TY - JOUR
T1 - The Role of Intrapersonal-, Interpersonal-, Family-, and School-Level Variables in Predicting Bias-Based Cybervictimization
AU - Strohmeier, Dagmar
AU - Gradinger, Petra
AU - Yanagida, Takuya
N1 - Publisher Copyright:
© The Author(s) 2021.
PY - 2022/11
Y1 - 2022/11
N2 - This study investigated whether social position (e.g., gender, migration, family status), intrapersonal-level (e.g., online risk behaviors, motives of Internet use), interpersonal-level (e.g., victimization and bullying), family-level (e.g., parental mediation), and class-level (e.g., teachers’ mediation, ethnic diversity) variables predict bias-based cybervictimization. Self-report questionnaires were completed by 1,018 Austrian adolescents (52.3% girls), aged 12 to 17 years ((Formula presented.) = 13.55, SD = 0.88). The logistic part of a multilevel zero-inflated Poisson model showed that higher levels of offline victimization and a higher proportion of immigrants in classes were predictors for students reporting at least one form of bias-based cybervictimization. The Poisson part of the model showed that being a girl, higher levels of cybervictimization, lower levels of avoiding online risks, and more discussions about media use with teachers in classes were predictors for students reporting a higher number of bias-based cybervictimization. Implications for prevention are discussed.
AB - This study investigated whether social position (e.g., gender, migration, family status), intrapersonal-level (e.g., online risk behaviors, motives of Internet use), interpersonal-level (e.g., victimization and bullying), family-level (e.g., parental mediation), and class-level (e.g., teachers’ mediation, ethnic diversity) variables predict bias-based cybervictimization. Self-report questionnaires were completed by 1,018 Austrian adolescents (52.3% girls), aged 12 to 17 years ((Formula presented.) = 13.55, SD = 0.88). The logistic part of a multilevel zero-inflated Poisson model showed that higher levels of offline victimization and a higher proportion of immigrants in classes were predictors for students reporting at least one form of bias-based cybervictimization. The Poisson part of the model showed that being a girl, higher levels of cybervictimization, lower levels of avoiding online risks, and more discussions about media use with teachers in classes were predictors for students reporting a higher number of bias-based cybervictimization. Implications for prevention are discussed.
KW - bias-based cybervictimization
KW - multilevel zero-inflated Poisson model
KW - online hate
KW - socio-ecological model
KW - stigma-based bullying
UR - http://www.scopus.com/inward/record.url?scp=85104831907&partnerID=8YFLogxK
U2 - 10.1177/02724316211010335
DO - 10.1177/02724316211010335
M3 - Article
AN - SCOPUS:85104831907
SN - 0272-4316
VL - 42
SP - 1175
EP - 1203
JO - Journal of Early Adolescence
JF - Journal of Early Adolescence
IS - 9
ER -