disorder has not been classified under main disorders of DSM-5, researchers have realized that Internet gaming is increasingly being used by people of all ages, especially younger population, who may face severe consequences associated with compulsive use of games ( 6 ). According to DSM-5 ( 4 ), Internet gaming disorder refers to the “persistent and recurrent use of the Internet to engage in games, often with other players, leading to clinically significant impairment or distress as indicated by 5 (or more) criteria in a 12-month period.” These criteria comprise lack of control over the use of Internet games, preoccupation with Internet gaming, psychological withdrawal, developing tolerance for games and need for increase use of games, loss of other significant interests, use of Internet games despite negative consequences, and significant decline in social and occupational domains ( 4 , 6 ). All these signs and symptoms were observed or reported in the described case report of patients. Internet gaming addiction is a disorder that is most dramatically expressed with games known as massively multiplayer online games (MMOs) ( 7 ) and specially massively multiplayer online role-playing games (MMORPGs) like World of Warcraft ( 8 ). MMORPGs are games played by thousands of players at the same time (massively multiplayer). Because these games are played online, there are no spatial or temporal boundaries and they allow players to adopt various virtual roles. MMORPGs utilize the principles of operant conditioning by using highly reinforcing random reward patterns. Hence, these games are specially engineered to maximize the amount of time a player stays in the game. The same was observed in the patients where they used to play such games with virtual friends across different countries and at odd hours.

There is a growing concern about several negative consequences associated with Internet gaming addiction. The psychological consequences vary and include difficulty in real-life relationships, disturbances in sleep, work, education, socializing, attention, academics, and memory. It may include aggression and hostility, stress, and high loneliness ( 6 , 9 - 11 ). Most of these disturbances were evident in both patients.

Considering the shared features with addiction disorders, which are evident from the above case, Internet gaming addiction could be placed alongside the main disorders in the future classificatory systems. DSM-5 needs to consider the severity classifiers for the disorder, which might present variedly depending upon the content and type of games, cultural context of gaming, and associated personality type. Internet addiction is a new and emerging group of disorders in Indian subcontinent ( 12 ). It has proliferated and spread across the subcontinent, in spite of deeply knit family systems and parental supervision. Systematic studies need to be undertaken in Indian subcontinent to evaluate the prevalence and type of gaming addiction. Crucial steps in curtaining this evolving epidemic must be taken in the form of legal limitations on sale/purchase, setting the age limit, and restricting access to online games.

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    Abstract Internet game addiction is becoming a severe problem in adolescents. The purpose of this article was to present a case study on Internet game addiction. The effects of a new program to treat Internet game addiction based on cognitive-behavioral therapy, behavior modification, and a 12-step program are described.

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    Internet game addiction is becoming a severe problem in ado- lescents. The purpose of this article was to present a case study on Internet game addiction. The effects of a new program to treat Internet game addiction based on cognitive-behavioral therapy, behavior modification, and a 12-step program are described.

  3. A case study of Internet Game Addiction

    The purpose of this article was to present a case study on Internet game addiction. The effects of a new program to treat Internet game addiction based on cognitive-behavioral therapy, behavior modification, and a 12-step program are described. The subject in this case study was a 16-year-old Korean adolescent who lived in the United States.

  4. Internet gaming addiction: current perspectives

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  5. Treatments for Internet Gaming Disorder and Internet Addiction: A

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  7. A case study of Internet Game Addiction

    A case study of Internet Game Addiction Eun Jin Lee , R.N., Ph.D., APRN Pages 208-213 | Published online: 16 Jan 2012 Cite this article https://doi.org/10.3109/10884602.2011.616609 Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article Internet game addiction is becoming a severe problem in adolescents.

  8. Internet Gaming Disorder Treatment: A Case Study Evaluation of Four

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  11. The Role of Context in Online Gaming Excess and Addiction: Some Case

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  12. A case study of Internet Game Addiction

    The purpose of this article was to present a case study on Internet game addiction. The effects of a new program to treat Internet game addiction based on cognitive‐behavioral therapy, behavior modification, and a 12‐step program are described. The subject in this case study was a 16‐year‐old Korean adolescent who lived in the United ...

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    spends playing video games. The client claims that on a typical weekday, he will spend between three and five hours playing video games, but on the weekends, he uses the internet for roughly thirteen hours per day (Lee, 2011). Addiction to online gaming is a process addiction. The DSM-5 describes internet addiction as "1) excessive use, often associated with a loss of sense of time or a ...