» Articles » PMID: 36388377

Cyberbullying Definitions and Measurements in Children and Adolescents: Summarizing 20 Years of Global Efforts

Overview
Specialty Public Health
Date 2022 Nov 17
PMID 36388377
Authors
Affiliations
Soon will be listed here.
Abstract

Despite numerous instruments existing to assist in the measurement of specific cyberbullying behaviors or cyberbullying in general, it is still unclear their purpose, corresponding scenarios, and their effectiveness. This study, therefore, aims to provide a comprehensive review of academic efforts on cyberbullying definitions, measurements, and their effectiveness in children and adolescents in the past two decades. A systematic review was performed using ASReview, an open source machine learning systematic review system. Three bibliographic citation databases, including Web of Science core collection, PubMed, and EBSCO were adopted for all relevant literature published from January 2001 to August 2021. In total, twenty-five studies, mentioning seventeen cyberbullying measurement scales, met the study collection criteria. The results found that most failed to provide a clear definition of cyberbullying, often providing unclear and inconsistent descriptions for the youth. Similarly, studies found it difficult to clearly reflect the three key elements of bullying, namely: harmfulness, repetitiveness, and the power imbalance between bullies and victims. With regard to cyberbullying types, most presented two or three categories, including victimization, perpetration, and bystanding, while some suggested four types based on the nature of the cyberbullying behavior, including written or verbal, visual or sexual, character impersonation, and exclusion. If characteristics are considered, cyberbullying becomes more specific with multiple categories being proposed, including flaming (or roasting), harassment, denigration, defamation, outing, jokes, online sexual harassment, and cyberstalking. With regard to measurements, many scales have been proposed and frequently refined to capture specific cyberbullying experience of the youth. This study emphasizes the value and importance of providing clear cyberbullying definitions and helps scholars in youth cyberbullying choose appropriate measurement scales.

Citing Articles

Cross-sectional study of cybervictimisation and non-suicidal self-injury among college students in China: a chain mediation effect of emotion dysregulation and social exclusion.

Liao X, Xine L, Ni J BMJ Open. 2025; 15(1):e087346.

PMID: 39855669 PMC: 11758688. DOI: 10.1136/bmjopen-2024-087346.


Collisions and Perceptions of Cyberbullying: Comparison of Intergenerational Experiences.

Soldatova G, Chigarkova S, Rasskazova E Int J Environ Res Public Health. 2024; 21(9).

PMID: 39338031 PMC: 11431141. DOI: 10.3390/ijerph21091148.


Digital Dilemma of Cyberbullying Victimization among High School Students: Prevalence, Risk Factors, and Associations with Stress and Mental Well-Being.

Ramadan O, Alruwaili M, Alruwaili A, Elsharkawy N, Abdelaziz E, El Badawy Ezzat R Children (Basel). 2024; 11(6).

PMID: 38929214 PMC: 11202024. DOI: 10.3390/children11060634.


Tunneling, cognitive load and time orientation and their relations with dietary behavior of people experiencing financial scarcity - an AI-assisted scoping review elaborating on scarcity theory.

van der Veer A, Madern T, van Lenthe F Int J Behav Nutr Phys Act. 2024; 21(1):26.

PMID: 38439067 PMC: 10910771. DOI: 10.1186/s12966-024-01576-9.


Artificial intelligence in systematic reviews: promising when appropriately used.

van Dijk S, Brusse-Keizer M, Bucsan C, van der Palen J, Doggen C, Lenferink A BMJ Open. 2023; 13(7):e072254.

PMID: 37419641 PMC: 10335470. DOI: 10.1136/bmjopen-2023-072254.

References
1.
Zhang W, Yuan H, Zhu C, Chen Q, Evans R . Does Citizen Engagement With Government Social Media Accounts Differ During the Different Stages of Public Health Crises? An Empirical Examination of the COVID-19 Pandemic. Front Public Health. 2022; 10:807459. PMC: 9237959. DOI: 10.3389/fpubh.2022.807459. View

2.
Kowalski R, Giumetti G, Schroeder A, Lattanner M . Bullying in the digital age: a critical review and meta-analysis of cyberbullying research among youth. Psychol Bull. 2014; 140(4):1073-137. DOI: 10.1037/a0035618. View

3.
Wang J, Zhou Y, Zhang W, Evans R, Zhu C . Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data. J Med Internet Res. 2020; 22(11):e22152. PMC: 7695542. DOI: 10.2196/22152. View

4.
Zhu C, Huang S, Evans R, Zhang W . Cyberbullying Among Adolescents and Children: A Comprehensive Review of the Global Situation, Risk Factors, and Preventive Measures. Front Public Health. 2021; 9:634909. PMC: 8006937. DOI: 10.3389/fpubh.2021.634909. View

5.
Palladino B, Nocentini A, Menesini E . Psychometric properties of the Florence CyberBullying-CyberVictimization Scales. Cyberpsychol Behav Soc Netw. 2015; 18(2):112-9. DOI: 10.1089/cyber.2014.0366. View