Cyberbullying: causes, effects, and prevention strategies

Testing Assumptions About Cyberbullying: Perceived Distress Associated With Acts of Conventional and Cyberbullying

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Cyber bullying

Bauman & Newman (2012), in light of the considerable attention that cyber bullying has received in the recent past and the assumptions the phenomenon had received, undertook to test assumptions about cyber bullying. Cyber bullying in essence has much to do with using the knowledge of information and communication technology to harm other people's social status, relationships, and reputation. Conspiracy that clouds cyber bullying continues considerable attention from popular media. Protracted legal tussles have been witnessed in instances when reports of isolated cases have been made. Bauman & Newman (2012), sought to establish whether experts speculation that the potential from cyber bullying was in deed greater than the dangers posed by conventional bullying. The fact that this assumption had not been empirically informed their resolve to conduct this study.

Five hundred and eighty eight students from Southern University participated in this study. Seventy six percent of the participants were female gender. The participants' ages ranged from 17 to 25. Their mean age was 19.8. About 45% of the participants came from the university vicinity. Ten per cent of them came from elsewhere while 35% were natives of other U.S. states. Nine percent of the participants had other national origins. Sixty-six percent of the participants were white, 7% African-American/Black, 17% Latino, 4% Native Americans, and 1% Pacific Islanders. Five percent of the participants indicated they belonged to "other" ethnicity. Participants were predominantly from psychology classes. They were recruited via online subject pool system.

The system was settled on because it provided several options for fulfilling students' course research requisites. The word bullying was never mentioned until the debriefing as the survey was advertised as a study of social attitudes. The online survey lasted for at least 15 minutes. Participants' informed consent was sought before the survey commenced. Procedures and measures were approved by the Institutional Review Board at the researcher's university. Questionnaires used in the survey were developed by the authors of the study. Items in the questionnaire captured a broad range of behaviors that represented familiar forms of bullying in 17- to 25-year-olds that could be delivered through conventionally or through the cyber. Final scale had eight pairs of items that described an incident in which a participant was bullied. The eight items also addressed incidences of conventional bullying.

The items also addressed parallel scenarios in which the same bullying behavior was perpetuated through communication technology. Response options ranged from 1 to 7. To assess historical victimization, participants were asked whether they were bullied during junior high, high school, and college by choosing from never, occasionally, or frequently. One participant reported having been bullied at college where as 16% of the participants indicated that they were victimized at junior and high school. Nineteen per cent of the participants reported having been bullied only in junior high school. Five percent were victimized in high school. Gender differences did not feature in victimization histories. Analysis was done using Predictive Analysis Software 2010, PASW 19.0.

The degree of freedom was 598 while "p" was put at .21. Because the rate of missingness for all variables and the samples was less than 1% and the sample was relatively large, missing variables was not imputed. Instead, listwise deletion was used for all the analysis. Missing data were considered MCAR (Missing Completely at Random).

The confirmatory Factor Analysis that was used to test the fit of the data was found to be uniformly poor. This was a pointer that the two factor model wasn't a good fit fir the data. Principal components analysis with 16 items of the questionnaire was subsequently conducted to explore the underlying structure. Oblique rotation was used in the analysis to counter the poor fit of the confirmatory factor analysis model. It allowed the components to correlate with one another. T-tests with each of the eight pairs of the items were conducted to examine the perceived distress associated with cyber vs. conventional bullying.

There was a significant difference between the paired items for all pairs except for "teachers pet" and "naked." Mean score of the conventional items was significantly higher among "cartoon," "exclusion," and "slut." Male and female participants' distress scores on subscales were significant on all subscales. Female participants had significantly higher distress scores than males. Victimization was significantly weakly correlated with general victimization scale (r=.10, p