Study for Relations between Smart-Phone Addiction Level and Korea Youth Self Report

스마트폰 중독 정도와 한국형 청소년 자기행동평가척도와의 상관성에 대한 연구

  • Seo, Chang Min (Department of Psychiatry, Catholic University of Daegu School of Medicine) ;
  • Lee, Jonghun (Department of Psychiatry, Catholic University of Daegu School of Medicine) ;
  • Choi, Tae Young (Department of Psychiatry, Catholic University of Daegu School of Medicine) ;
  • Kim, Jihyun H. (Department of Psychiatry, Catholic University of Daegu School of Medicine) ;
  • Shin, Imhee (Department of Medical Statistics, Catholic University of Daegu School of Medicine) ;
  • Woo, Jungmin (Department of Psychiatry, Catholic University of Daegu School of Medicine)
  • 서창민 (대구가톨릭대학 의과대학 정신건강의학교실) ;
  • 이종훈 (대구가톨릭대학 의과대학 정신건강의학교실) ;
  • 최태영 (대구가톨릭대학 의과대학 정신건강의학교실) ;
  • 김지현 (대구가톨릭대학 의과대학 정신건강의학교실) ;
  • 신임희 (대구가톨릭대학 의과대학 의학통계학교실) ;
  • 우정민 (대구가톨릭대학 의과대학 정신건강의학교실)
  • Published : 2012.12.31

Abstract

Objectives: Recent years, the smart-phone usage has been rapidly increased. While it gave us many conveniences and be-nefits, the adverse effects also came to emerge and threatened individual's mental health. Especially, its overusage in the adolescents can have substantial impact on their psychosocial development. We aim to evaluate the psychopathologies of the adolescents according to smart-phone addiction level, by using the Korea-Youth Self Report. Methods: We selected four high schools within Daegu, Korea. Among the smart-phone users, 276 subjects were enrolled. The severity of addiction was measured through '2010 Smart-phone Addiction Rating Scales' guided by the Korean Internet & Security Agency. The psychopathologies of the subjects were evaluated with the Korea-Youth Self Report. Results: The total score of the Smart-phone Addiction Rating Scales and the total problematic behavior score of Korea-Youth Self Report showed a positive correlation(r=.412, p<0.001). The group with more severely addicted showed higher T-scores on the nine of eleven subscales of the Korea-Youth Self Report[somatic complaints(p<0.05), anxiety/depression(p<0.01), thought problems(p<0.01), attention problems(p<0.001), delinquency(p<0.001), aggressiveness(p<0.001), inter- nalizing problems(p<0.001), externalizing problems(p<0.001), total problematic behaviors(p<0.001)]. Among the contents and situations of smart-phone usage, utilizing the smart-phone for Social Network Services(OR : 1.83 ; 95% CI :1.29-2.59) and situations of smart-phone usage like 'in bedtime'(OR : 1.52, 95% CI :1.04-2.23), 'at bathroom'(OR : 1.84, 95% CI :1.28-2.65) w-ere risk factors for high level group of smart-phone addiction. Conclusions: We suggest that smart-phone addiction level is related to compromised psychological well-being of the adolescences. Also, Specific purpose and situations of smart-phone usages are associated to smart-phone addiction level. In the future, if more obvious psychopathologies and risk factors are grasped, it may be helpful in screening and intervention of high risk adolescent to smart-phone addiction.

Keywords

References

  1. Nielsen. Smartphone penetration. Nielson mobile insight; 2012.
  2. 염성희. 유무선통신가입자 통계 현황, 방송통신위원회; 2012.
  3. Yun MH, Kim SJ.. Global mobile software platform trends. J Elec Teleco Trends; 2008. p. 23.
  4. 한국 인터넷 진흥원. 2011년 상반기 스마트폰 이용실태 조사. 방송통신위원회; 2011.
  5. American Psychiatric Association. Diagnostic and Statistical Manual of Mental disorder: DSM-IV-TR. Washington, DC: APA; 2000.
  6. 한국 인터넷 진흥원. 2010년 인터넷 및 스마트폰 중독 실태 보고서, 방송통신위원회; 2010.
  7. Tahiroglou AY, Celik GG, Uzel M, Ozcan N, Avci A. Internet use among Turkish adolescents. Cyberpsychol Behav 2008;11:537-43. https://doi.org/10.1089/cpb.2007.0165
  8. Leung L. Stressful life events, motives for internet use, and social support among digital kids. Cyberpsychol Behav 2007;10:204-14. https://doi.org/10.1089/cpb.2006.9967
  9. Pallanti S, Bernardi S, Quercioli L. The Shorter PROMIS questionnaire and the internet addiction scale in the assess- ment of multiple addictions in a high-school population: prevalence and related disability. CNS Spectr 2006;11:966-74.
  10. Ha EH. A validation study of the Korean Youth Self Report. Sook-Myung J Child Study 2005;18:83-104
  11. Edelbrock C, Costello AJ, Dulcan Mk, Conover MC, Kala R. Parent-child agreement on child psychiatric symptoms assessed via structured interview. J Child Psychol Psychiatry 1986;27:181-90.
  12. Kormas G, Critselis E, Janikian M, Kafetzis D, Tsitsika A. Risk factors and psychosocial characteristics of potential pr-oblematic and problematic internet use among adolescents: a cross-sectional study. BMC Public Health 2011;11:595. https://doi.org/10.1186/1471-2458-11-595
  13. Morahan-Martin J, Schumacher P. Incidence and correlates of pathological Internet use among college students. Comput Human Behav 2000;16:13-29. https://doi.org/10.1016/S0747-5632(99)00049-7
  14. McKenna KY, Bargh JA. The implications of the internet for personality and social psychology. Pers Soc Psychol Rev 2000;4:57-75. https://doi.org/10.1207/S15327957PSPR0401_6
  15. Kim EJ, Namkoong K, Ku T, Kim SJ. The relationship between online game addiction and aggression, selfcontrol and narcissistic personality traits. Eur Psychiatry 2008;23:212-8. https://doi.org/10.1016/j.eurpsy.2007.10.010
  16. Ha JH, Yoo HJ, Cho IH, Chin B, Shin D, Kim JH, et al. Psychiatric comorbidity assessed in Korean children and adolescents who screen positive for internet addiction. J Clin Psychiatry 2006;67:821-6. https://doi.org/10.4088/JCP.v67n0517
  17. Yen JY, Ko CH, Yen CF, Chen SH, Chung WL, Chen CC, et al. Psychiatric symptoms in adolescents with internet addiction: comparison with substance use. Psychiatry Clin Neurosci 2008;62:9-16. https://doi.org/10.1111/j.1440-1819.2007.01770.x
  18. Young KS. Psychology of computer use: XL, Addictive use of the internet: A case that breaks the stereotype. Psychological Rep 1996;79:899-902. https://doi.org/10.2466/pr0.1996.79.3.899
  19. Lee JY. An exploration of socio-environmental and individual- psychological variable affecting the adolescent's cellular phone addiction[dissertation]. Korea National University of Education Graduate School; Cheongwon; 2006.
  20. Shin Hk, Lee MS, Kim HG. An empirical study on mobile usage behavior; focusing on smartphone usage addiction. Informatization Policy 2011;18:50-68.
  21. Park JS. The Variables in Influencing on Smart phone Addiction in Adolescents and College Students [dissertation]. Graduate School of Education of Dankook University; Korea; 2011.
  22. Lee MS. Smartphone Addiction and Related Social Concerns[dissertation]. Graduate School of Information of Yonsei University; Korea; 2010.
  23. Becker JB, Hu M. Sex differences in drug abuse. Front Neuroendocrinol 2008;29:36-47. https://doi.org/10.1016/j.yfrne.2007.07.003
  24. Becker JB, Perry AN, Westenbroek C. Sex differences in the neural mechanisms mediating addiction: a new synthesisand hypothesis. Biol Sex Differ 2012;3:14. https://doi.org/10.1186/2042-6410-3-14
  25. Rees H, Noyes J. Mobile telephones, computers, and the internet. Sex differences in adolescents' use and attitudes. Cyberpsychol Behav 2007;10:482-4. https://doi.org/10.1089/cpb.2006.9927
  26. Lam LT, Peng ZW, Mai JC, Jing J. Factors associated with internet addiction among adolescents. CyberPsychology Behav 2009;12:551-5. https://doi.org/10.1089/cpb.2009.0036
  27. Odell PM, Korgen KO, Schumacher P, Delucchi M. Internet use among female and male college students. CyberPsychology Behav 2000;3:855-62. https://doi.org/10.1089/10949310050191836
  28. Weiser EB. Gender differences in internet use patterns and internet application preferences: A two-sample comparison. CyberPsychology Behav 2000;3:167-77. https://doi.org/10.1089/109493100316012
  29. Achenbach TM. Manual for the child Behavior Checklist: 4-18 and 1991 Profile. Burlington: University of Vermont, Department of Psychiatry; 1991.
  30. Ha EH, Lee SJ, Oh KJ, Hong GE. Parent adolescent agreement in the assessment of behavior problems of adolescents: comparison of factor structures of K-CBCL and YSR. J Korean Acad Child Adolesc Psychiatry 1998;9:3-12.