000119868 001__ 119868 000119868 005__ 20240111111740.0 000119868 0247_ $$2doi$$a10.1016/j.chb.2022.107491 000119868 0248_ $$2sideral$$a130374 000119868 037__ $$aART-2023-130374 000119868 041__ $$aeng 000119868 100__ $$0(orcid)0000-0002-0100-1449$$aLozano Blasco, Raquel$$uUniversidad de Zaragoza 000119868 245__ $$aSex, age and cyber-victimization: A meta-analysis. 000119868 260__ $$c2023 000119868 5060_ $$aAccess copy available to the general public$$fUnrestricted 000119868 5203_ $$aCyberbulling is one of the biggest challenges the school faces. However, the lack of coherence between the data of the literature review makes it necessary to consider which elements are the ones that truly lead to the appearance of cyber-victimization. Through the meta-analysis methodology, it has been tried to clarify the role of sex (k = 41 samples, n = 176,658 adolescents) and age (k = 45 samples, n = 238,977 adolescents) in cyber-victimization. The effect size for the random model is small for both sex (r = 0.058; p < 0.00, 95% CI = 0.090; 3.45) and for age (r = 0.094; p = 0.004; 95% CI = 0.015; 2.910). Indications of significant differences in sex are observed, with women being the most affected. However, the results of the meta-regression have shown how the North American culture plays a key role in age as a moderating variable in relation to the rest of continental cultures. These results support the conclusion that age and sex represent variables that influence cyber-victimization. More specifically, there is a positive relationship between age and cybervictimization, so that the older the age, the higher the cybervictimization, but this is negatively mediated by the American culture. At the same time, some socio-contextual characteristics also seem to have effects on this aspect. Considering this, some important practical implications emerge related to the need to address the study, care and prevention of cyber-victimization as well as any form of violence that occurs inside and outside the classroom. 000119868 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ 000119868 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000119868 700__ $$0(orcid)0000-0001-8473-8114$$aQuilez Robres, Alberto$$uUniversidad de Zaragoza 000119868 700__ $$0(orcid)0000-0002-6083-8759$$aLatorre Cosculluela, Cecilia$$uUniversidad de Zaragoza 000119868 7102_ $$14001$$2215$$aUniversidad de Zaragoza$$bDpto. Ciencias de la Educación$$cÁrea Didáctica y Organiz. Esc. 000119868 7102_ $$14009$$2735$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicolog.Evolut.Educac 000119868 7102_ $$14001$$2625$$aUniversidad de Zaragoza$$bDpto. Ciencias de la Educación$$cÁrea Métod.Invest.Diag.Educac. 000119868 773__ $$g139, 107491 (2023), [10 pp.]$$pComput. hum. behav.$$tCOMPUTERS IN HUMAN BEHAVIOR$$x0747-5632 000119868 8564_ $$s3638852$$uhttps://zaguan.unizar.es/record/119868/files/texto_completo.pdf$$yVersión publicada 000119868 8564_ $$s2730191$$uhttps://zaguan.unizar.es/record/119868/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000119868 909CO $$ooai:zaguan.unizar.es:119868$$particulos$$pdriver 000119868 951__ $$a2024-01-11-11:01:14 000119868 980__ $$aARTICLE