Hostname: page-component-f554764f5-fnl2l Total loading time: 0 Render date: 2025-04-16T20:17:59.177Z Has data issue: false hasContentIssue false
  • English
  • Français

Attached to the web — harmful use of the Internet and its correlates

Published online by Cambridge University Press:  16 April 2020

J. Korkeila ,
S. Kaarlas ,
M. Jääskeläinen ,
T. Vahlberg  and
T. Taiminen
J. Korkeila*
Affiliation:
Department of Psychiatry, University of Turku, Kunnallissairaalantie 20, 20700Turku, Finland Harjavalta Hospital, Satakunta Hospital District, Sairaalatie 14, 29200Harjavalta, Finland
S. Kaarlas
Affiliation:
Department of Psychiatry, University of Turku, Kunnallissairaalantie 20, 20700Turku, Finland
M. Jääskeläinen
Affiliation:
Turku University Central Hospital, Kiinanmyllynkatu 4–8, 20521Turku, Finland
T. Vahlberg
Affiliation:
Department of Biostatistics, University of Turku, Lemminkäisenkatu 1, 20014Turun Yliopisto, Finland
T. Taiminen
Affiliation:
Department of Psychiatry, Turku University Central Hospital, Kiinanmyllynkatu 4–8, 20521Turku, Finland
*
*Corresponding author. Tel.: +358 2 269 2557; fax: +358 2 269 2528. E-mail addresses: [email protected], [email protected] (J. Korkeila).
Get access

Abstract

Background and aims

The aim of this study was to test the validity of the Finnish version of the Internet Addiction Test and the correlates of harmful use of the Internet.

Methods

One thousand eight hundred and twenty-five students (45.5% men and 54.5% women, mean age 24.7 years, S.D. = 5.7) filled in a web-based questionnaire including IAT, reasons for use of the Internet, distress, social support, and substance use.

Results

Men had a statistically significantly higher mean score on the IAT than women. Subjects with self-reported use of cannabis had higher mean score on the IAT compared to non-users (39.5 [11.3] vs 35.8 [10.8]). The total IAT score was associated with “adult entertainment” (OR = 1.07, 95%CI: 1.06–1.08, P < 0.001), “playing games” (OR = 1.05, 95%CI: 1.04–1.06, P < 0.001), “chatting” (OR = 1.07, 95%CI: 1.06–1.08, P < 0.001) and “discussion” (OR = 1.08, 95%CI: 1.07–1.09, P < 0.001) as reasons for Internet use. The IAT score had a significant negative correlation with social support (r = −0.24, P < 0.001) and a significant positive correlation with the CAGE score (r = 0.18, P < 0.001). Using factor analysis, we found a single factor solution with a Cronbach's α of 0.92.

Conclusions

The IAT seems to provide a valid measurement of harmful use of the Internet, as the score was significantly associated with variables tapping psychopathology.

Keywords

Internet addictionPsychological distressSubstance abuseSocial support
Type
Original article
Information
European Psychiatry , Volume 25 , Issue 4 , May 2010 , pp. 236 - 241
Copyright
Copyright © Elsevier Masson SAS 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Anderson, S.E., Gansneder, B.M.Using electronic mail surveys and computer-monitored data for studying computer-mediated communication systems. Soc Sci Comput Rev 1995; 13: 53–85.CrossRefGoogle Scholar
Beard, K.W., Wolf, E.M.Modification in the proposed diagnostic criteria for Internet addiction. Cyberpsychol Behav 2001; 4: 377–383.CrossRefGoogle ScholarPubMed
Berwick, D.M., Murphy, J.M., Goldman, P.A., Ware, J.E., Barsky, A.J., Weinstein, M.C.Performance of a five-item mental health-screening test. Med Care 1991; 29: 169–176.CrossRefGoogle ScholarPubMed
Bijl, R., Ravelli, A.Current and residual functional disability associated with psychopathology Findings from the Netherlands Mental Health Survey and Incidence Study (NEMESIS). Psychosom Med 2000; 30: 657–668.CrossRefGoogle Scholar
Black, D.W., Belsare, G., Schlosser, S.Clinical features, psychiatric comorbidity, and health-related quality of life in persons reporting compulsive computer use behavior. J Clin Psychiatry 1999; 60: 839–844.CrossRefGoogle ScholarPubMed
Block, J.J.Issues for DSM-V: Internet addiction. Am J Psychiatry 2008; 165: 306–307.CrossRefGoogle ScholarPubMed
Brown, R.I.E.Gaming, gambling and other addictive play. Kerr, J.H., Apter, M.J., Adult play: A reversal theory approach. Amsterdam: Swets & Zeitlinger; 1991. 101–118.Google Scholar
Campbell, A.J., Cumming, S.R., Hughes, I.Internet use by the socially fearful: addiction or therapy?. Cyberpsychol Behav 2006; 9: 69–81.CrossRefGoogle ScholarPubMed
Charlton, J.P.A factor-analytic investigation of computer “addiction” and engagement. Br J Psychol 2002; 93: 329–344.CrossRefGoogle ScholarPubMed
Cherpitel, C.J.Analysis of cut points for screening instruments for alcohol problems in the emergency room. J Stud Alcohol 1995; 56: 695–700.CrossRefGoogle ScholarPubMed
Couper, M.P., Blair, J., Triplett, A comparison of mail and e-mail for a survey of employees in US Statistical Agencies. J Off Stat 1999; 15: 39–56.Google Scholar
Dalgard, OS.Community health profile as tool for psychiatric prevention. In: Trent, DR, Reed, C, editors. Promotion of mental health, vol. 5. Aldershot: Avebury; 1996.Google Scholar
Demetrovics, Z., Szeredi, B., Rózsa, S.The three-factor model of Internet addiction: The development of the Problematic Internet Use Questionnaire. Behav Res Methods 2008; 40: 563–574.CrossRefGoogle ScholarPubMed
Engelberg, E., Sjöberg, L.Internet use, social skills, and adjustment. Cyberpsychol Behav 2004; 7: 41–47.CrossRefGoogle Scholar
Greenfield, D.N., Davis, R.A.Lost in cyberspace: The web @ work. Cyberpsychol Behav 2002; 5: 347–353.CrossRefGoogle Scholar
Griffiths, M.Psychology of computer use: XLIII Some comments on “addictive use of the Internet” by Young. Psychol Rep 1997; 70: 81–82.CrossRefGoogle Scholar
Kaltiala-Heino, R., Lintonen, T., Rimpelä, A.Internet addiction? Potentially problematic use of the Internet in a population of 12–18 year-old adolescents. Addict Res Theory 2004; 1: 89–96.CrossRefGoogle Scholar
Korkeila, J., Lehtinen, V., Dalgard, O.S., Kovess, V., Madianos, M., Salize, H.J.Piloting a minimum data set for mental health indicators for Europe. J Mental Health 2007; 16: 401–413.CrossRefGoogle Scholar
Kovess, V. and “The State of Mental Health in The European Union” collaborators. The State of Mental Health in the European Union. Health and Consumer Protection Directorate General. European Communities: European Commission. 2004. Available at http://www.europa.eu.int/comm/health/ph_projects/2001/monitoring/fp_monitoring_2001_frep_06_en.pdf.Google Scholar
Lee, Y.S., Hyun Han, D., Yang, K.C., Daniels, M.A., Na, C., Seok Kee, B.et al.Depression like characteristics of 5HTTLPR polymorphism and temperament in excessive Internet users. J Affect Dis 2008; 109: 165–169.CrossRefGoogle ScholarPubMed
Liu, C.-Y., Kuo, F.-Y.A study of Internet addiction through the lens of the interpersonal theory. Cyberpsychol Behav 2007; 10: 799–804.CrossRefGoogle ScholarPubMed
Mayfield, D., McLeod, G., Hall, P.The CAGE questionnaire: validation of a new alcoholism screening instrument. Am J Psychiatry 1974; 131: 1121–1123.Google ScholarPubMed
McCabe, C.J., Thomas, K.J., Brazier, J.E., Coleman, P.Measuring the mental health status of a population: a comparison of the GHQ-12 and the SF-36 (MHI-5). Br J Psychiatry 1996; 169: 517–521.CrossRefGoogle Scholar
Mick, T.M., Hollander, E.Impulsive-compulsive sexual behavior. CNS Spectr 2006; 11: 944–955.CrossRefGoogle ScholarPubMed
Nalwa, K., Anand, A.P.Internet addiction in students: a cause for concern. Cyberpsychol Behav 2003; 6: 653–656.CrossRefGoogle Scholar
Nichols, L.A., Nicki, R.Development of a psychometrically sound Internet addiction scale: a preliminary step. Psychol Addict Behav 2004; 18: 381–384.CrossRefGoogle ScholarPubMed
Orford, J.Conceptualizing addiction. Addiction as excessive appetite. Addiction 2001; 96: 15–31.CrossRefGoogle Scholar
Özcan, N.K., Buzlu, S.Internet use and its relation with the psychosocial situation for a sample of university students. Cyberpsychol Behav 2007; 10: 7676–7772.CrossRefGoogle ScholarPubMed
Rumpf, H.J., Meyer, C., Hapke, U., John, U.Screening for mental health: validity of the MHI-5 using DSM-IV Axis I psychiatric disorders as gold standard. Psychiatry Res 2001; 105: 243–253.CrossRefGoogle ScholarPubMed
Saxon, D., Garratt, D., Gilroy, P., Cairns, C.Collecting data in the information age. Exploring web-based survey methods in educational research. Res Educ 2003; 69: 51–66.CrossRefGoogle Scholar
Shapira, N.A., Goldsmith, T., Keck, P.E., Khosla, U.M., McElroy, S.L.Preliminary communication: Psychiatric features of individuals with problematic Internet use. J Affective Dis 2000; 57: 267–272.CrossRefGoogle Scholar
Shaw, M., Black, D.W.Internet addiction: definition, assessment, epidemiology and clinical management. CNS Drugs 2008; 22: 353–365.CrossRefGoogle ScholarPubMed
Statistics Finland. Survey on ICT usage in households and by individuals. 2007. Available at http://www.stat.fi/til/sutivi/2007/sutivi_2007_2007-09-28_tie_001_en.html (website consulted on 28th September 2007).Google Scholar
Ware, J.E. Jr., Sherbourne, C.D.The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992; 30: 473–483.CrossRefGoogle ScholarPubMed
Webropol Company Finland. Available at http://www.webropol.com/ (website consulted on 1st January 2003).Google Scholar
Whang, L.S., Lee, S., Chang, G.Internet over-users’ psychological profiles: a behavior sampling analysis on Internet addiction. Cyberpsychol Behav 2003; 6: 143–150.CrossRefGoogle ScholarPubMed
Widyanto, L., McMurran, M.The psychometric properties of the Internet Addiction Test. Cyberpsychol Behav 2004; 7: 443–450.CrossRefGoogle ScholarPubMed
Yammarino, F.J., Skinner, S.J., Childers, T.L.Understanding mail survey response behavior. A meta-analysis. Public Opin Q 1991; 55: 613–639.CrossRefGoogle Scholar
Yoo, H.J., Cho, S.C., Ha, J., Kim, S.J., Hwang, J., Chung, A.et al.Attention deficit hyperactivity and Internet addiction. Psychiatry Clin Neurosci 2004; 58: 487–494.CrossRefGoogle ScholarPubMed
Young, K.Caught in the Net. New York: John Wiley & Sons; 1998.Google Scholar
Young, K.S., Case, C.J.Internet abuse in the workplace: new trends in risk management. Cyberpsychol Behav 2004; 7: 105–111.CrossRefGoogle ScholarPubMed
Yuen, C.N., Lavin, M.J.Internet dependence in the collegiate population: the role of shyness. Cyberpsychol Behav 2004; 7: 379–383.CrossRefGoogle Scholar
Submit a response

Comments

No Comments have been published for this article.