As technologies rapidly grow and usage of smartphone and social media increases, the number of cyberbullying victims among adolescents is keep rising. Being the victims of cyberbullying during adolescence cause deleterious impacts as the cyberbullying ...
As technologies rapidly grow and usage of smartphone and social media increases, the number of cyberbullying victims among adolescents is keep rising. Being the victims of cyberbullying during adolescence cause deleterious impacts as the cyberbullying victimization can be carried out 24 hours a day regardless of time or place. Although extensive research on cyberbullying has been conducted over the past decade, there are only few standardized measurement tools in South Korea to measure cyberbullying victimization in a way that reflects the rapid changes of cyberbullying. Therefore, this study aims to develop and validate a measurement of cyberbullying victimization that has secured validity and reliability through the use of mixed methods. In order to develop a Korean cyberbullying victimization scale, preliminary questions were drawn through development of items and qualitative surveys in the first year, and final items were drawn through delphi methods and preliminary indicators in the second year.
During the first year, to provide an overview of the existing scales and to suggest ways to standardize the cyberbullying measurement, the study conducted a systematic review of the cyberbullying victimization scales, perpetration scales, and scales of both. This study analyzed sixty-four international studies on cyberbullying measurements using the following categories: general characteristics, definition of cyberbullying, study sample characteristics, sample size, type of device or social media, time frame, survey type, item-pooling method, subscales, reliability, and validity. All studies were published from 2002 to 2020 and the studies were conducted in 17 different countries, Out of 17 different devices or social media platforms, mobile phones were included the most, followed by e-mails and text messages. Furthermore, only 15 studies followed the recommended guidelines, either fully or partially, when developing their scale. Thirty instruments out of the total 64 instruments had subscales. More specifically, eight instruments (12.5%) consisted of two subscales. Thirty-three instruments performed factor analyses, including a confirmatory factor analysis (CFA) or exploratory factor analysis (EFA); 51.6% (16 instruments for CFA, six instruments for EFA, and 11 instruments for both CFA and EFA).
The item pools were generated through concept mapping approach with three topics: definition, protective factors, and impacts of cyberbullying victimization. This method is consisted of 6 steps: (1) preparation, (2) generation, (3) structuring, (4) representation, (5) interpretation, and (6) utilization. Following these 6 steps, participants generated a large set of statements on cyberbullying victimization, each then sorted these statements into piles based on their perceived similarity and rated them. The collected data was analyzed through concept system software and was represented by visualized cluster map. First, concept mapping revealed five major definitions of cyberbullying victimization: bullying, abusive language and behavior, invasion of privacy, sexual violence and pornography, and hacking and threatening. For the protective factors for cyberbullying victimization among Korean adolescents, concept mapping revealed six major factors: supportive relationship, school’s interest in cyberbullying, personal traits, reporting and monitoring system, education and help-seeking and personal traits in online behavior, Finally, concept mapping revealed six major impacts of cyberbullying victimization among Korean male adolescents: internalizing problems, externalizing problems, school and peer problems, online problems, seeking social support, and avoidance.
In order to add more ideas and opinions were added to the cyberbullying victimization item pools, five experts including school social worker, adolescent counselors, and other professionals were recruited for the focus group interview. During the interview, experts discussed on the topic of “what is the impacts of cyberbullying victimization?” Next, seventeen panelists including experts in the child and adolescent welfare, were invited to participate in the Delphi survey. These panelists reviewed and rated the generated statements based on the three criteria: validity, importance, feasibility (or practicality). Based on the results of the two rounds of rating and the comments received, the items were revised.
Revised items were then evaluated on a pilot-study and proceeded to validation procedure. To figure out the number of subscales within the cyberbullying victimization scale, the exploratory factor analysis was performed using the varimax rotation method. Factor 1 consists of five items (e.g., item #5, #6, #7, #8, #14) which include experience about verbal attack through posts and replies, and about being exposed to sexual contents. Thus, Factor 1 was named as “verbal and sexual attack.” Factor 2 is composed of five items (e.g., item #4, #10, #11, #12, #15) and deal with the leakage of personal information, and being excluded or kicked out from online spaces by a group of people and/or friends. As a result, the Factor 2 was nominated as “intrusiveness.” Factor 3 includes four items (e.g., item #1, #2, #3, #16) which target at the extortion of online money, game item, mobile data, and receiving verbal threats about me and my family through online messages and/or chatting. Thus, this subscale was named after “verbal and financial threat.” The overall reliability of the cyberbullying victimization scale (α = .80), and the respective subscales had moderate and acceptable range of reliability. The model fit indicated a ‘good model fit‘. The cyberbullying victimization scale was all significantly correlated with the external criteria including gaming addiction, smartphone addiction, self-efficacy, stress, depression, and self-esteem.