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Studying internet addiction profile of university students with latent class analysis

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Abstract

This study determined the internet addiction profiles of university students with latent class analysis based on their responses to Internet Addiction Test (IAT). The study group consisted of 480 university students. The participants were classified into four groups according to their total score: “normal (0-30), mild (31-49), moderate (50-79) and severe (80 and above)” level of internet addiction, respectively (Young 2010). The performance of latent classes across six factors of IAT found substantial difference among three latent classes for salience, excessive use, neglect of work and anticipation factors. Amongst these, the mean score of highest latent class (LC3) was around 60 while it was 50 and 40 for latent class 2 (LC2) and latent class 1 (LC1), respectively, in which distinction between latent classes were obvious. However, discrepancy between higher two classes (LC2 and LC3) with respect to the factors of “lack of control and the neglect of social life” were negligible low indicating the existence of only two significant classes (LC1 and LC2) for these two factors. These results suggest that the same clustering criterion cannot be applied to each factor of IAT and using same criterion for each factor might lead to inaccurate and biased classification of individuals.

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This study observed ethics of social science research. It is non-sponsored study and NO funding was obtained from any organization.

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Authors and Affiliations

  1. Department of Education, The Islamia University of Bahawalpur, Bahawalpur, Pakistan

    Irshad Hussain

  2. Department of Computer Education and Instructional Technologies, Faculty of Educational Sciences, Ankara University, Ankara, Turkey

    Ozlem Cakir

  3. Department of Mathematics and General Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Burhanettin Ozdemir

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  1. Irshad Hussain
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  2. Ozlem Cakir
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  3. Burhanettin Ozdemir
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Correspondence to Irshad Hussain.

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Appendix

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Table 5 The Chi-Square Test on Statistical Dependency between Gender and Latent Class of Students
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Table 6 The Chi-Square Test on Statistical Dependency between Locality and Latent Class of Students
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Table 7 The Chi-Square Test on Statistical Dependency Between Education Level and Latent Class of Students
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Table 8 The Chi-Square Test on Statistical Dependency Between Students’ Age and Latent Class of Students
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Table 9 The Chi-Square Test on Statistical Dependency Between classification based on total score and Latent Class of Students
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Hussain, I., Cakir, O. & Ozdemir, B. Studying internet addiction profile of university students with latent class analysis. Educ Inf Technol 25, 4937–4959 (2020). https://doi.org/10.1007/s10639-020-10203-6

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