Occurence of internet addiction in a general population sample: a latent class analysis

Eur Addict Res. 2014;20(4):159-66. doi: 10.1159/000354321. Epub 2013 Dec 24.


Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence.

Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence.

Methods: A telephone survey was conducted based on a random digit dialling procedure including landline telephone (n=14,022) and cell phone numbers (n=1,001) in participants aged 14-64. The Compulsive Internet Use Scale (CIUS) served as the basis for a LCA used to look for subgroups representing participants with Internet addiction or at-risk use. CIUS was given to participants reporting to use the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend (n=8,130).

Results: A 6-class model showed best model fit and included two groups likely to represent Internet addiction and at-risk Internet use. Both groups showed less social participation and the Internet addiction group less general trust in other people. Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample, 2.4% (CI 1.9-3.1) in the age group 14-24, and 4.0% (CI 2.7-5.7) in the age group 14-16. No difference in estimated proportions between males and females was found. Unemployment (OR 3.13; CI 1.74-5.65) and migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction.

Conclusions: This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population and provides characteristics to further define this rather new disorder.

MeSH terms

  • Adolescent
  • Adult
  • Behavior, Addictive / epidemiology*
  • Emigration and Immigration / statistics & numerical data*
  • Female
  • Humans
  • Internet*
  • Male
  • Middle Aged
  • Models, Statistical
  • Prevalence
  • Risk Factors
  • Unemployment / statistics & numerical data*
  • Young Adult