A group-based modeling approach to estimating longitudinal trajectories of Korean adolescents’ on-line game time
Introduction
According to the latest statistics from Korea Communications Commission (KCC) and the National Internet Development Agency of Korea (NIDA), Internet use in Korea has been steadily increasing on a yearly basis throughout the last decade. One of the main reasons as to why young people use the Internet is to play online games (NISA, 2007). The Korea Creative Content Agency (KOCCA) conducted a survey on online game addiction among adolescents in South Korea (2007. 12–2008. 2), and found that 12.1% of young people in their adolescence play online games for more than three hours per day. Among these players, 29.1% reported that they feel anxious and uneasy if they cannot play online games or if they suddenly reduce their game play time. 53.5% reported that they have attempted to stop playing, but failed to do so. This suggests that a considerable number of young people feel a strong need to play online games. For some adolescents, participating in online games extends beyond merely engaging in a leisure activity; it becomes an addiction.
Online game addiction is commonly classified under the category of Internet addiction (Young, 1999). Addiction is ordinarily diagnosed when social or professional functioning is damaged in concert with physiological dependence, tolerance and/or withdrawal symptoms due to the abuse of substances such as alcohol, cocaine or marijuana or due to compulsive behaviors. Because Internet addiction causes similar results, it has been classified as a subcategory of addiction (Griffiths & Hunt, 1998). Researchers found that the more adolescents spend time playing games, the more they show low self-control, poor grades (Kim & Cho, 2002), low emotional intelligence, poor relationship with teachers and peers, poor school adjustment (Kim, 2010) and aggressive attitude (Lee, 2011). Online game addiction leads to obsessive playing, which may engender impaired daily life, difficulty in separating fantasy from reality and withdrawal symptoms.
Adolescence is an important period of human development (Baker, Yardley, & McCaul, 2001). Thus, a great deal of the time spent addicted to online games during this critical formative developmental stage can hinder young people’s normal development (Young, 1999). It may disrupt one’s physical and mental growth and negatively influence the formation of one’s self-identity and academic performance. Due to the consequence that addiction can be a serious problem with far-reaching consequences for adolescents, examining the related factors is of great importance. A meta-analysis of related studies reported that some personal characteristics were found to possess a significant relation to online game addiction (Kang & Son, 2007). Thus, in order to improve our understanding of game addiction in adolescents, the current study aims to investigate how personal characteristics (e.g., sex, self-control, self-esteem, aggressiveness, emotion regulation, academic stress, academic motivation and social skills) influence the change pattern in Korean adolescents’ online game addiction over time.
Section snippets
Overview of the literature
This paper discusses eight personal characteristics that have been identified as having connections with game addiction.
Research questions
Online game addiction is a behavioral pattern that develops over a long period of time. However, although many studies have examined the relation between personal characteristics and online game addiction, most are based on cross-sectional data and thus, cannot adequately explain how the characteristics affect the change in the addiction level over time. Thus, our study examined the following research questions: (1) Are there distinct patterns of latent classes according to online game time?
Participants
The current study used the dataset of the Korean Youth Panel Study (KYPS). KYPS is a multi-wave, longitudinal study that focuses on adolescents’ school experiences from the period of mid-junior high school to early high school. Students’ self-report questionnaires were used in this study. The current study’s sample included 1725 males and 1724 females (mean age: 14.78 years, SD: .41 years) from four waves of KYPS.
Measures
For the outcome measure, the same item (i.e., “How often do you use the computer for
The number and pattern of the latent classes
Figure 1 shows the AIC and BIC values of the model fit between the class models of class 2 and 5. Model selection is analogous to the scree plot for the principal component analysis (Petras & Masyn, 2010). It is seen that AIC and BIC values are improved by using more than one class and that there is a sharp drop between 4 and 5 class models before leveling off. It is important when detecting the number of classes in order to distinguish the prominent and substantively meaningful number of
Discussion and limitation
In this study, we classified adolescent online game players based on the change in the amount of play time. Further, we also investigated each group’s (i.e., latent class) relation to personal characteristics such as sex, self-control, self-esteem, aggressiveness, emotion regulation, academic stress, academic motivation and social skills. In the process of deriving the latent classes, the four-class model was determined to be the most suitable representation of the latent classes. The four
Conclusion
The current study did not only measure the level of online game addiction at a given moment, but also tracked the changes within the level over time. The study also looked into the personal characteristics that influence the participants’ addictive behaviors across time periods. The results provide important implications for practitioners and researchers. First, practitioners can utilize the information to develop and provide services for groups with different levels of online game addiction.
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