Your browser doesn't support javascript.
loading
Perceived COVID-19 stress and online aggression among Chinese first-year college students: a moderated mediation model.
Guo, Lingjing; Xu, Liyuan; Yang, Qiang.
Afiliação
  • Guo L; Center of Mental Health Education and Research, Preschool Education Research Center, School of Psychology, School of Education, Jiangxi Normal University, Nanchang, China.
  • Xu L; Mental Health Education Center, Chengdu University, Chengdu, China.
  • Yang Q; Mental Health Education and Counselling Center, Department of Student Affairs Management, Beijing Sport University, Beijing, China.
Front Psychiatry ; 14: 1221379, 2023.
Article em En | MEDLINE | ID: mdl-37547220
ABSTRACT

Purpose:

Few studies have explored factors that may account for potential mechanisms between perceived coronavirus disease 2019 (COVID-19) stress and online aggression. The current study examined a moderated mediation model with anxiety as a mediator and perceived anonymity as a moderator.

Methods:

A cross-sectional study was conducted. 3,069 participants across China completed scales assessing perceived COVID-19 stress, anxiety, online aggression, and perceived anonymity.

Results:

Perceived COVID-19 stress was positively related to online aggression. The association between perceived COVID-19 stress and online aggression was mediated by anxiety. Besides, the relationship between perceived COVID-19 stress and online aggression, as well as the relationship between anxiety and online aggression were moderated by perceived anonymity.

Conclusion:

This study explains the possible potential mechanisms for reducing online aggression in the context of COVID-19. In order to intervene in online aggression, psychological strategies are supposed to be drawn to reduce anxiety and perceived anonymity.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article