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Studying internet addiction profile of university students with latent class analysis

机译:潜在阶级分析研究大学生互联互联概况

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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.
机译:本研究确定了大学生对潜在阶级分析的互联网成瘾型材,基于他们对互联网成瘾测试(IAT)的反应。该研究组由480名大学生组成。根据总分分为四组:“正常(0-30),温和(31-49),中等(50-79)和严重(80及以上)”的互联网成瘾水平(年轻2010)。在IAT中六个因素的潜在阶段的表现发现了三个潜在的级别,过度使用,忽视工作和预期因素的三个潜在课程中的显着差异。在这些中,最高潜在的阶级(LC3)的平均得分在60左右,虽然潜伏等级2(LC2)和潜伏等级1(LC1)分别为50和40,其中潜在课程之间的区别是显而易见的。然而,关于“缺乏控制和社会生活的忽视和忽视社会生活的因素”之间的差异是可忽略的低,表明这两个因素只有两种重要组(LC1和LC2)。这些结果表明,相同的聚类标准不能应用于IAT的每个因子,并且使用每个因素的相同标准可能导致个人的分类不准确和偏见。

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