Short CommunicationSubstance abuse precedes internet addiction
Highlights
► Of internet users, 3.0 percent were users with high risk for internet addiction. ► The severity of internet use was correlated with the severity of substance use. ► Earlier onset of substance use was associated with internet addiction.
Introduction
Several studies have reported that the risk of internet addiction is associated with an increased prevalence of substance dependence (Bakken et al., 2009, Padilla-Walker et al., 2010). However, the subjects in most published studies have been adults and the number of subjects surveyed not been typically large enough to demonstrate significant co-morbidity of substance and internet addiction. Adolescence is a critical period which is characterized by risk-taking behavior, increased levels of novelty seeking and exploration, and intimate social interaction (Spear, 2000). In addition, 12% of 8th graders (13–14 years old) and 22% of 10th graders in USA students had episodes of heavy alcohol drinking within past two years (Johnston, O'Malley, Bachman, & Schulenberg, 2004).
The overlap between internet addiction and substance abuse and dependence may be due to similar characteristics predisposing toward, and brain regions responding to, internet use or substances. Individuals with internet addiction and substance addiction share similar temperaments. In a study of 686 high school students, Cho, Kim, Kim, Lee, and Kim (2008) reported that adolescents with problematic internet use showed higher self-directedness and cooperativeness and lower scores in novelty seeking and self-transcendence on a junior temperament and character inventory. In a study of 166 high school students, Lee et al. (2008) reported that adolescents with excessive internet use showed higher harm avoidance, relative to healthy comparison adolescents. In 88 patients with alcohol dependence, harm avoidance was negatively associated with the duration of abstinence (Ando et al., 2012) In addition, low novelty seeking and high self-directedness were also reported in adults with alcohol dependence (Anghelescu et al., 2010). Individuals with internet addiction and substance addiction may also share similar vulnerable brain regions including dorsolateral and orbitofrontal cortices (Crockford et al., 2005, Han et al., 2010, Ko et al., 2009).
Based on studies consistently reporting overlap and shared characteristics in individuals with internet and substance addiction, the purpose of the current study was to evaluate possible overlapping substance addiction and internet addiction in a large uniformly sampled population, ranging in age from 13 to 18 years.
Section snippets
Participants and data collecting
Seventy three thousand two hundred thirty eight participants in the current study were drawn from the 6th Korea Youth Risk Behavior Web-based Survey (KYRBWS-V) for students from 400 middle schools and 400 high schools in 16 cities within South Korea (KCDCP, 2011). The response rate for students was 97.7% (N = 73,238). The IRB of Chung Ang University Hospital approved data analysis without informed consent considering that the KYRBWS-V cohort is a nationally representative group and the survey
Demographic characteristics
Eighty-two percent of Korean teenager students reported use of the internet in the current survey. Of internet users, 85.2% were general users, 11.9% were users with potential risk for internet addiction, and 3.0% were users with high risk for internet addiction. Twenty one point two percent of students reported drinking alcohol. The rate of alcohol drinking in male students (23.5%) was higher than the rate (18.7%) in female students (χ2 = 256.9, p < 0.01). Twelve point two percent of students were
Discussion
The current study suggests that the risk for internet addiction is associated with smoking and drug use in teenage students. Moreover, the severity of internet use was positively correlated with the severity of alcohol use, smoking, and drug use. In addition, adolescents with earlier ages of onset of substance use and multiple substance use were more likely to be at increased risk of internet addiction. The present study is valuable for its uniform sampling of a large population with 73,000
Conclusions
As far as we know, this is the first large scale study of the correlation between substance abuse and internet addiction in teenagers. Because students with a high risk for internet addiction have vulnerability for addictive behaviors, co-morbid substance abuse should be evaluated and, if found, treated in adolescents with internet addiction.
Role of funding sources
Funding for this study was the Korea Centers for Disease Control & Prevention (KCDCP), 2011. This work was also supported by Korean Game Culture Foundation. KCDCP and KGCF had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
Contributors
Doug Hyun Han and Perry Renshaw designed the study and wrote the protocol. Young Sik Lee and Sun Mi Kim conducted literature searches and provided summaries of previous research studies. Doug Hyun Han conducted the statistical analysis. Doug Hyun Han and Perry Renshaw wrote the first draft of the manuscript and all authors contributed to and have approved the final manuscript.
Conflict of interest
All authors declare that they have no conflicts of interest.
Acknowledgement
We thank Korean Game Culture Foundation and Korea Center for Disease Control and Prevention (KCDCP) for presenting of data.
References (18)
- et al.
Cue-induced brain activity in pathological gamblers
Biological Psychiatry
(2005) - et al.
Brain activities associated with gaming urge of online gaming addiction
Journal of Psychiatric Research
(2009) - et al.
Depression like characteristics of 5HTTLPR polymorphism and temperament in excessive internet users
Journal of Affective Disorders
(2008) The adolescent brain and age-related behavioral manifestations
Neuroscience and Biobehavioral Reviews
(2000)- et al.
Massively multiplayer online role-playing games: Comparing characteristics of addict vs non-addict online recruited gamers in a French adult population
BMC Psychiatry
(2011) - et al.
Personality traits and coping compensate for disadvantageous decision-making in long-term alcohol abstinence
Alcohol and Alcoholism
(2012) - et al.
Low novelty seeking and high self directedness scores in alcohol-dependent patients without comorbid psychiatric disorders homozygous for the A10 allele of the dopamine transporter gene
The World Journal of Biological Psychiatry
(2010) - et al.
Test–retest reliability of a questionnaire for the Korea Youth Risk Behavior Web-based Survey
Journal of Preventive Medicine and Public Health
(2010) - et al.
Internet addiction among Norwegian adults: A stratified probability sample study
Scandinavian Journal of Psychology
(2009)
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