A Discriminant Analysis to Predict the Impact of Personality Traits, Self-esteem, and Time Spent Online on Different Levels of Internet Addiction Risk among University Students

The aim of the current study is to evaluate the predictive influence of Big Five personality traits, self-esteem, and time spent online in discriminating among a sample of university students classified as normal, mildly, and moderately addicted Internet users. Self-report measures were administered to 207 Italian university students aged 19 to 41 years. Results indicated no severe Internet addiction among the participants, but only a mild and moderate risk. Correlation analysis revealed a significant negative association between Internet addiction score and self-esteem. The discriminant analysis indicated two main functions that allow discrimination in terms of the influence of personality traits, self-esteem, and time spent online in three groups of participants. These results may have valid implications in assessing students engaged in intensive online activities, indicating that tailored approaches to their problems are particularly important in preventing the risk of Internet addiction disorder.

Abstract licence: CC BY

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