CHAPTER II Review of Related Literature This chapter presents the relevant literature and studies that the researcher considered in strengthening the importance of the present study. It also presents the synthesis or the art to fully understand the research for better comprehension of the study. Many people casually consider themselves as “being addicted” when they enjoy something they do or when they feel they do something quite frequently. Yet, in clinical terms, addictions manifest themselves as issues with tolerance, withdrawal, dependence, and as social problems (Holden, 2001; Kwon, Lee, et al., 2013). Addictions can be divided into two categories: addictions caused by psychoactive substances (e.g., abuse of alcohol or drugs) and those which are behavioural (e.g., videogaming, shopping, and Internet addiction; Kim & Kim, 2002) - even though, in the past, the term ‘addiction’ has been primarily associated with substance abuse, the impact of technology on the everyday lives of most people has led to the association of addiction with behavioral concepts (Kim et al., 2006; Kim et al., 2016; Kwon, Lee, et al., 2013). Despite this development in conceptualizing addiction, there are no officially recognized diagnostic criteria for smartphone addiction (Noyan, Darçin, Nurmedov, Yılmaz, & Dilbaz, 2014). Accordingly, it has been debated whether or not smartphone addiction should be listed as a mental disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM5; American Psychiatric Association [APA], 2013). Proponents for its inclusion base their arguments on the idea that uncontrollable and too frequent smartphone use may lead to social, behavioural, and emotional problems (Choliz, 2010). Conversely, as with Internet addiction, it is unclear if smartphone addiction indicates an underlying disorder or whether it is a discrete disease entity. This might also raise the question of causality in the context of comorbidity (Pies, 2009). As with Internet addiction, smartphone addiction might be a secondary manifestation of other psychological disorders, such as depression and anxiety. In addition, Billieux, Maurage, Lopez-Fernandez, Kuss, and Griffiths (2015) criticize the symptom-based addiction model because it could lead to the oversimplification of an individual’s psychological processes, which might be accompanied by non-relevant standardized treatments. Altogether, the latest version of the DSM does not include smartphone addiction as a separate disorder (APA, 2013). This fact, of course, does not necessarily mean that no such behavioral disorder exists. It simply implies that, currently, the construct of this behavioral addiction remains unclear. Naturally, it will take time to understand the full impact of smartphones. Firstly, because the technology itself is relatively novel and, secondly, because the impact needs to be carefully observed in the context of our contemporary, increasingly globalized world. In fact, Tossel, Kortum, Shepard, Rahmati, and Zhong (2015) have emphasized that the term smartphone addiction might be somewhat misleading, as it is not a currently diagnosable disorder. Furthermore, it has been claimed that there is too little evidence to suggest that smartphone use (or overuse) has similar impacts on the neurological and psychological mechanisms as the impacts observed with other behavioral and substance-related disorders (Billieux et al., 2015). Therefore, rather than use the term smartphone addiction, the use of other terms such as smartphone overuse, problematic smartphone use, or compulsive smartphone use has been advised (Ching et al., 2015; Lepp et al., 2013). Despite not being listed as a disorder in the DSM-5, some work has been done to study the association of these digital technologies with everyday life. The research on problematic aspects of smartphone use was preceded by studies on their technological predecessors, mobile phones. Many self-report scales were created in order to study problematic mobile phone use (e.g., Billieux, Van der Linden, & Rochat, 2008; Rutland, Sheets, & Young, 2007; Toda, Monden, Kubo, & Morimoto, 2004; see Billieux, 2012, for a review). Recently, however, research has also been conducted on smartphone-specific measurement tools; the research is at best limited. The first and, according to scientific citations, most influential instrument to measure smartphone addiction was devised by Kwon, Lee, et al. (2013). The authors argued that because using the Internet in general and using the Internet on smartphones is, in essence, highly similar, the symptoms of smartphone addiction ought to be similar as well; however, this may not be the case. Using the Internet on a smartphone is different from using the Internet more generally. This is true for several reasons: pocket-sized smartphones have a small screen, various applications, increased availability of the Internet due to their mobility, and generally, smartphone usage is flexible in time and space (Nielsen & Fjuk, 2010). As such, Kwon, Lee, et al. (2013) devised the Smartphone Addiction Scale (SAS), based on the Internet Addiction Test (IAT; Young, 1998). As part of the process, items for Internet usage were adjusted accordinToday's adolescents are highly receptive of new forms of media such as smartphones [4] as they are the first generation to have grown up surrounded by various forms of high-tech media [5]. This could mean that youths are more susceptible to the adverse effects of smart media than older age groups. In South Korea, youths addicted to smartphone have reached 11.4% of the population, with the top 2.2% facing difficulty living out their everyday lives due to their addiction [6]. Before the spread of smartphones, cell phones took up a huge part of adolescents' lives to the point where some reported experiencing high levels of anxiety when their phone is not always on [4]. Cellular phone addiction and age seem to be inversely proportional, with younger people using their phones more frequently [8], and two times more likely to admit to being a “cellular phone addict” than adults [9]. For adolescents, phone-based communication is an important way to maintain their social relationships [7]. As smartphone addiction is becoming a major issue amongst youths, developing a scale that can estimate the levels and conditions of smartphone addiction among adolescents seems urgent in order to protect them from the addiction's adverse effects.Because the distribution of smartphones is a relatively recent phenomenon, studies that have defined the unique symptoms of smartphone addiction are rare. The closest concept to smartphone addiction may be cellular phone addiction, which is considered to be a type of behavioral addiction characterized by problems with impulse control. Reported symptoms of cellular phone addiction include withdrawal, tolerance, disturbance of adaptive functions, compulsion, and pathological immersion [12] and abstinence, lack of control and problems derived from the use, and tolerance and interference with other activities [13]. Existing cellular phone addiction scales [47] [48] [49] have been developed based on Young [10]’s Internet Addiction Test (IAT) and Goldberg [11]’s diagnostic criteria for internet addiction. However, smartphones are different to cellular phones in four major ways. First, smartphone users are more dynamically involved with the device than regular cell phone users. Smartphone users actively engage with the device itself and the contents (applications) simultaneously, and may play a role of producer by creating personalized applications. Since applications allow smartphone users to give immediate, mutual feedback, smartphone users tend to be active, participatory, relational, competent, and productive [15]. Consequently, smartphone usage has been shown to be directly proportional to application usage [14]. Second, smartphones place a greater importance on the sensory features that stimulate users' expressive side [16]. Smartphone's distinctive user interface system, which includes touch screen operation, keyboard arrangements, icons, sensible design, and other components, enables its user to reveal his or her individuality [17]. The importance of the expressive aspect of smartphone applications can also be seen in the fact that users prefer applications that allow multiple users to have fun together and to be socially expressive over applications that can only be enjoyed alone [18]. Third, smartphones provide a convergence of services such as the camera, MP3, GPS, web browsing, calling, e-mail, gaming, and social networking services (SNS) [19] [20] on one portable device. Also called the “handheld Internet,” smartphones' portability allows for real-time and personalized services anywhere which could not be fulfilled on a typical desktop computer. Moreover, smartphone's “Push Service” notifies the users with relevant updates, such as newest emails or Facebook replies, even before the user asks for them [21]. Such personalized services provided by smartphones can be helpful, but may also induce people to overuse their smartphones [22] [23]. Finally, people of different age groups show varying smartphone usage patterns. Teens mainly use their smartphones for the camera, MP3, and other entertainment functions; people in their 20's mainly use SNS; and the people in their 30's and 40's typically manage their schedules, contacts list, e-mail, and other business related functions [24] [25]. Despite smartphones' distinctive characteristics as mentioned above, many of the existing smartphone addiction scales were identical to the cellular phone addiction scale, with the word “cellular phone” simply replaced with “smartphone”. One of the most recent, Casey [26] 's smartphone addiction scale had also extracted items from scales that measure other types of media addiction such as the Mobile Phone Problem Use Scale [27], Internet Addiction Test [10], and Television Addiction Scale [28]. Besides, since cellular phone addiction was also seen as a type of behavioral addiction due to impulse control problems, it was usually comprised with elements from internet addiction. Therefore, the current study developed the Korean Smartphone Addiction Proneness Scale (SAPS) for Youth by adding items that reflect unique characteristics of smartphones to the Internet Addiction Proneness Scale (IAPS) for Youth [29]. The IAPS is a 20-item scale that has been used to check the level of internet addiction among youth in South Korea since 2007. The SAPS developed through current study will be a useful tool for examining the phenomenon of smartphone overuse among youths, and will ultimately contribute to preventing smartphone addiction. Smartphone addiction is an emerging public health issue. The epidemic of smartphone addiction has rapidly spread from young adults and adolescents to children in many countries. Taiwan news reported a 10-year-old boy died after his parent took away his smartphone. However, Taiwan has officially recognized e-sports as an official competitive sport, while more politicians have endorsed e-sports markets. Experts and parents worry that the negative impact of these events might cause more children and adolescents to develop Internet and smartphone addictions. Studies have developed scales to measure smartphone addiction, but most of these studies are based on young adults and adolescents. Experts have criticized the different scales and cut-point values that may cause variations in the definition and features of smartphone addiction. Little research has been focused on assessing transitions in smartphone addiction among children and examining the effects of gender, use patterns and depression on smartphone addiction transitions. Latent Class Analysis (LCA) has proven to be highly useful in recent years for modeling complex behavior, while Latent Transition Analysis (LTA), a longitudinal extension of LCA, could be used to model transition patterns and developments in discrete latent variables [28]. This study used LTA to identify the latent statuses of SAP and transitions in SAP from 5th grade to 6th grade. Effects of gender and smartphone use patterns were also explored. Glanze, Anderson, and Anderson (1998, p. 321) defined addiction as “compulsive, uncontrollable dependence on a substance, habit, or practice to such a degree that cessation causes a severe emotional, mental, or physiological reaction.” Researcher argued differently on applications of addiction concept. Some researcher emphasized on the application of addiction concept in chemical substances, such as alcohol or drug (BRATTER; FORREST, 1985; WALKER, 1989; RACHLIN, 1990). On the other hand, some researchers used this concept in problematic behaviors, such as internet addiction (YOUNG, 1998; KANDELL, 1998; GRIFFITHS, 1998; GOLDBERG, 1995), computer game playing (GRIFFITHS; HUNT, 1995), sex (CARNES, 1983), and pathological gambling (GRIFFITHS, 1990). Technology addiction is becoming prevalent everywhere with various forms such as Internet addiction, mobile addiction and smartphone addiction. Young (1998) reported internet addiction having online dependency symptoms such as withdrawal, impatience, loss of control, disorder in academic, job, and social performance. Based on Internet Related Addictive Behavior Inventory, Brenner (1997) reported some daily-life disturbances such as less sleeping time, less time management, missing meal and other symptoms. Accordingly, Ko et al., (2006) identified several factors of internet addiction, such as impatience, withdrawal, compulsive use, and interpersonal problem. In recent years, the extant research has been shifted from internet addition to mobile phone addiction. Researcher of mobile phone addiction uses internet addiction measures in designing mobile phone addiction instrument. Smartphone addiction and mobile phone addiction are not same. Apart from mobile phone addiction tool, smartphone addiction demands some salient criteria based on its numerous distinct features (KWON, et al., 2013). Although, previous studies have mixed-up these two distinct tools and used interchangeably (HONG, et al., 2012). Addiction in smartphone deserves distinct tool for on its salient features, such as multitasking, installing applications, internet usability. People also personalize their smartphones with various apps. In a study, Hong et al. (2012) have developed smartphone addiction scale using mobile phone related addictive items ignoring distinct features of smartphone. Although some features of mobile phone and smartphone are same, researchers are emphasizing on the separate tool for smartphone addiction. Some papers discuss about smartphone addiction on academic arena such as nursing student (CHO; LEE, 2015; JEONG; LEE, 2015), others emphasize specific group of generation such as youths (KIM; LEE; LEE; NAM; CHUNG, 2014) ignoring the addictive behavior of university students (with exception of SAMAHA; HAWI, 2016; HAWI; SAMAHA, 2016). There are few studies on smartphone addiction. In a study on smartphone addiction, Cho and Kim (2014) identified gender, average daily using time in a week, average daily using time in weekend, wrist pain in using smartphone, accident in using smartphone, sociality, impulsiveness, and Social Networking Sites (SNS) addiction as significant predictors. They have found 43.3% explained variance of these factors in smartphone addiction. Jeong and Lee (2015) studied smartphone addiction on nursing students in Korea and revealed several influencing factors of smartphone addiction that includes reading quality, the number of friends, the number of groups involved, academic achievement, average daily hours of smartphone use, and personal distress. They reported 17.4% explanatory power of these variables. Jeong and Lee (2015) like other study (e.g., KIM; KIM; JEE, 2015) in Korea used Smartphone Addiction Proneness Scale (SAPS) that is developed by the National Information Society Agency (SHIN; KIM; JUNG, 2011). The SAPS contains 15 items consisting of four subdomains, such as impatience, withdrawal, disturbance of adaptive functions, and virtual life orientation.
