Developing a College Students’ Cyberbullying Scale

Abbreviations

BGCM: Barlett and Gentile Cyberbullying Model; F2F: Face- to-Face; WHO: World Health Organization; KMO: Kaiser- Meyer-Olkin.

Introduction

The Internet has become a ubiquitous communication tool, with violent extremists using it to socialize, learn, and become activists. Internet 2.0 technology has transformed social media platforms like Twitter and Facebook, transforming daily activities like education, business, entertainment, and e-government. By 2021, these networks will have over 3.02 billion active users globally. The Internet and social media raise issues like cyberbullying due to misunderstandings about freedom of speech. It is critical to detect cyberbullying without victim involvement [1]. Contemporary youth rely heavily on social networking tools to maintain their social circles, potentially making them vulnerable to cyberbullying and associated victimization [2].

Bullying, dating back to the 1530s, involves a bully or intimidator abusing a victim through physical, verbal, or other means to gain a sense of superiority and power. Prevention and statistics are crucial in addressing this issue [3]. Since the 1980s, schools have grappled with bullying as a significant issue, often ignoring or denying it. Since then, social scientists, educators, teachers, and parents have worked together to raise awareness and find ways to reduce and prevent it. A research program on school bullying has developed through four phases: origins in western Scandinavia, spreading ideas to other countries, establishing an international research program, and the advent of cyberbullying. Cyberbullying has revitalized the bullying research program by bringing in a new mix of disciplines and researchers, leading to increased publications and resources for anti-bullying programs [4].

Amanda Todd and Rehtaeh Parsons’ high-profile cases highlight the severe consequences of cyberbullying. In 2012, Todd, a 15-year-old Canadian, took her own life due to cyberbullying. She received pressure from an anonymous individual to send explicit images of herself to her school students. In 2014, authorities arrested a 35-year-old Dutch citizen on charges of extortion, Internet luring, criminal harassment, and child pornography. These events caused Todd to suffer anxiety, depression, and panic attacks, culminating in several attempts to harm herself. Rehtaeh Parsons, a teen from Nova Scotia, committed suicide in 2013 following her rape in 2011. The incident was considered “he said, she said” by police, leading to no further action. One individual pleaded guilty and received a conditional discharge with 12 months of probation in 2014. These incidents highlight the harm of cyberbullying [2].

Cyberbullying, a growing concern in the 21st century, involves sending intimidating messages online, allowing perpetrators to escalate abuse and traumatize victims. The internet has connected youths, leading to an increase in students using the internet at home or in school. Cyberbullying can worsen depression and post-traumatic stress disorder symptoms in young inpatients, especially those with a history of abuse. It is more pernicious than traditional bullying due to its viral and persistent nature. Victims often feel isolated and helpless, leading to feelings of depression and anxiety. Cyberbullying is more dangerous because of its anonymity, repetition, and location, which make it difficult to detect. Altering the university and school climate and providing psychological support are crucial for behavioral change and reducing strain. Evidence also suggests that cyberbullying among college students and school-age children is associated with problem behaviors and other adverse school performance constructs. Consequently, educators have developed and implemented numerous school-based programs aimed at reducing cyberbullying perpetration and victimization [5].

Cyberbullying has become a significant social and political issue, prompting governments and educational institutions to focus on combating this issue through all means, including legal, social, health, and political means. Cyberbullying is more dangerous because of its anonymity, repetition, and location, which make it difficult to detect. Altering the university and school climate and providing psychological support are crucial for behavioral change and reducing strain [2].

Cyberbullying: The Definition

Patchin and Hinduja’s definition of cyberbullying is “willful and repeated harm inflicted through the use of computers, cell phones, and other electronic devices” [6] (p.11). “Willful” denotes an unwavering commitment to a particular activity, while “repetition” describes the regular use of electronic devices to transmit and consume harmful content. Bullying extends beyond campus and into the home, posing a threat to safety due to technological advancements [6]. Cyberbullying, often perpetrated through cellular phones and internet-enabled computers, presents a unique balance of power due to the perceived anonymity of the perpetrator, the lack of immediate victim response observation, and the potential for an infinite audience, making it a prevalent issue with little parental or school community guardianship [5]. Cyberbullying is characterized by anonymity, rapid dissemination of information, a lack of face-to-face confrontation, and a lack of parental control. Only 40–50% of victims know the perpetrator’s identity, leading to frustration and helplessness. Cyberbullying often reaches a wider audience, making it difficult for victims to remove content. Lack of visual signals and written communication can also contribute to cyberbullying. High levels of parental supervision and support can help prevent children from participating in bullying [7].

Cyberbullying is defined as an aggressive, intentional act carried out by a group or individual using electronic forms of contact repeatedly and over time against a victim who cannot easily defend themselves. It is a form of willful and repeated harm inflicted through the use of computers, cell phones, and other electronic devices. The definitions highlight common elements such as the use of electronic media, intent to harm, repetition, and power imbalance between the bully and the victim. These definitions are frequently cited in academic literature and practical guidelines addressing cyberbullying. The most cited definitions are from Smith PK, Patchin JW, Tokunaga RS, Menesini E, Willard N [8, 9, 10, 11, 12].

Theoretical Framework

Cyberbullying is a complex issue that has been studied by various researchers from psychology, sociology, and communication studies. Some of the most influential theories include the Social Learning Theory, General Strain Theory, Routine Activity Theory, Anonymity and Deindividuation Theory, Self-Control Theory, Social Identity Theory, and The Theory of Planned Behavior. These theories provide a comprehensive understanding of cyberbullying, encompassing individual psychological factors, social influences, environmental conditions, and the unique characteristics of online interactions. Social Learning Theory suggests that individuals learn behaviors through observation, imitation, and modeling, The Barlett and Gentile Cyberbullying Model (BGCM) is a learning- based theory that posits the importance of positive cyberbullying attitudes predicting subsequent cyberbullying perpetration. Furthermore, the tenants of the BGCM state that cyberbullying attitude are likely to form when the online aggressor believes that the online environment allows individuals of all physical sizes to harm others and they are perceived as anonymous [13]. General Strain Theory suggests that individuals experiencing stress or strain are more likely to engage in deviant behaviors, including cyberbullying. According to General Strain Theory, youth who experience strain are more likely to engage in both traditional and non-traditional forms of bullying [14]. Patchin and Hinduja [14] found that strain in youth increases cyberbullying, but anger or frustration doesn’t mediate the relationship, unlike traditional bullying experiences. Jang [15] investigated the relationship between traditional bullying victimization and cyberbullying engagement, positing that offline bullying victimization positively correlates with cyberbullying. Navarro and Jasinski [16] found that suitability and availability significantly correlate with cyberbullying experiences among youth. Routine Activity Theory focuses on the circumstances that make cyberbullying more likely to occur, such as the availability of targets, lack of capable guardianship, and the presence of motivated offenders. Routine Activities Theory. They found that 61.5% of youth use the internet daily, and 90% use it weekly. Targeting social networking sites increased, with cyberbullying emerging as the most prevalent form. Parents used browser history, website filters, and software to protect their children.

Over the years, there has been a significant increase in studies on cyberbullying, with a total of 195 papers published in 2018. However, there is a lack of consensus among the findings due to common limitations in the concept’s definition and operationalization. The National Crime Victimization Survey: School Crime Supplement (NCVS:SCS) BJS [17] has expanded the subject to include Internet, instant messaging, and text messaging but has not included cyberspace. As awareness of cyberbullying grows, so does the desire to capture this phenomenon more accurately. Measurement tools for cyberbullying frequently fail to accurately reflect technological advancements, and clear estimates of reliability and validity are often lacking. Additionally, study samples differ widely, and most studies are cross-sectional, making it difficult to determine causality and the direction of the relationship between variables. Previous studies on cyberbullying have limitations, including the definition, conceptualization, and operationalization of the concept, as well as the validity and reliability of the instruments used to measure it. Only about half of the instruments were used for “cyberbullying,” and there are few reports on the instruments’ reliability and validity. Additionally, data should be collected from sources such as parents, peers, and teachers [5]. Olweus and Limber [18] report that prevalence estimates vary from 3% to 40%, likely due to differences in measurement Figure 1.

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Cyberbullying’s psychological variables and processes require further research, particularly for adolescent samples. The Barlett Gentile Cyberbullying Model (BGCM)

is the only validated theory to predict cyberbullying perpetration. Applying the BGCM to adolescents presents both challenges and opportunities for future research and intervention development [19]. The integration of cyber-racism perpetration into the broader cyberbullying context, highlighting similarities and differences between the two types of online behavior. It focuses on a cyber- racism model that emphasizes anonymity perceptions as a key factor in causing cyber-racism, including online disinhibition, deindividuation, group polarization, and stereotypes. The review concludes with a discussion of theoretical and intervention implications, aiming to spark further research on cyber-racism and cyberbullying [20]. Cyberbullying significantly impacts students, causing reduced concentration, school avoidance, increased absences, isolation, and negative school climate perceptions, particularly affecting girls. Perpetrators of cyberbullying cause adverse health effects, including increased depression, anxiety, substance use, and comorbidities. Understanding risk factors is crucial for preventing morbidity and mortality [21]. The study examines the impact of strain variables on cyberbullying victimization among college students in Qatar. It found that a significant percentage of students were exposed to bullying, with gender differences and mean differences. The findings suggest that cyberbullying victimization could lead to delinquency and strains [22].

In their systematic review and meta-analysis of interventions to decrease cyberbullying perpetration and victimization [5]. analyzed programming to reduce cyberbullying perpetration and victimization, dividing it into seven categories: skill-building, curricula and prepared materials, psychoeducation, multimedia materials, training, school climate or policy, and group or individual targeted responses. Nearly 80% of programs included some form of skill-building, with many using curricula, other prepackaged materials, or multimedia materials. Skill-building focuses on teaching students to develop competencies they can apply independently in real-time situations, particularly when adults or peers are absent. Curricula and prepared materials refer to uniform content that guides students through the curriculum. Programs targeting cyberbullying behavior were more effective in reducing cyberbullying compared to general violence prevention programs. The average effects of most bullying prevention program meta-analyses ranged from 0.15 to 0.20, a value that is lower than the average effect of incorporating a cyberbullying component in this meta-analysis (0.25). We need future research to confirm whether incorporating a cyberbullying component within the prevention program can reduce traditional bullying. The study also found that only 18% of studies met the highest World Health Organization (WHO) rating, and 44% did not meet WWC standards. Schools must also carefully consider the availability of resources for program implementation [5].

Al-badayneh, et al. found that 44.5% of students said they had been bullied, and 9.6% said they had been the target of cyberbullying and 5% were cyberbullying. Face- to-face (F2F) bullying was more prevalent in males, who were both victims and bullies. According to the findings, bullying differed significantly between males and females. Compared to women, men are more likely to be bullied [23]. A study on expats in Qatar found that 10.8% reported cyberbullying victimization, with 46% being male and 54% being female. Victims came from intact families (62.4%) and had a lack of a father during childhood (31.7%). About a third of victims found it easy to talk to their father when needed. Additionally, 50% of victims were victims of face- to-face bullying [24].

The Purpose of the Study

This research is an attempt to narrow the gap in cyberbullying measurement and aims to develop a cyberbullying scale applicable to youth in Jordan that can be extended to Arab States. We can apply and test this scale, which offers insights for formulating policies and understanding the implications for law and security. The scale can identify conceptual constructs of cyberbullying, aid policy formation, and provide legal and security implications for youth prevention.

Methodology

Scale development is a complex and time-consuming process that provides accurate and valid measures of constructs, such as abstract and complex constructs like self- perception. These instruments are often difficult to create due to their complexity and the need for validation [4].

Discussion

Cyberbullying, a form of violence and crime involving new technologies, requires a comprehensive understanding from a criminal law perspective [24]. Cyberbullying has become a severe social, health and legal problem in modern societies. We need a reliable tool to measure cyberbullying and understand its causes and effects. We should update and approve youth policies based on universal human values to address the deficiency in research-based education and development strategies.

The research aims to develop a youth cyberbullying scale for Jordan that can be generalized and applicable for Arab States, providing insights for policy formulation and understanding law and security implications. The findings revealed that six factors, comprising the 37 items of the scale, collectively accounted for 76.6% of the variance in youth cyberbullying. The first factor, labeled “self and bystanders cyberbullying perpetration” (25 items), accounted for 67.5% of the variance; the second factor (9 items), “self and bystanders cyberbullying victimization,” was responsible for 4.7%; and the third factor (5 items), “vicarious and group perpetration and victimization cyberbullying,” contributed 4.4% of the variance. Findings showed Looking at Table 10 and Figure 3, the study found big differences between cyberbullying rates for boys and girls (F = 4.726, ± ≤0.000). Boys were more likely to be cyberbullied than girls (mean = 35.9 vs. 32.7), with a range of 1.6 to 1.4.

Conclusion

The study presents a reliable scale for measuring youth cyberbullying, suitable for Arab cultures and countries. It suggests younger students are suitable for prevention due to potential crime involvement. The scale is valid and comprehensive. To address cyberbullying, we need a research-based policy that focuses on victim experiences, prevention strategies, online communication education, ensures effective treatment, and balances technological advancements.