Skip to main content

Relation Between Depression, Loneliness, Self-Esteem and Internet Addiction

Buy Article:

$24.00 + tax (Refund Policy)

Problem: Internet addiction has been emerged as a result of excessive internet misuse. In this study, analyzing the effects of depression, loneliness and self-esteem has been aimed in the prediction of the internet addiction levels of secondary education students.

Method: The research is conducted according to the cross-sectional model as one of the survey models. The sample of the research is comprised of 292 students who continue their education in the first term of 2009-2010 academic year in Trabzon. Internet addiction, Beck depression, UCLA loneliness and Rosenberg self-esteem scale have been used as data collection tool in the research. Result: In consequence of the research a positive, mid-level and significant relation with internet addiction has come out when depression, loneliness and self-esteem variables are considered together. These variables explain 14 % of internet addiction's total variance.

Conclusions: The relative order of importance of the variables on internet addiction is depression, loneliness and self-esteem. While depression and loneliness variables are significant predictors on internet addiction, self-esteem is not a significant predictor.

Keywords: Depression; Internet addiction; Loneliness; Self-esteem

Document Type: Research Article

Publication date: April 1, 2013

More about this publication?
  • Education publishes original investigations and theoretical papers dealing with worthwhile innovations in learning, teaching, and education. Preference is given to innovations in the school — proposed or actual — and theoretical or evaluative. Papers concern all levels and every area of education and learning. Education is primarily concerned with teacher preparation in all of its many aspects.
  • Information for Authors
  • Submit a Paper
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content