Validating a Cyberbullying Victimization Measure Among Undergraduates

2021 ◽  
Vol 62 (1) ◽  
pp. 124-129
Author(s):  
Virginia L. Byrne
Keyword(s):  
Cyberbullying Victimization

Cyberbullying, student nurses’ ethical awareness and the Covid-19 pandemic

2021 ◽  
pp. 096973302110102
Author(s):  
Ka Young Kim ◽  
Jeong Sil Choi
Keyword(s):  
Clinical Practice ◽  
Nursing Students ◽  
Nursing Intervention ◽  
Cross Sectional Study ◽  
Hierarchical Regression ◽  
Clinical Practices ◽  
Ethical Awareness ◽  
Cross Sectional ◽  
Cyberbullying Victimization ◽  
Cyber Ethics

Background: The global COVID-19 pandemic has increased cyber communication, causing nursing students’ clinical practice to be held in cyberspace. Thus, it is essential to ensure that nursing students develop comprehensive cyber ethics awareness. Moreover, cyberbullying is becoming more widespread and is an increasingly relevant new concept. Objectives: This study aimed to assess the experiences of cyberbullying among nursing students during clinical practice and determine the effects of cyberbullying victimization and cyber environments on their cyber ethics awareness. Research design: Data for this descriptive cross-sectional study were collected in July 2020 using a self-reported questionnaire and analyzed using hierarchical regression. Participants and research context: The study included data from 291 nursing students with more than 6 months of clinical experience who were enrolled in two nursing universities in two cities in South Korea. Ethical considerations: This study was conducted after obtaining approval from the Institutional Review Board of G University. Written, informed consent was obtained from all participants. Results: Cyberbullying victimization experiences during clinical practice were few. The most common cyberbullies of work- and person-related cyberbullying were nurses and classmates, respectively. Discussion: Cyber ethics awareness was affected by cyber anonymity and the perceived seriousness of cyberbullying; cyberbullying related to clinical practices was a new factor that significantly affected cyber ethics awareness. Conclusions: Hospitals and nursing universities should develop a multi-dimensional, comprehensive, and effective nursing intervention education program to be integrated into the nursing curriculum to enhance cyber ethics awareness and reduce cyberbullying of nursing students.

The Predictability of Routine Activity Theory for Cyberbullying Victimization Among Children and Youth: Risk and Protective Factors

2021 ◽  
pp. 088626052199743
Author(s):  
Dana Aizenkot
Keyword(s):  
Protective Factors ◽  
Activity Theory ◽  
Educational Institution ◽  
Risk And Protective Factors ◽  
Routine Activity Theory ◽  
Children And Youth ◽  
Routine Activity ◽  
Effective Prevention ◽  
School Year ◽  
Cyberbullying Victimization

Cyberbullying has been pervading worldwide with negative implications for victims. Therefore, there is an urgent need to better understand this phenomenon and the factors that predict it, as the basis for effective prevention and intervention efforts. The current research aims to examine routine activity theory (RAT) as a theoretical framework predictive of cyberbullying victimization (CV) among children and youth. It was hypothesized that each of the RAT measures and the convergence of all measures predict CV. Data were collected from 5,719 primary, middle, and high school Israeli students (51.9% females) during the 2019–2020 school year via online questionnaires. Regression and moderation analyses were conducted to assess the predictability of CV from RAT measures, separately and converged. All RAT measures, separately and converged, predict CV. While off-line trust negatively predicts CV, other control variables, that is, online trust, educational institution phase, and gender, do not. Implications for school programs and guidelines for parents address the risk and protective factors of CV found. This study provides support for the predictability of CV from RAT and expands the knowledge of risk and protective factors predictive of CV.

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