TY - JOUR
T1 - Social Epidemiology of Early Adolescent Cyberbullying in the United States
AU - Nagata, Jason M.
AU - Trompeter, Nora
AU - Singh, Gurbinder
AU - Ganson, Kyle T.
AU - Testa, Alexander
AU - Jackson, Dylan B.
AU - Assari, Shervin
AU - Murray, Stuart B.
AU - Bibbins-domingo, Kirsten
AU - Baker, Fiona C.
N1 - Funding Information:
Funding: J.M.N. was supported by the American Heart Association Career Development Award ( CDA34760281 ) and the National Institutes of Health ( K08HL159350 ). S.B.M. was supported by the National Institutes of Health ( K23 MH115184 ). K.B.D. is supported by the National Institutes of Health ( K24DK103992 ). The ABCD Study was supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022 , U01DA041025 , U01DA041028 , U01DA041048 , U01DA041089 , U01DA041093 , U01DA041106 , U01DA041117 , U01DA041120 , U01DA041134 , U01DA041148 , U01DA041156 , U01DA041174 , U24DA041123 , and U24DA041147 . A full list of supporters is available at https://abcdstudy.org/federal-partners/ . A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal-investigators.html . ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in analysis or writing of this report.
Publisher Copyright:
© 2022 The Authors
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Objective: To determine the prevalence and sociodemographic correlates of cyberbullying victimization and perpetration among a racially, ethnically and socioeconomically diverse population-based sample of 11–12-year-old early adolescents. Methods: We analyzed cross-sectional data from the Adolescent Brain Cognitive Development (ABCD) Study (Year 2; N = 9429). Multiple logistic regression analyses were used to estimate associations between sociodemographic factors (sex, race/ethnicity, sexual orientation, country of birth, household income, parental education) and adolescent-reported cyberbullying victimization and perpetration. Results: In the overall sample, lifetime prevalence of cyberbullying victimization was 9.6%, with 65.8% occurring in the past 12 months, while lifetime prevalence of cyberbullying perpetration was 1.1%, with 59.8% occurring in the past 12 months. Boys reported higher odds of cyberbullying perpetration (AOR 1.71, 95% CI 1.01–2.92) but lower odds of cyberbullying victimization (AOR 0.80, 95% CI 0.68–0.94) than girls. Sexual minorities reported 2.83 higher odds of cyberbullying victimization (95% CI 1.69–4.75) than nonsexual minorities. Lower household income was associated with 1.64 (95% CI 1.34–2.00) higher odds of cyberbullying victimization than higher household income, however household income was not associated with cyberbullying perpetration. Total screen time, particularly on the internet and social media, was associated with both cyberbullying victimization and perpetration. Conclusions: Nearly one in 10 early adolescents reported cyberbullying victimization. Pediatricians, parents, teachers, and online platforms can provide education to support victims and prevent perpetration for early adolescents at the highest risk of cyberbullying.
AB - Objective: To determine the prevalence and sociodemographic correlates of cyberbullying victimization and perpetration among a racially, ethnically and socioeconomically diverse population-based sample of 11–12-year-old early adolescents. Methods: We analyzed cross-sectional data from the Adolescent Brain Cognitive Development (ABCD) Study (Year 2; N = 9429). Multiple logistic regression analyses were used to estimate associations between sociodemographic factors (sex, race/ethnicity, sexual orientation, country of birth, household income, parental education) and adolescent-reported cyberbullying victimization and perpetration. Results: In the overall sample, lifetime prevalence of cyberbullying victimization was 9.6%, with 65.8% occurring in the past 12 months, while lifetime prevalence of cyberbullying perpetration was 1.1%, with 59.8% occurring in the past 12 months. Boys reported higher odds of cyberbullying perpetration (AOR 1.71, 95% CI 1.01–2.92) but lower odds of cyberbullying victimization (AOR 0.80, 95% CI 0.68–0.94) than girls. Sexual minorities reported 2.83 higher odds of cyberbullying victimization (95% CI 1.69–4.75) than nonsexual minorities. Lower household income was associated with 1.64 (95% CI 1.34–2.00) higher odds of cyberbullying victimization than higher household income, however household income was not associated with cyberbullying perpetration. Total screen time, particularly on the internet and social media, was associated with both cyberbullying victimization and perpetration. Conclusions: Nearly one in 10 early adolescents reported cyberbullying victimization. Pediatricians, parents, teachers, and online platforms can provide education to support victims and prevent perpetration for early adolescents at the highest risk of cyberbullying.
UR - http://www.scopus.com/inward/record.url?scp=85136752999&partnerID=8YFLogxK
U2 - 10.1016/j.acap.2022.07.003
DO - 10.1016/j.acap.2022.07.003
M3 - Article
SN - 1876-2859
VL - 22
SP - 1287
EP - 1293
JO - Academic Pediatrics
JF - Academic Pediatrics
IS - 8
ER -