Prevalence and predictors of smartphone addiction proneness among Korean adolescents
Introduction
Recently, with the increase in the use of and popularity of smartphones, adolescent smartphone addiction proneness has become a serious social problem (Kim et al., 2014, Kwon et al., 2013). Smartphones have been integrated into Asian cultures, and smartphone addiction proneness is increasing rapidly among younger people (BBC, 2015). Many adolescents experience conflicts with parents because of their uncontrolled use of smartphones at home, and with teachers at school owing to unregulated smartphone use during class (Lee & Kim, 2013). An increasing number of adolescents suffer from inattention to school work, interruption of social interaction, or sleep disturbance, which may be attributable to smartphone overuse (Lemola et al., 2015, Wang et al., 2013). According to a national survey of the National Information Society Agency or NISA (2015), a governmental organization established to nurture information culture in Korea, 32.6% of teenagers suffered from disturbance, and 30.1% experienced deterioration of visual acuity because of smartphone overuse. Adolescents spend an excessive amount of time on their smartphones chatting (e.g., Kakaotalk), listening to music, using SNS (e.g., Facebook), playing games, and exploiting Webtoon services (Lee & Kim, 2013). As of 2016, about 90% of Korean middle and high school students own a smartphone; ownership had also increased rapidly in recent years (Korea Information Society Development Institute, 2016). These findings indicate that smartphone use is common and routinized among Korean adolescents.
Despite the growing public concern over adolescents' vulnerability to smartphone addiction proneness, there is a lack of empirical research examining the factors that influence smartphone addiction among adolescents. Who are more vulnerable to smartphone addiction proneness? Are contextual factors, such as those related to family, peers, and school, which have been implicated as predictors of problematic media use, also significant with respect to smartphone addiction? What are the motives of adolescents who are addicted to smartphones? This study aims to fill the existing knowledge gap by examining the influences of demographic, contextual, and motivational factors on adolescent smartphone addiction proneness.
Public concern over excessive use of digital media by adolescents has prompted several academic studies investigating the symptoms of addictive behaviors, causes, and consequences in various countries (e.g., Choo et al., 2015, Jiang, 2014, Kuss et al., 2013, ŞaŞmaz et al., 2013, Wang et al., 2013, Wang et al., 2014). Among the diverse kinds of technological addictions, smartphone addiction proneness is a relatively new concept that is receiving increasing amounts of attention, following the interest in internet addiction. An often-cited definition of internet addiction is “an impulse-control disorder that does not involve an intoxicant” (Young, 1998, p. 237). Many scholars prefer the terms “compulsive internet use” (Greenfield, 1999), “problematic internet use” (Caplan, 2002, Caplan, 2010), or “unregulated internet use” (Larose, Lin, & Eastin, 2003). In accordance with these definitions of internet addiction, smartphone addiction is defined loosely as overuse of smartphones that leads to adverse consequences or disturbance of daily life (Demirci et al., 2014, Kwon et al., 2013).
Overall, Korean scholars developed a scale measuring smartphone addiction proneness. For example, the 33-item Smartphone Addiction Scale (SAS) by Kwon et al. (2013) covers six factors, namely, daily life disturbance, positive anticipation, withdrawal, cyberspace-oriented relationship, overuse, and tolerance (p. 6). Another example is the Korean Smartphone Addiction Proneness Scale, or SAPS (Kim et al., 2014), with its reliability and validity verified based on a national survey of young people in Korea. Its four sub-domains include disturbance of adaptive functions, virtual life orientation, withdrawal, and tolerance (Kim et al., 2014). Disturbance of adaptive functions indicates the negative consequences, such as neglect of schoolwork and falling school grades, caused by smartphone overuse. Virtual life orientation points to the extent of users' preoccupation with the virtual world. Withdrawal refers to symptoms that emerge when users are unable to use a smartphone. Tolerance indicates an increasing amount of time spent on smartphone to satisfy users' satisfaction.
In 2015, NISA conducted a national survey on smartphone addiction, using the SAPS (National Information Society Agency, 2015). According to the survey results, 31.6% and 13.5% of adolescents and adults, respectively, were addicted to smartphones. With respect to internet addiction, the rates were 13.1% and 5.8% among adolescents and adults, respectively. According to this survey, teenagers spent about five hours a day on their smartphones, and most of them used messenger service, SNS, and game on the device (National Information Society Agency, 2015). The results indicated that adolescents are more addicted to smartphones than the internet, and smartphone addiction is more serious among youths than adults.
Thus, this study assesses the prevalence of adolescent smartphone addiction proneness by using the SAPS; categorizes adolescents into non-addicts, those at potential risk for addiction, and high-risk individuals; and examines the differences among the group by gender, grade, socioeconomic status, academic performance, and school rules regarding smartphone usage. Next, it will analyze the predictors of smartphone addiction proneness.
Gender differences are apparent in the use of new technology. In general, men are more likely to show positive and open attitudes toward new technology compared with women (Ray, Sormunen, & Harris, 1999). Many previous studies have shown that male students are much more addicted to the internet and online games than females (Choo et al., 2015, Dhir et al., 2015, Huanhuan and Su, 2013, Leung and Lee, 2012, Wang et al., 2013, Wang et al., 2014, Yoon et al., 2014). However, findings of recent studies on mobile phone addiction are contradictory, indicating that females are more likely to be involved excessively with their mobile phones to the extent that they develop dependency on or addiction to mobile phones and become vulnerable to abuse of mobile phones (Chiu et al., 2013, Koo, 2012, Walsh et al., 2011). This can be attributed to female adolescents being more involved in communication with others via their mobile phones and utilizing diverse communication services, such as SNS, chatting, and texting (Chiu et al., 2013). This dependence on communication via a mobile phone exhibits females' stronger relationship with smartphone addiction than gaming (Jeong, Kim, Yum, & Hwang, 2016). Thus, this study hypothesizes that H1 Female students are more likely to be addicted to smartphones than their male counterparts.
According to social control theory, an individual's bond to society plays an important role in deterring a delinquent activity (Hirschi, 1969). Adolescents' attachment to parents, friends, and teachers is critical in preventing them from committing a delinquent activity. This theory has been applied to addiction issues. For example, previous research has indicated that parental attachment (Kim & Kim, 2015), parent–child closeness (Choo et al., 2015), and a warm family environment (Liau et al., 2015) reduce the risk of addiction to video games or the internet. Better parent–adolescent relationships also enhanced connections to school, thereby reducing internet gaming addiction (Zhu, Zhang, Yu, & Bao, 2015). Social support from family or friends was also related negatively to internet addiction (Gunuc & Dogan, 2013). Although adolescents, who have many friends exhibiting deviant behaviors, are more likely to be addicted to internet gaming (Zhu et al., 2015), overall satisfaction with friendships is related negatively to smartphone addiction (Bae, 2015). Thus, this study hypothesizes that H2a Attachment to parents is related negatively to smartphone addiction. H2b Attachment to friends is related negatively to smartphone addiction. H2c Attachment to teachers is related negatively to smartphone addiction.
Adjustment to school is an important factor related to addiction (Lee, Lee, & Shin, 2009). According to a study by Ju and Cho (2015), maladjustment to school plays an important role in increasing adolescents' smartphone addiction. In their study, addicts had less satisfying relationships with peers compared with non-addicts. Adolescents consider peer relations to be important. Consequently, they try to maintain an intimate relationship with their friends. Otherwise, they are likely to feel lonely and alienated, making them more addicted to their mobile phones (Kim & Hwang, 2012). Moreover, participation in a wide breadth of extracurricular activities, such as sports, was associated negatively with internet addiction (Wang et al., 2013). According to Ryou's (2013) study, adolescents who participated in club activities, were less likely to become addicted to the internet. Life satisfaction was also associated negatively with gaming addiction (Lemmens, Valkenburg, & Peter, 2009). Addicted adolescents reported lower satisfaction with life compared with non-addicted ones (Wang et al., 2013). Accordingly, adolescents who are not satisfied with school life are likely to depend on smartphones to obtain the satisfaction that they do not derive from relationships or activities in the physical world. Thus, this study hypothesizes that H3 Satisfaction with school life is related negatively to smartphone addiction.
According to the uses and gratifications theory, motivations for media use influence the patterns of usage and result in need gratifications and other intended and unintended consequences (Katz, Blumler, & Gurevitch, 1973). The uses and gratification research has classified the motivations for media use in terms of surveillance (i.e., to learn about events and affairs that might affect one), social utility (i.e., to obtain information for conversations and utilize it for companionship), personal identity (i.e., to reinforce one's values, beliefs, and attitudes), and diversion (i.e., an escape from routines or for emotional release) (Ruggiero, 2000). The motives for media use have been examined as factors that account for duration of media usage, type of content consumption, and intended or unintended outcomes. Media addiction is associated with unregulated usage and unintended outcomes, which are affected by certain motives for or gratifications derived from media.
Previous research has identified various motives related to addictive media use. For example, Song, Larose, Eastin, and Lin (2004) found that gratification obtained from internet use, including being part of a virtual community, diversion, and maintaining relationships, was related to internet addiction among college students. Bian and Leung (2014) identified four types of smartphone use motives, namely, information seeking, utility, fun seeking, and sociability. Their findings indicated that the more college students used smartphones to find information, for practical purposes and fun, the higher the likelihood that they were addicted. Meanwhile, Kim and Shin (2015) identified three types of smartphone use motives, namely, constant use of information, convenience of use, and ostentation and fashion. In their study, using a smartphone only to display ostentation as a fashion accessory was related significantly to smartphone addiction in middle school students. Although a few previous studies have examined the relationship between motives for smartphone use and addictive use, no consistent pattern has been found. Most of all, there is a lack of research that examines adolescents' motives for smartphone use, considering their unique developmental needs, such as peer acceptance and identity formation. Consequently, this study aims to identify the unique motives for smartphone use among adolescents and examine how these motives based on their developmental needs are associated with smartphone addiction as an unintended outcome. RQ1 How are adolescents' motives for smartphone use related to addictive behaviors?
Section snippets
Participants
Participants in the study were 3000 adolescents, with 1580 male (52.7%) and 1420 female (47.3%) students. The sample included 484 students (16.1%) in grade seven, 494 (16.5%) in grade eight, 519 (17.3%) in grade nine, 503 (16.8%) in grade 10, 503 (16.8%) in grade 11, and 494 (16.5%) in grade 12. The percentages used in this study follows closely the population distribution in 2012 National Statistics: 52.5% (male), 47.5% (female); 15.8% (7th grade), 16.3% (8th grade), 17% (9th grade), 17% (10th
Prevalence of smartphone addiction proneness
Among all respondents, 7.6% were classified as high-risk users and 27.6%, as potentially at-risk users for smartphone addiction (see Table 3). In total, 35.2% of students were addicted to smartphones.
Differences in the proportion of smartphone addiction by gender, school grade, and academic performance were statistically significant. Results regarding gender difference indicated that 9.5% of female and 5.9% of male students were classified as high-risk users, whereas 33.1% of female and 22.7%
Discussion
The purpose of this study was to identify the prevalence of and predictors related to smartphone addiction proneness. The results indicated that the proportions of high-risk (7.7%) and potentially at risk (27.9%) users for smartphone addiction were quite high; that is, 35.6% of students were classified as addicts. This figure is similar to the 31.6% indicated in the 2015 NISA survey, which showed that many students in Korea were addicted to smartphone compared with those in other countries. For
Conclusion
The findings of this study advance an understanding of the predictors related to addictive use of smartphones by adolescents. Identifying the factors related to addictive use is important, as it informs on who are more likely to be vulnerable to problematic smartphone use and why they are more likely to become compulsive smartphone users. This study showed that females,children with low academic performance, children who have a poor relationship with their parents, and those who are less
Acknowledgements
This study was based on data from a 2013 research project, titled “Diffusion of Smartphone and Youth Protection Policy,” by the National Youth Policy Institute in Korea.
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