School of Psychology, Inner Mongolia Normal University, Hohhot, Inner Mongolia, China.
College of Physical Education, Inner Mongolia Normal University, Saihan District, Hohhot, Inner Mongolia, China.
PLoS One. 2021 Mar 15;16(3):e0248555. doi: 10.1371/journal.pone.0248555. eCollection 2021.
The relationships between negative emotions and smartphone addiction has been tested through the literature. However, most of the studies applied variable-centered approaches. The heterogeneity of smartphone addiction severity has not been examined for the associations with negative emotion variables. The purposes of the present study is to explore the latent classes of smartphone addiction and analyze the relationships between depression, social anxiety and boredom and these subgroups. The Smartphone Addiction Scale-Short Version (SAS-SV) and three negative emotion scales were employed to conduct a survey of 539 college students. Mplus8.3 software was applied to perform the latent class analysis (LCA) based on the smartphone addiction symptom ratings. ANOVA and multinomial logistic regression were used to explore the differences among these latent categories and the associations between these subgroups and negative emotion variables. Results demonstrated that Negative emotional variables were significantly correlated with smartphone addiction proneness. Based on their scores on the Smartphone Addiction Scale, smartphone users were divided into three latent classes: low risk class, moderate class and high risk class. Women were more likely to be classified in the high-risk class. The severity of depression and boredom was able to predict the membership of the latent class effectively; while social anxiety failed to do this in the high risk class.
负面情绪与智能手机成瘾之间的关系已经在文献中得到了检验。然而,大多数研究采用了变量中心的方法。智能手机成瘾严重程度的异质性尚未被用来检验与负面情绪变量之间的关系。本研究的目的是探索智能手机成瘾的潜在类别,并分析抑郁、社交焦虑和无聊感与这些亚组之间的关系。采用智能手机成瘾量表短版(SAS-SV)和三个负面情绪量表对 539 名大学生进行了调查。基于智能手机成瘾症状评分,使用 Mplus8.3 软件进行潜在类别分析(LCA)。方差分析和多项逻辑回归用于探索这些潜在类别之间的差异,以及这些亚组与负面情绪变量之间的关联。结果表明,负面情绪变量与智能手机成瘾倾向显著相关。根据智能手机成瘾量表的得分,智能手机用户被分为三个潜在类别:低风险类、中度类和高风险类。女性更有可能被归入高风险类。抑郁和无聊感的严重程度能够有效地预测潜在类别的成员身份;而社交焦虑在高风险类别中无法做到这一点。