잠재계층분석(LCA)을 활용한 아동·청소년 사이버폭력 피해집단 유형 및 영향요인 분석

초록

This research aimed to categorize and analyze groups of children and adolescents affected by cyber violence based on symptoms observed after experiencing such victimization. Using data from the 2022 Cyber Violence Survey conducted by the Korea Communications Commission and the National Information Society Agency(NIA), a latent class analysis(LCA) was conducted, and four victim groups were identified: the non-risk group, the academic & relational problems group, the depression & anxiety group, and a high-risk group. Building upon this foundation, a multinomial logistic regression was conducted to explore the factors influencing the categorization of victim groups. The analysis unveiled that personal factors, such as gender and internet usage time, along with victim-related factors, including the frequency of victimization based on violence types, perpetrator characteristics, the number of perpetrators involved, and the duration of victimization, exerted a meaningful impact on the categorization of victim groups. Based on the above analysis, the implications and limitations of the study were discussed.

키워드