Internet addiction in adolescents: Prevalence and risk factors
Introduction
With the availability and mobility of new media, Internet addiction has emerged as a potential problem in young people. Based on a growing research base (Young, 2010), the American Psychiatric Association aims to include Internet Use Disorder in the appendix of the upcoming fifth edition of the Diagnostic and Statistical Manual for Mental Disorders (2012) for the first time, acknowledging the problems arising from this type of addictive disorder. Adolescents appear to be a population at risk for developing Internet addiction (Leung, 2007) due to variability in developing their cognitive control (Casey, Tottenham, Liston, & Durston, 2005) and boundary setting skills (Liu & Potenza, 2007).
With regards to prevalence of Internet addiction in adolescents, estimates vary widely across countries. Using Young’s Internet Addiction Test (1999), 1.5% of Greek (Kormas, Critselis, Janikian, Kafetzis, & Tsitsika, 2011) and 1.6% of Finnish adolescents (Kaltiala-Heino, Lintonen, & Rimpela, 2004) were found to be addicted to using the Internet. Using a modified version of the Minnesota Impulsive Disorders Inventory, 4% of US high school were identified as addicted to using the Internet (Liu, Desai, Krishnan-Sarin, Cavallo, & Potenza, 2011). Higher prevalence rates have been reported in South East Asian countries (e.g., Taiwan, Singapore, South Korea and China). For example, using Young’s Internet Addiction Test (1998a) 8% of adolescents in China (Cao, Sun, Wan, Hao, & Tao, 2011) and 10.7% of adolescents in South Korea (Park, Kim, & Cho, 2008) were found to be addicted to using the Internet. In comparison and unsurprisingly, prevalence estimates in youth psychiatric settings are reported to be considerably higher. For instance, the prevalence of Internet addiction among minors using the Assessment of Internet and Computer Game Addiction Scale (Wölfling, Müller, & Beutel, 2010) was found to be 11.3% in Germany (Müller, Ammerschläger, Freisleder, Beutel, & Wölfling, 2012), and assessed via the Internet Addiction Test (Young, 1998b), 11.6% of adolescent outpatients in Latin America were classed as being Internet addicts (Liberatore, Rosario, Colon-De Marti, & Martinez, 2011). A detailed outline of the reported studies can be found in Table 1.
Overall, in the reported studies to date, a variety of measurement instruments have been used that do not allow for a clear-cut and comparable estimation of Internet addiction prevalence in both adolescent and adult populations. Therefore, there is a need for utilising actual clinical criteria in order to demarcate potentially pathological (i.e., addictive) behaviours from high-engagement behaviours that appear to be linked to a number of personality traits in addicted Internet users (Charlton & Danforth, 2010). In this study, clinical criteria for Internet addiction will be adopted, which will provide an indication of potential Internet addiction assessed via self-report (Meerkerk, Van Den Eijnden, Vermulst, & Garretsen, 2009). The criteria are based on the official diagnoses of substance dependence and pathological gambling (American Psychiatric Association, 2000) and are planned to be integrated in the proposed addition to the updated DSM, Internet Use Disorder (American Psychiatric Association., 2012). Accordingly, Internet addiction as adopted in this paper does not refer to a clinical diagnosis, but to a potentially pathological behavioural pattern. It is denoted by the presence of the following symptoms: (i) a loss of control over the behaviour, (ii) conflict (internal and interpersonal), (iii) preoccupation with the Internet, (iv) using the Internet to modify mood, and (v) withdrawal symptoms (Meerkerk et al., 2009).
From the perspective of the engagement in specific online activities, rather than focusing on Internet addiction per sé, researchers have now identified a number of activities that can be engaged in excessively online that may lead to symptoms similar to substance-related addictions (Yellowlees & Marks, 2007). Among these, excessive online gaming (Kuss & Griffiths, 2012a), excessive online gambling (Griffiths & Parke, 2010), and the use of social media (van den Eijnden, Meerkerk, Vermulst, Spijkerman, & Engels, 2008), such as online social networks (SNSs) (Kuss & Griffiths, 2011) appear to stand out. Their increasing diversity and usage growth among young populations (Entertainment Software Association, 2012, Lenhart et al., 2012) is mirrored by the rising number of treatment studies (King et al., 2011, Liu et al., 2012).
Research and clinical practice suggest that the concept of Internet addiction is not to be taken lightly as a number of negative consequences of excessive Internet use in adolescents have been identified in the literature. For instance, a recent review of the neuroscientific evidence (Kuss and Griffiths, 2012c) indicates that Internet addiction in adolescence can have a negative impact on identity formation (Kim et al., 2012) and change the structure of the developing brain (Lin et al., 2012, Yuan et al., 2011). In addition to this, it may negatively affect cognitive functioning (Park et al., 2011), lead to poor academic performance and engagement in risky activities (Tsitsika et al., 2011), poor dietary habits (Kim et al., 2010), low quality of interpersonal relations (Milani, Osualdella, & Di Blasio, 2009), and self-injurious behaviour (Lam, Peng, Mai, & Jing, 2009) in adolescents. From the reported negative consequences, it appears that Internet addiction can have a variety of detrimental psychosocial and physical outcomes for adolescents that may require professional intervention (King, Delfabbro, & Griffiths, 2012).
In addition to this, Internet addiction appears to be comorbid with clinical disorders and premorbid symptoms. In adolescents, Internet addiction has been reported to be comorbid with depression and insomnia (Cheung & Wong, 2011), suicidal ideation (Fu, Chan, Wong, & Yip, 2010), attention-deficit hyperactivity disorder, social phobia, and hostility (Ko, Yen, Chen, Yeh, & Yen, 2009), schizophrenia, obsessive–compulsive disorder (Ha et al., 2006), aggression (Ko, Yen, Liu, Huang, & Yen, 2009), drug use (Gong et al., 2009), and problematic alcohol use (Ko et al., 2008a). These comorbidities may be suggestive of a bidirectional causality relationship and similar etiology (Ko et al., 2008b, Mueser et al., 1998), and increased severity of psychopathology relative to a single presenting mental health problem (de Graaf, Bijl, Spijker, Beekman, & Vollebergh, 2003). In light of this, Internet addiction in adolescents cannot be dismissed as a transitory phenomenon that will take care of itself. Instead, it appears important to establish and explore a diagnosis that may prove beneficial for young populations who experience similar and related problems (King, Delfabbro, Griffiths, & Gradisar, 2012).
The personality traits that distinguish addicted gamers from high engagement gamers are reported to be negative extraversion (i.e., introversion), emotional stability, agreeableness, negative valence (indicated by being demanding, needy, and eager to impress), and attractiveness (characterised by care about appearance, being well groomed, neat and efficient, and highly motivated) (Charlton & Danforth, 2010). Other research has indicated that online gaming addiction may be related to neuroticism, anxiety, and sensation seeking (Mehroof & Griffiths, 2010). Apart from online gaming, research indicates that adolescent Internet addicts score significantly lower on extraversion compared to non-addicted adolescents (Huang et al., 2010), have low emotional stability, low extraversion, and low agreeableness (van der Aa et al., 2009). In summary, low emotional stability, low agreeableness, and low extraversion seem convincing candidates for increasing the risk of Internet addiction as these associations are found in multiple studies. However, to date, no study has investigated the interactions between personality and different types of potentially problematic Internet usage in increasing the risk for being addicted to using the Internet. Assessing the interactions between these variables may allow discerning both risk as well as protective factors for Internet addiction in adolescents who use the Internet frequently. Specifically, the identification of characteristics that demarcate frequent users who develop addiction symptoms from frequent users who do not may prove beneficial with regards to prevention and treatment. Behaviours and cognitions associated with the preventive character traits in the risk groups (i.e., high frequency users of specific Internet applications) can be established and maintained.
With this study, it is aimed to fill the gap in knowledge in current research by (i) assessing the prevalence of Internet addiction in a large sample of adolescents, and (ii) for the first time exploring the interactions between personality traits and the usage of particular Internet applications as risk factors for Internet addiction. Based on previous research, the hypotheses are that (i) using online applications that enable social functions (i.e., SNSs, chatting, instant messaging, and Twitter) and online gaming, and (ii) specific personality traits (i.e., low emotional stability, low agreeableness, and low extraversion) increase the risk for being addicted to the Internet, and (iii) there exist interaction effects between the usage of specific Internet applications and personality traits in elevating or decreasing the chances of Internet addiction, the precise nature of which still needs to be determined.
Section snippets
Design
In this study, the 2011 subsample of the annual Monitor study “Internet and Youth” (Eijnden, Spijkerman, Vermulst, van Rooij, & Engels, 2010) which specifically assesses Internet usage behaviours among adolescents was utilised, including 3173 adolescents from 13 schools in the Netherlands. The Monitor study uses school sampling stratified according to region of the school, urbanisation, and education level. A total of 3756 questionnaires were distributed in participating classes with an overall
Results
Response pattern analysis revealed a total of 2457 different response patterns in the data for the CIUS, indicating a good variability in CIUS scores. When analysing the response pattern in more detail, 191 participants answered “never” to all items, and “seldom”, “sometimes”, “often” and “very often” were endorsed on all items by one participant each. In terms of Internet use, results indicated that nearly all adolescents (99.8%) used the Internet at home or in school. In 44.9% of cases,
Discussion
In the present research, the risk for Internet addiction in a large sample of Dutch adolescents was investigated by looking at the interplay between personality traits and the usage of different Internet applications. Using a validated self-report measure (Meerkerk et al., 2009), it was found that 3.7% of the adolescents included were classified as addicted to using the Internet. This appears to be at the more conservative end of estimates that range from 1.5% in Greece (Kormas et al., 2011) to
Conclusion
In conclusion, Internet addiction appears as a mental health problem for Dutch adolescents. The results support the American Psychiatric Association’s efforts to include Internet addiction in the updated version of the DSM as a psychiatric condition that requires further research (2012). Although conservative relative to other estimates, the reported prevalence of addiction-related problems in 3.7% of the present Dutch adolescent sample is somewhat disconcerting. Internet addiction is
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