The digital game sector has recently been growing in both quality and quantity. Digital games have become a popular leisure medium in many countries, and are increasingly expanding into various areas, such as e-sports and live streaming, in formats including Twitch and YouTube. However, with increased awareness of the positive effects of these games for the economy through their distribution, social concern is rising about their adverse effects and negative consequences, such as pathological gaming, namely, excessive use of games with resulting symptoms of mental, emotional, physical, and social problems (Jeong & Kim, 2011). In particular, the World Health Organization (2018) officially recognized gaming disorder as a disease in the 11th edition of the International Classification of Diseases. Gaming disorder involves persistent gaming behavior, impaired control over gaming, and functional impairment (King et al., 2020). The debate over whether pathological gaming is a pathological disease or a cognitive problem has recently become more intense (Aarseth et al., 2017; van Rooij et al., 2018).

There has been steady support for the proposal that preventing negative damage from pathological gaming requires identification of the various factors leading to problematic behaviors, and recommendations have been made to obtain greater clarity in the relationships of these influencing factors (Jeong & Kim, 2011; Mei et al., 2016). If pathological gaming is triggered by negative social and psychological factors, it may be difficult to solve the related fundamental problems by simply reducing the amount of gaming time or administering medication.

Various studies have been conducted in an attempt to uncover the psychological or environmental factors leading to pathological gaming, and to verify the causality in these relationships (Krossbakken et al., 2018; Servidio et al., 2018). Adolescents are the most active age group in using games (Granic et al., 2014) and, in particular, the aspects of parent, peer, and teacher as environmental factors, and the psychological variables related to the formation and development of the self-concept of these game users, have drawn researchers’ attention (Mei et al., 2016; Younes et al., 2016). The psychological variables of self-assessment and ability to control oneself have been found to have a major impact on the curbing or promoting of problematic addictive behaviors (Bozoglan et al., 2013; Tangney et al., 2004).

Self-esteem refers to individuals’ positive assessment of or perceived affection for themselves (J. D. Brown et al., 2001), and it helps individuals to maintain a positive personal assessment despite negative external stimuli and to prevent deviant behavior through frustration (J. D. Brown & Marshall, 2001). Low self-esteem is a factor in individuals’ loss of self-control, lack of belief in their worth, frustration, and obsessive use of social media (Bozoglan et al., 2013; Yao et al., 2014). Thus, the lower individuals’ self-esteem is, the more reluctant they will be to face the gap between what is ideal and what is real; consequently, they will find it hard to understand the practical side effects of addiction or control behavior (Mei et al., 2016). Thus, individuals with low self-esteem will likely try to restore their positive self-expectations by focusing on their achievement in digital games as a form of compensation mentality (King & Delfabbro, 2014). Self-esteem affects cyber addiction; in particular, low self-esteem increases the negative impact of immersing oneself in pathological gaming (Lemmens et al., 2011; Servidio et al., 2018).

Self-control involves individuals’ ability to control their behavior to achieve long-term goals, and to restrain themselves from choosing impulsive actions for short-term gains (Baumeister & Vohs, 2004; Tangney et al., 2004). Low self-control is strongly linked to the pursuit of instant gratification and impulsive behavior (Cao et al., 2007), and to deviant behaviors, including addiction (Davis, 2001; Özdemir et al., 2014). Therefore, self-control is a powerful factor in predicting pathological gaming. Chen and Leung (2016) reported in a study on mobile game users that the lower individuals’ self-control is, the more vulnerable they are to pathological gaming. In contrast, high self-control inhibits problematic game behaviors and pathological gaming (E. J. Kim et al., 2008).

Adolescents are vulnerable to problems such as pathological gaming because, compared to adults, they are less physically and mentally mature. In addition, addiction behavior is influenced not only by individuals’ psychological state, but also by their social environment or context (Orford, 2001). These environmental factors play an important role in young people’s behaviors because adolescence is when they establish their self-concept through contacts with surrounding people, including parents, friends, and teachers (Miklikowska et al., 2019).

Parental support has a decisive effect on adolescents’ identity development and negative behaviors, such as substance addiction (Soh et al., 2018). Stable ties and regular parental communication can help prevent adolescents from experiencing emotional and behavioral problems. In contrast, parents’ negative nurturing style can negatively affect their adolescent children’s self-identity formation, leading them to exhibit problematic behaviors (E. H. Lee & Jeong, 2006; Miller et al., 2006). Negative nurturing parents tend to control or interfere excessively with their child’s daily routine. Such intrusiveness combined with high parental stress has been found to be associated with adolescents’ pathological gaming (Charoenwanit & Sumneangsanor, 2014).

Teenagers’ peer relationships also have an important effect on their mental health and self-formation. Higher peer-rated crowd status has been found to be related to high self-esteem owing to a sense of belonging (B. B. Brown & Lohr, 1987), and peer attachment has been observed to be correlated with high self-esteem via empathy and prosocial behavior (Gorrese & Ruggieri, 2013). Experience with peer groups positively affects adolescent self-control, and Meldrum and Hay (2012) reported in a long-term study of 776 children that peer behavior had a significant effect on their self-control.

The role of teachers is also an important factor affecting adolescents, who spend much of their time in school (Miklikowska et al., 2019). By forming positive relationships with their adolescent students, teachers can help them create a positive self-identity, and ease their emotional and behavioral problems, including pathological gaming (Joyce & Early, 2014). In particular, the strong academic stress caused by Korean parents’ pressure on their adolescent children, and the expectation that the adolescents will later attend an advanced school, could bring about negative results and pose a direct threat for development of gaming disorder (M. Lee & Larson, 2000). Teachers can intervene in their students’ academic stress experience, to help avoid this having a significant impact on the likelihood of developing a problem with gaming (Jia et al., 2017), and damaging students’ self-control (Tice et al., 2001). This damage can adversely affect adolescents’ self-esteem, which serves as a protective factor against stress in the long term.

Although previous researchers have examined the association between environmental factors (parents, peers, and teachers) and the psychological factors of self-esteem and self-control (Gorrese & Ruggieri, 2013; Tangney et al., 2004), few have examined their effect on pathological gaming, and those who have done so used cross-sectional data (E. J. Kim et al., 2008). Moreover, few researchers have examined the effects of self-esteem and self-control on adolescents’ pathological gaming using a model in which these environmental factors are considered as subdimensions.

Thus, we aimed to empirically verify a path model of how environmental factors affect psychological factors in relation to self-identify formation, and, ultimately, how they affect pathological gaming among South Korean adolescents. We proposed the following hypotheses:
Hypothesis 1a: Parental environment will be positively associated with adolescents’ self-control.
Hypothesis 1b: School environment will be positively associated with adolescents’ self-control.
Hypothesis 1c: Peer environment will be positively associated with adolescents’ self-control.
Hypothesis 2a: Parental environment will be positively associated with adolescents’ self-esteem.
Hypothesis 2b: School environment will be positively associated with adolescents’ self-esteem.
Hypothesis 2c: Peer environment will be positively associated with adolescents’ self-esteem.

We also proposed the following research question:
Research Question 1: How do the psychological factors of self-identity and self-control affect pathological gaming among adolescents?

Method

Participants and Procedure

Prior to commencing the study we obtained approval from the Konkuk University Ethics Committee. We conducted a panel survey with 2,000 adolescents in South Korea, aged from 10 to 16 years, who played video games. We used a quota sampling method based on school grade and gender ratio. Trained professional interviewers met the students face-to-face to get responses to the measure three times (6-month intervals between each wave), using established survey guidelines. Participants each received KRW 30,000 (USD 27.00) as compensation for taking part in the study.

After surveys with incomplete responses had been eliminated, data from 1,037 respondents were analyzed. Of the participants, 517 (49.9%) were boys and young men and 520 (50.1%) were girls and young women (M_age = 13.36 years, SD = 2.44). Regarding age group and grade level at school, there were 340 (32.8%) students in elementary school (M_age = 10.46 years, SD = 0.59), 382 (36.8%) students in middle school (M_age = 13.40 years, SD = 0.63), and 315 (30.4%) students in high school (M_age = 16.36 years, SD = 0.79).

Measures

Translation of measures that were developed in the English language was completed by professional translators.

Pathological Gaming
To measure pathological gaming we adopted Young’s (1998) 20-item Internet Game Addiction Scale. The scale has been translated into Korean and used in a number of previous studies (see, e.g., Jeong & Kim, 2011). Items are rated on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree. Sample items are “I often find that I play a game for longer than I initially intended” and “I often find myself saying ‘Just a few more minutes’ when gaming.” Cronbach’s alpha in our study was .96.

Self-Control
To measure self-control we used three items from Tangney et al.’s (2004) Brief Self-Control Scale. Items are rated on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree. A sample item is “It is not difficult for me to concentrate.” Cronbach’s alpha in our study was .79.

Self-Esteem
To measure self-esteem we used nine items from the Rosenberg Self-Esteem Scale (Rosenberg, 1965). Items are rated on a 4-point Likert scale ranging from 1 = completely disagree to 4 = completely agree. A sample item is “I feel that I am a person of worth, at least on an equal plane with others.” Cronbach’s alpha in our study was .85.

Parental Environment
To assess parental environment we adopted 13 items from previous studies on parents’ nurturing styles and communication (Liu et al., 2015; National Youth Policy Institute, 2013). Exploratory factor analysis with varimax rotation according to the Kaiser rule (i.e., eigenvalue > 1.0), yielded four components: parents’ affection, parents’ rationality, parents’ excessive interference, and communication with parents (eigenvalues = 5.02, 1.74, 1.12, and 1.00, respectively). Items are rated on a 4-point Likert scale ranging from 1 = completely disagree to 4 = completely agree.
Parents’ affection and rationality. We used four items to measure parents’ affection (e.g., “My parents express that they like me”), and three items to assess parents’ rationality (e.g., “Parents explain why their children should do as they say instead of forcing them to follow their decisions unconditionally”). Cronbach’s alphas in this study were .63 for affection and .76 for rationality.
Parents’ excessive interference and communication with parents. We used three items to measure parents’ excessive interference (e.g., “Often, my parents don’t let me do what I want”), and three items to measure communication with parents (e.g., “It is easy for me to express all my true feelings to my parents”). Cronbach’s alphas in our study were .70 for excessive interference and .82 for communication.

School Environment
To measure the school environment we used seven items on academic stress and students’ relationship with teachers from the Life Stress and Coping Scale (Choi & Moon, 2010; Seo & Kim, 2006). Two subdimensions (academic stress and teacher support) were extracted (eigenvalues = 2.85 and 1.73, respectively).
Academic stress and teacher support. To measure academic stress we used four items about pressure from tests and grades. Items were rated on a 3-point Likert scale ranging from 1 = never to 3 = often (e.g., “I wasn’t focused on studying”). To assess teacher support we used three items rated on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree (e.g., “My teacher often encourages me when I am facing some difficulty”). Cronbach’s alphas were .71 for academic stress and .87 for teacher support.

Peer Environment
To measure peer environment we adopted six items from previous studies on peer relationships (e.g., K. H. Kim & Chon 1993). Two components were extracted: peer stress and peer support (eigenvalues = 3.03 and 1.33, respectively).
Peer stress and peer support. To measure peer stress we used three items about difficulty in communicating and associating with friends (e.g., “I was bullied by a friend”; α = .74). Items were rated on a 3-point Likert scale ranging from 1 = never to 3 = often. To measure peer support we used three items (e.g., “When I am sad, my friends comfort me”; α = .86). Items were rated on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

Daily Gaming Time
We asked participants about the average time they spent daily on gaming (i.e., “How many hours in a day do you play games?”), with nine response options: 1 (none), 2 (less than 30 minutes), 3 (30 minutes to 1 hour), 4 (1–2 hours), 5 (2–3 hours), 6 (3–4 hours), 7 (4–5 hours), 8 (5–6 hours), and 9 (over 6 hours).

Results

All the constructs were tested in a reliability assessment of the multi-item measures (see Table 1). The correlations and discriminant validity of the constructs were also checked (see Table 2). The results indicate the measures showed adequate validity, on the basis of the recommendations by Chin (1998): composite reliability of .80 and average variance extracted of .50.

The structural equation modeling results yielded adequate valid indices for the model fit, comparative fit index (CFI) = .90, incremental fit index (IFI) = .90, root mean square error of approximation (RMSEA) = .044 (see Figure 1). We calculated 1,000 bootstrapped resamples with 95% confidence intervals (CIs) to increase confidence in the results. At Time 3 both Time 2 self-control and Time 2 self-esteem showed negative effects on pathological gaming, β = −.32, 95% CI [−0.42, −0.23] and β = −.12, 95% CI [−0.21, −0.04], respectively. Gaming time (Time 2), however, increased pathological gaming, β = .23, 95% CI [0.17, 0.29]. School environment (Time 1) was most strongly associated with self-control, β = .49, 95% CI [0.34, 0.67], and parental environment was most strongly associated with self-esteem, β = .40, 95% CI [0.32, 0.48]. Finally, gaming time (Time 1) negatively affected self-control, β = −.07, 95% CI [−0.13, −0.01]. Thus, all the hypotheses were supported. In addition, both self-control and self-esteem negatively affected pathological gaming.

Discussion

We empirically tested the effects of South Korean adolescents’ self-esteem and self-control on their degree of pathological gaming, in an integrated path model. Our findings indicate that adolescents with greater self-control and higher self-esteem showed a low degree of pathological gaming. Further, self-control (vs. gaming time) had a much stronger effect on pathological gaming. These results show the critical role of psychological factors related to self-identity formation in preventing pathological gaming among adolescents, regardless of gaming time.

It is notable that the school environment had a far greater effect on self-control than did gaming time. Self-control was strengthened by the school environment, which, in turn, decreased pathological gaming. As the school environment assessment in our study consisted of measures of academic stress and teachers’ support, our results indicate that a decrease in academic stress and an increase in teachers’ support can protect adolescents from the negative results of excessive gaming by increasing their self-control. These results are in line with those of previous studies supporting the deficient self-regulation model (LaRose et al., 2003; Tice et al., 2001), in which the focus is on lower self-control as a critical antecedent to pathological gaming. Adolescents’ pathological gaming is closely associated with lack of self-control, that is, those with low self-control are susceptible to pathological gaming (E. J. Kim et al., 2008).

Our results also show that self-esteem, which was mostly influenced by the parental environment, diminished pathological gaming. This implies that parents who have a positive attitude toward their adolescent children, including treating them with rationality, affection, and communication, and do not hold negative attitudes toward them as characterized by excessive interference, can inhibit the adolescents’ development of pathological gaming by enhancing their self-esteem.

This study has several practical implications. First, we examined the influence of self-control and self-esteem on pathological gaming, which has not been previously tested in an integrated model of pathological gaming. Next, we empirically examined if self-control and self-esteem, as affected by environmental factors, are crucial determinants of pathological gaming in the integrated model, including assessing the subdimensions of each construct. We found that academic stress, a subfactor of school environment, and parents’ affection and communication, two subfactors of parental environment, were strongly associated with pathological gaming. Our results provide game policymakers and activists with practical ideas for how to prevent pathological gaming among adolescents. Existing policies in South Korea that aim to protect adolescents from pathological gaming are mainly focused on blocking gaming time (C. Lee et al., 2017). As our results show, however, environmental conditions had a much greater impact on pathological gaming than did gaming time; thus, improving the environmental conditions of adolescents may have a better and more effective impact on pathological gaming than will deterrence of gaming time. Specifically, the government could aim to improve school systems by enacting policies focused on lessening adolescents’ academic stress, or provide programs to help parents communicate more effectively with their children.

There are several limitations in this study. First, participants were all from South Korea, where, because examinations for college entrance are highly competitive, adolescents are strongly influenced by their parents to maintain high grades. These cultural characteristics could have significantly influenced the results. Future researchers could replicate this study with other populations to examine the generalizability of our results across countries. Second, more diverse variables could be included to compare their effect sizes on pathological gaming. Models from different theories and perspectives could then be compared with various data. Finally, all measurements were self-reported. To address the possibility of social desirability bias influencing the results, future researchers could adopt other systems of measurement, such as using behavioral scales.

Aarseth, E., Bean, A. M., Boonen, H., Colder Carras, M., Coulson, M., Das, D., … Van Rooij, A. J. (2017). Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal. Journal of Behavioral Addictions, 6(3), 267–270.
https://doi.org/10.1556/2006.5.2016.088

Baumeister, R. F., & Vohs, K. D. (Eds.). (2004). Handbook of self-regulation: Research, theory, and applications. Guilford Press.

Bozoglan, B., Demirer, V., & Sahin, I. (2013). Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: A cross-sectional study among Turkish university students. Scandinavian Journal of Psychology, 54(4), 313–319.
https://doi.org/10.1111/sjop.12049

Brown, B. B., & Lohr, M. J. (1987). Peer-group affiliation and adolescent self-esteem: An integration of ego-identity and symbolic-interaction theories. Journal of Personality and Social Psychology, 52(1), 47–55.
https://doi.org/10.1037/0022-3514.52.1.47

Brown, J. D., Dutton, K. A., & Cook, K. E. (2001). From the top down: Self-esteem and self-evaluation. Cognition and Emotion, 15(5), 615–631.
https://doi.org/10.1080/02699930126063

Brown, J. D., & Marshall, M. (2001). Self-esteem and emotion: Some thoughts about feelings. Personality and Social Psychology Bulletin, 27(5), 575–584.
https://doi.org/10.1177/0146167201275006

Cao, F., Su, L., Liu, T., & Gao, X. (2007). The relationship between impulsivity and Internet addiction in a sample of Chinese adolescents. European Psychiatry, 22(7), 466–471.
https://doi.org/10.1016/j.eurpsy.2007.05.004

Charoenwanit, S., & Sumneangsanor, T. (2014). Predictors of game addiction in children and adolescents. Thammasat Review, 17(1), 150–166. https://bit.ly/3qr6nxD

Chen, C., & Leung, L. (2016). Are you addicted to Candy Crush Saga? An exploratory study linking psychological factors to mobile social game addiction. Telematics and Informatics, 33(4), 1155–1166.
https://doi.org/10.1016/j.tele.2015.11.005

Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.

Choi, J. E., & Moon, S. B. (2010). A structural analysis on school-aged children’s Internet game addiction and its related variables [In Korean]. Korean Journal of Child Education and Care, 10(3), 149–168. https://bit.ly/3838xer

Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187–195.
https://doi.org/10.1016/S0747-5632(00)00041-8

Gorrese, A., & Ruggieri, R. (2013). Peer attachment and self-esteem: A meta-analytic review. Personality and Individual Differences, 55(5), 559–568.
https://doi.org/10.1016/j.paid.2013.04.025

Granic, I., Lobel, A., & Engels, R. C. M. E. (2014). The benefits of playing video games. American Psychologist, 69(1), 66–78.
https://doi.org/10.1037/a0034857

Jeong, E. J., & Kim, D. H. (2011). Social activities, self-efficacy, game attitudes, and game addiction. CyberPsychology, Behavior, & Social Networking, 14(4), 213–221.
https://doi.org/10.1089/cyber.2009.0289

Jia, J., Li, D., Li, X., Zhou, Y., Wang, Y., & Sun, W. (2017). Psychological security and deviant peer affiliation as mediators between teacher–student relationship and adolescent Internet addiction. Computers in Human Behavior, 73, 345–352.
https://doi.org/10.1016/j.chb.2017.03.063

Joyce, H. D., & Early, T. J. (2014). The impact of school connectedness and teacher support on depressive symptoms in adolescents: A multilevel analysis. Children and Youth Services Review, 39, 101–107.
https://doi.org/10.1016/j.childyouth.2014.02.005

Kim, E. J., Namkoong, K., Ku, T., & Kim, S. J. (2008). The relationship between online game addiction and aggression, self-control and narcissistic personality traits. European Psychiatry, 23(3), 212–218.
https://doi.org/10.1016/j.eurpsy.2007.10.010

Kim, K. H., & Chon, K. K. (1993). Development of a life stress and coping scale for junior high school students [In Korean]. Korean Journal of Clinical Psychology, 12(2), 197–217.

King, D. L., Chamberlain, S. R., Carragher, N., Billieux, J., Stein, D., Mueller, K., … Delfabbro, P. H. (2020). Screening and assessment tools for gaming disorder: A comprehensive systematic review. Clinical Psychology Review, 77, Article 101831.
https://doi.org/10.1016/j.cpr.2020.101831

King, D. L., & Delfabbro, P. H. (2014). The cognitive psychology of Internet gaming disorder. Clinical Psychology Review, 34(4), 298–308.
https://doi.org/10.1016/j.cpr.2014.03.006

Krossbakken, E., Pallesen, S., Mentzoni, R. A., King, D. L., Molde, H., Finserås, T. R., & Torsheim, T. (2018). A cross-lagged study of developmental trajectories of video game engagement, addiction, and mental health. Frontiers in Psychology, 9, Article 2239.
https://doi.org/10.3389/fpsyg.2018.02239

LaRose, R., Lin, C. A., & Eastin, M. S. (2003). Unregulated Internet usage: Addiction, habit, or deficient self-regulation? Media Psychology, 5(3), 225–253.
https://doi.org/10.1207/S1532785XMEP0503_01

Lee, C., Kim, H., & Hong, A. (2017). Ex-post evaluation of illegalizing juvenile online game after midnight: A case of shutdown policy in South Korea. Telematics and Informatics, 34(8), 1597–1606.
https://doi.org/10.1016/j.tele.2017.07.006

Lee, E. H., & Jeong, S. O. (2006). Ego identity as a mediator between parenting behaviors, peer relationships, and depression in adolescence: A structural equation analysis [In Korean]. Studies on Korean Youth, 17(2), 213–239. https://bit.ly/36Ej28H

Lee, M., & Larson, R. (2000). The Korean “examination hell”: Long hours of studying, distress, and depression. Journal of Youth and Adolescence, 29(2), 249–271.
https://doi.org/10.1023/A:1005160717081

Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and consequences of pathological gaming. Computers in Human Behavior, 27(1), 144–152.
https://doi.org/10.1016/j.chb.2010.07.015

Liu, Q.-X., Fang, X.-Y., Yan, N., Zhou, Z.-K., Yuan, X.-J., Lan, J., & Liu, C.-Y. (2015). Multi-family group therapy for adolescent Internet addiction: Exploring the underlying mechanisms. Addictive Behaviors, 42, 1–8.
https://doi.org/10.1016/j.addbeh.2014.10.021

Mei, S., Yau, Y. H. C., Chai, J., Guo, J., & Potenza, M. N. (2016). Problematic Internet use, well-being, self-esteem and self-control: Data from a high-school survey in China. Addictive Behaviors, 61, 74–79.
https://doi.org/10.1016/j.addbeh.2016.05.009

Meldrum, R. C., & Hay, C. (2012). Do peers matter in the development of self-control? Evidence from a longitudinal study of youth. Journal of Youth and Adolescence, 41(6), 691–703.
https://doi.org/10.1007/s10964-011-9692-0

Miklikowska, M., Thijs, J., & Hjerm, M. (2019). The impact of perceived teacher support on anti-immigrant attitudes from early to late adolescence. Journal of Youth and Adolescence, 48(6), 1175–1189.
https://doi.org/10.1007/s10964-019-00990-8

Miller, C. H., Burgoon, M., Grandpre, J. R., & Alvaro, E. M. (2006). Identifying principal risk factors for the initiation of adolescent smoking behaviors: The significance of psychological reactance. Health Communication, 19(3), 241–252.
https://doi.org/10.1207/s15327027hc1903_6

National Youth Policy Institute. (2013). Korean Children and Youth Panel Survey [In Korean]. https://bit.ly/3nhom7Y

Orford, J. (2001). Addiction as excessive appetite. Addiction, 96(1), 15–31.
https://doi.org/10.1046/j.1360-0443.2001.961152.x

Özdemir, Y., Kuzucu, Y., & Ak, Ş. (2014). Depression, loneliness and Internet addiction: How important is low self-control? Computers in Human Behavior, 34, 284–290.
https://doi.org/10.1016/j.chb.2014.02.009

Rosenberg, M. (1965). Rosenberg Self-Esteem Scale (RSES) [Database record]. APA PsycTests.
https://doi.org/10.1037/t01038-000

Seo, J. Y., & Kim, M. Y. (2006). Stress, physical symptoms, and coping styles of high school students [In Korean]. Journal of Korean Academy of Child Health Nursing, 12(4), 470–477. https://bit.ly/37wx9fz

Servidio, R., Gentile, A., & Boca, S. (2018). The mediational role of coping strategies in the relationship between self-esteem and risk of Internet addiction. Europe’s Journal of Psychology, 14(1), 176–187.
https://doi.org/10.5964/ejop.v14i1.1449

Soh, P. C.-H., Chew, K. W., Koay, K. Y., & Ang, P. H. (2018). Parents vs peers’ influence on teenagers’ Internet addiction and risky online activities. Telematics and Informatics, 35(1), 225–236.
https://doi.org/10.1016/j.tele.2017.11.003

Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324.
https://doi.org/10.1111/j.0022-3506.2004.00263.x

Tice, D. M., Bratslavsky, E., & Baumeister, R. F. (2001). Emotional distress regulation takes precedence over impulse control: If you feel bad, do it! Journal of Personality and Social Psychology, 80(1), 53–67.
https://doi.org/10.1037/0022-3514.80.1.53

van Rooij, A. J., Ferguson, C. J., Carras, M. C., Kardefelt-Winther, D., Shi, J., Aarseth, E., … Przybylski, A. K. (2018). A weak scientific basis for gaming disorder: Let us err on the side of caution. Journal of Behavioral Addictions, 7(1), 1–9.
https://doi.org/10.1556/2006.7.2018.19

World Health Organization. (2018). International classification of diseases: The global standard for diagnostic health information (11th ed.). Author.

Yao, M. Z., He, J., Ko, D. M., & Pang, K. (2014). The influence of personality, parental behaviors, and self-esteem on Internet addiction: A study of Chinese college students. Cyberpsychology, Behavior, and Social Networking, 17(2), 104–110.
https://doi.org/10.1089/cyber.2012.0710

Younes, F., Halawi, G., Jabbour, H., El Osta, N., Karam, L., Hajj, A., & Khabbaz, L. R. (2016). Internet addiction and relationships with insomnia, anxiety, depression, stress and self-esteem in university students: A cross-sectional designed study. PLoS ONE, 11(9), e0161126.
https://doi.org/10.1371/journal.pone.0161126

Young, K. S. (1998). Caught in the net: How to recognize the signs of Internet addiction—and a winning strategy for recovery. John Wiley & Sons.

This work was supported by Konkuk University in 2017.
Data used in this study are available with permission from the Korea Creative Content Agency (https

//www.kocca.kr/gameguide/contents.do?menuNo=203709).

Eui Jun Jeong, Department of Digital Culture and Contents, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea. Email: [email protected]