Objective To identify the latent classes of cyberbullying in college students, and to analyze its relationship with de-pressive symptoms and suicidal ideation, so as to provide a theoretical reference for effectively intervention of cyberbullying.
Methods Cluster random sampling was used to select 1 094 college students from Liaoning Province and Jilin Province from April to May, 2021. The Cyberbullying Victims’ Behaviors Scale, the Center for Epidemiological Studies Depression Scale and BSI-CV wereused in this study and data was analyzed by using latent class analysis, one-way analysis of variance and Logistic regression to analyze the data.
Results Cyberbullying of college students could be divided into three latent classes: low incidence group (72.40%), general incidence group (20.20%) and high incidence group(7.40%). There were significant differences in depressivesymptoms and suicidal ideation among different classes of cyberbullying ( P<0.01). Logistic regression analysis showed that aftercontrolling for demographic variables, general incidence group and high incidence group significantly and positively predicted depressive symptoms (β general incidence group=0.88, β high incidence group=2.44, P<0.01) and suicidal ideation (β general incidence group=0.50, β high incidence group=1.20, P<0.01.
Conclusion Families, schools and society should conduct different interventions for collegestudents who suffer from different classes of cyberbullying to reduce depressive symptoms and suicidal ideation and promote mental health of college students.
【摘要】 目的 识别大学生网络欺凌的潜在类别, 分析不同潜在类别与抑郁症状、自杀意念的关联, 以期为有效开展网络欺凌干预工作提供理论依据。 方法 采用方便整群随机抽样的方法, 于2021年4一5月在辽宁省和吉林省抽取1 094名大学生进行问卷调査。采用受网络欺凌行为问卷、流调中心抑郁量表中文版和Beck自杀意念量表中文版, 对数据进行潜在类别分析、单因素方差分析及Logistic回归分析。 结果 大学生网络欺凌可分为低发组(72.40%)、普通组(20.20%)和髙发组(7.40%)3个类别, 不同类别的网络欺凌者在抑郁症状和自杀意念上差异均有统计学意义( P值均<0.01)。Logistic回归分析结果显示, 控制人口学变量后, 网络欺凌普通组和网络欺凌髙发组均能正向预测抑郁症状(β 普通组=0.88, β 髙发组=2.44)和自杀意念(β 普通组=0.50, β 髙发组=1.20) ( P值均<0.01)。 结论 家庭-学校-社会可以针对不同类别的网络欺凌大学生进行干预, 以防范大学生抑郁症状及自杀意念的发生, 提升其心理健康水平。