¼­¹ÎÀç, ÃÖÅ¿µ, ¿ìÁ¤¹Î, ±èÁöÇö, ÀÌÁ¾ÈÆ (2013). Çѱ¹ û¼Ò³â Á¤½Åº´¸®¿Í ½º¸¶Æ®Æù Áßµ¶ ¹× ÀÎÅÍ³Ý Áßµ¶ÀÇ »ó°ü¼º. »ý¹°Ä¡·áÁ¤½ÅÀÇÇÐ, 19(2), 154-162.

Objectives: Despite the benefits of smartphone, the adverse effects have emerged. While it is well known that the internet addiction could affect mental health in adolescents, the information about the effect of smartphone addiction is relatively limited. We evaluated the relationships among smartphone addiction, internet addiction and psychopathologies of adolescents.

Methods: One hundred ninety four adolescents participated in this study. The severity of addiction was measured through the 2010 Smart-phone Addiction Rating Scales(SARS) and Young Internet Addiction Scale(YIAS). The psychopathologies of the subjects were evaluated with the Korea-Youth Self Report(K-YSR). We evaluated the correlations among SARS, YIAS and K-YSR using Pearson¡¯s correlation and the differences of the K-YSR score depending on each degree of smartphone and internet addiction by one-way ANOVA.

Results: The total score of the SARS(r=0.469, p£¼0.001) and YIAS(r=0.440, p£¼0.001) had positive correlations with the total problematic behavior score of K-YSR, respectively. We divided the subjects into four groups which were the L-L group(low smartphone addiction-low internet addiction), L-H group(low smartphone addiction-high internet addiction), H-L group(high smartphone addiction-low internet addiction), H-H(high smartphone addiction-high internet addiction) group depending on the mean value of addiction. ANOVA revealed a significant difference among these groups on the nine of eleven subscales of the K-YSR.

Conclusion: Our result showed that the more addicted, the more severe psychopathologies, regardless of addictive patterns. The number of adolescents who addicted to smartphone use must be increased as the popularization of smartphone is inevitable social trend. We should try to screen the smart-phone addiction as well as internet addiction in adolescents.