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. Author manuscript; available in PMC: 2017 Sep 27.
Published in final edited form as: Coll Stud J. 2016 Spring;50(2):278–287.

CYBERBULLYING BEHAVIORS AMONG FEMALE COLLEGE STUDENTS: WITNESSING, PERPETRATION, AND VICTIMIZATION

Ellen M Selkie 1, Rajitha Kota 2, Megan Moreno 3
PMCID: PMC5615856  NIHMSID: NIHMS850163  PMID: 28966413

Abstract

Problem

Cyberbullying is common among adolescents, and emerging studies also describe this phenomenon in college students. Less is known about specific cyberbullying behaviors and roles in cyberbullying incidents experienced by college females.

Methods

249 female students from 4 colleges completed online surveys assessing involvement in 11 specific cyberbullying behaviors in any of the following roles: bully, victim, or witness.

Results

Nearly half (n = 110, 44.2%) of participants had experienced cyberbullying in college as a bully, victim, witness, or combination of the three. The most commonly witnessed behaviors included “posting degrading comments or hate speech” and “posting explicit or unwanted pictures.” Over one third of the witnesses were classified as bystanders who purely observed cyberbullying without participating.

Conclusions

Cyberbullying is common among college women, with more people witnessing behaviors than participating. Given the large proportion of witnesses, mobilizing bystanders is a potential target for cyberbullying in the college population.

Introduction

Bullying is a serious public health problem that has been linked to physical and mental health problems in both aggressors and targets (Gini & Pozzoli, 2009; Tokunaga, 2010). Today, the internet and social media have provided new avenues through which children, adolescents, and young adults can hurt their peers. These behaviors are commonly known as cyberbullying, internet harassment, or electronic harassment (Tokunaga, 2010). College students remain an understudied population regarding cyberbullying. Prevalence of cyberbullying perpetration in college has been estimated to be between 8.6% and 22.5% (Dilmac, 2009; MacDonald & Roberts-Pittman, 2010) while prevalence rates of victimization range from 8.6% to 55.3% (Dilmac, 2009; Schenk & Fremouw, 2012). College students are an important population on which to focus regarding the issue of cyberbullying because this period of older adolescence can be formative for habits that persist into young adulthood. In college, bullies may use more subtle attacks that are meant to exclude or leverage power over others rather than being overtly aggressive (Kota, Schoohs, Benson, & Moreno, 2014). Bullying behaviors that attack college students’ identities may have a considerable impact because this period is a unique time for identity formation that can be stressful and vulnerable (Orlofsky, 1977).

Female undergraduates are a population of interest regarding cyberbullying in college students. First, a greater proportion of females (71%) compared to males (62%) use social networking sites, among all internet users (Duggan & Brenner, 2013). Cyberbullies commonly use social network sites to bully, which is important because use of these websites among college students is almost universal (Smith, Rainie, & Zickuhr, 2011). Second, studies suggest that females are more often involved in cyberbullying both as a victim and as a bully (Dehue, Bolman, & Vollink, 2008; Haque & Khatibi, 2013; Jackson et al., 2009; Mesch, 2009; Slonje & Smith, 2008; Vandebosch & Van Cleemput, 2008). These findings are also consistent with the types of indirect bullying often seen between girls in traditional bullying scenarios. Specifically, relational aggression among females often takes the form of gossiping or spreading rumors, friendship betrayals, exclusion, and other manipulative behaviors that affect relationships, and many of these behaviors can be easily facilitated through cyberbullying (Raskauskas & Stoltz, 2007; Viljoen, O’Neill, & Sidhu, 2005).

In traditional bullying, it is understood that behaviors can have negative impacts on victims and bullies as well as bystanders. Bystanders, those who witness bullying without actively participating, are a population of interest as they can contribute to social norms regarding bullying by passively allowing such aggression to occur (Christina Salmivalli, 2010). Bullies may see this inaction as an indirect approval of this behavior and continue to victimize others (Twemlow, Fonagy, & Sacco, 2004). Conversely, motivated bystanders can also intervene when bullying is observed and in so doing, decrease the frequency of bullying behavior (C. Salmivalli, Voeten, & Poskiparta, 2011). The prevalence of bystanders in the electronic arena of bullying may be increased compared to traditional bullying given the reach of the Internet; however, prevalence of witnessing online aggression is poorly understood.

Given that college students have a high prevalence of technology use, it is conceivable that they will witness cyberbullying behaviors as much as, if not more than, other age groups, with females having greater exposure than males. It remains unclear how commonly specific cyberbullying behaviors are experienced by victims, bullies and bystanders. While some studies have measured college students’ awareness of cyberbullying (MacDonald & Roberts-Pittman, 2010), to our knowledge no studies have examined the prevalence of witnessing specific cyberbullying behaviors in which college students engage. Knowing which cyberbullying behaviors are common in a college population could aid in development of a college-specific screening tool. Therefore, the first aim of our study was to determine the prevalence of cyberbullying witnessing among female college students in the context of specific cyberbullying behaviors. Our secondary aim was to determine the prevalence of other roles (bully, victim) that female college students play in college cyberbullying.

Methods

Data for this study were collected between October and November 2012, and the protocol was approved by the four relevant university Institutional Review Boards.

Setting and Subjects

We surveyed female college students from introductory undergraduate communications, biology, nursing, and psychology courses at four different universities. To be included in the study analysis, students had to report their sex as female and age as between 18 and 23 years. We distributed flyers to a total of 662 students and 334 participants completed the survey (response rate=50.5%). A total of 249 surveys met criteria to be included in the analysis.

Data Collection and Recruitment

Study personnel went to each class and handed out paper flyers with a link to the online survey. Students were also sent several emails reminding them to take the survey from course instructors. The survey was administered online using a university sponsored Catalyst WebQ online survey engine. Survey respondents were provided a $5 Starbucks gift card as compensation. Informed consent information was provided on the first page of the survey.

Measures

Demographics

We collected age, race/ethnicity, sexual orientation, relationship status, and major in school from students (Table 1).

Table 1.

Demographics of sample of female college students from four universities (n=249).

All Participants N (%) No Cyberbullying Experience n (%) Cyberbullying Experience n (%)
Sexual orientation
 Heterosexual 240 (96.4) 137 (57.1) 103 (42.9)
 Homosexual 4 (1.61) 0 (0) 4 (100)
 Bisexual 5 (2) 2 (40) 3 (60)
Year in school
 Freshman 48 (19.3) 31 (64.6) 17 (35.4)
 Sophomore 68 (27.3) 35 (51.5) 33 (48.5)
 Junior 76 (30.5) 50 (65.8) 26 (34.2)
 Senior 57 (22.9) 23 (40.4) 34 (59.6)
Race
 Caucasian 212 (85.1) 117 (55.2) 95 (44.8)
 Non Caucasian 37 (14.9) 22 (59.5) 15 (40.5)
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Survey Development

The cyberbullying field lacks a standardized, operational definition of the phenomenon. Thus, we developed survey items using focus groups. In a previous study of focus groups (Kota et al., 2014), college students described typical types of and examples of cyberbullying. Data from this study were used to develop a specific set of 11 example behaviors that represented cyberbullying in college. This 11-item survey was then pilot tested with college students to ensure completeness and comprehension. This instrument was then used in this study.

Cyberbullying Measures

In order to characterize the nature of cyberbullying among college students, we asked students to respond “Yes”, “No”, or “Don’t Know” to the question “Have you ever witnessed, experienced, or participated in cyberbullying in college?” Participants who answered “No” skipped the next series of questions. Participants who answered either “Yes” or “Don’t Know” moved on to another set of questions where they were asked about 11 specific examples of cyberbullying including “hacking into another person’s online accounts”, “texting embarrassing or threatening messages”, “harassing other players during live online gaming”, or “outing someone’s sexual status or health status (i.e. sexually transmitted infection (STI) status) online”. The full list of behaviors along with their descriptions in the survey may be seen in the Appendix. Participants were asked to report whether they had been a target of the behavior, had perpetrated the behavior, or whether they had simply witnessed the behavior; participants could check more than one option (i.e. if they had been both a perpetrator and a target). Due to the potentially stigmatizing nature of these topics, students were allowed to skip questions that they did not feel comfortable answering.

Analysis

Participants who endorsed perpetrating one or more cyberbullying behaviors were classified as “bully,” and participants who endorsed being a target of one or more behaviors were classified as “victim.” Those participants who endorsed witnessing one or more behaviors were classified as “witness.” Of note, participants could be classified as more than one of the above. However, if a participant endorsed witnessing one or more cyberbullying behaviors, but had not perpetrated or been a target of any cyberbullying behavior, they were additionally classified as “bystanders.” Descriptive statistics for all groups were calculated using Microsoft Excel.

Results

Demographics

Of the 249 female participants, 85.1% were Caucasian and 96.4% were heterosexual, with nearly one third of participants in their junior year of college (Table 1).

Cyberbullying Behaviors

Nearly half (n = 110,44.2%) of the survey sample had experienced cyberbullying in college as a bully, victim, witness, or combination of the above. The number of participants in each category is displayed in Table 2.

Table 2.

Number (percent) of females reporting cyberbullying behaviors as bullies, victims, and/or witnesses (Total n=110).

Witness Bully Victim Bully + Victim Bully + Witness Victim + Witness Bully + Victim + Witness N/A* No Answer
Hacking into another person’s online account 55 (50) 9 (8.2) 12 (10.9) 6 (5.5) 3 (2.7) 3 (2.7) 1 (0.9) 21 (19.1) -
Posting degrading comments or hate speech 82 (74.6) - 12 (10.9) 3 (2.7) - 2 (1.8) - 10 (9.1) 1 (0.9)
Posting explicit or unwanted pictures 65 (59.1) - 9 (8.2) - - - 1 (0.9) 35 (31.8) -
Creating groups to harass another student 60 (54.5) - - - - 1 (0.9) - 49 (44.6) -
Creating false profiles to post embarrassing comments 50 (45.5) 2 (1.8) 1 (0.9) - - 2 (1.8) - 55 (50) -
Texting embarrassing or threatening messages 44 (40) 1 (0.9) 18 (16.4) 4 (3.6) - 4 (3.6) - 39 (35.5) -
Sending embarrassing or threatening e-mails 34 (30.9) - 10 (9.1) - 1 (0.9) 2 (1.8) - 62 (56.4) 1 (0.9)
Harassing other players during live online gaming 32 (29.1) - 1 (0.9) 2 (1.8) - - - 72 (65.5) 3 (2.7)
Using the Internet to discriminate 51 (46.4) - 1 (0.9) - - - - 57 (51.8) 1 (0.9)
Unwanted sexual advances via the Internet 41 (37.3) - 27 (24.6) 2 (1.8) 1 (0.9) 5 (4.6) - 34 (30.9) -
“Outing” someone’s sexual status or health status 34 (30.9) - 1 (0.9) - - 1 (0.9) - 74 (67.3) -
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*

N/A indicates that the participant has no experience with the behavior.

Witness and Bystander Prevalence

Of the total sample, 105 (42.2%) of respondents had witnessed at least one type of cyberbullying behavior. For most specific behaviors, participants more commonly endorsed witnessing the behavior without participation (i.e. there were fewer in the “bully + witness” or “victim + witness” groups than in the “witness” groups). Among those who witnessed cyberbullying, over a third (n=38, 36.2%) were classified as bystanders; that is, they had witnessed at least one behavior but had not perpetrated or been a target of any cyberbullying behaviors. The most commonly witnessed behavior was posting degrading comments or hate speech (n=82), followed by posting explicit or unwanted picture without consent or knowledge (n=65).

Bully Prevalence

Only 10.8% (n=27) of the total sample endorsed perpetration of cyberbullying behaviors. The majority of these participants (n=19) endorsed hacking or taking over someone else’s social media account and posting as that person.

Victim Prevalence

Among those who reported being targets of cyberbullying (n=61, 24.5% of sample), the most commonly reported types of victimization occurred through unwanted sexual advances through the Internet, i.e. sexting or explicit messages (n=34).

Conclusions

Our results indicate that nearly half of all female college students (44%) have experience with cyberbullying, whether they played the role of bully, victim, or witness. This prevalence rate is consistent with what some previous studies have found in younger adolescents; this suggests that asking about specific behaviors may be a viable way to assess the extent of cyberbullying in the college population (R. M. Kowalski, Giumetti, Schroeder, & Lattanner, 2014). The most commonly witnessed behavior was “degrading comments or hate speech,” while the most common behavior perpetrated was “hacking into another person’s accounts” and the most common behavior among targets was “unwanted sexual advances through the Internet.”

Multiple behaviors were endorsed when participants acknowledged being the target of cyberbullying; such behaviors included “hacking into another person’s online accounts”, “posting degrading comments or hate speech”, “posting explicit or unwanted pictures without consent or knowledge”, “texting embarrassing or threatening messages”, “sending embarrassing or threatening e-mails”, and “unwanted sexual advances through the internet (sexting, explicit messages or e-mails)”. In contrast, admitting to having engaged in bullying behaviors was much rarer and was largely endorsed as having hacked into someone else’s online accounts. This finding is interesting given the considerable number of people who report having been either victims or witnesses of the other behaviors. One explanation could be that hacking is deemed “acceptable” online behavior, while other behavior may be considered “childish” or subject to social desirability bias (Kota et al., 2014).

The results of our study indicate that a large number of college students have witnessed the cyberbullying behaviors we inquired about, with over a third being bystanders, solely witnessing without participating in any way. The bystander effect is a phenomenon under study to understand why individuals either intervene or do not intervene when bullying and victimization is happening in front of them (Nichols, Perkins, Wellman, & Wellman, 2013). This has been widely studied in traditional bullying, but less so in cyberbullying (Cappadocia, Pepler, Cummings, & Craig, 2012; Howard, Landau, & Pryor, 2013; Nichols et al., 2013; Rivers, 2012). Interventions for mediating the bystander effect in traditional bullying have shown promise for decreasing bullying (Andreou, Didaskalou, & Vlachou, 2008; Evers, Prochaska, Van Marter, Johnson, & Prochaska, 2007; Nickerson, Mele, & Princiotta, 2008). In younger adolescents, factors contributing to bystander intervention in cyberbullying scenarios include the perceived severity of cyberbullying and relationships between bystander, bully, and victim (Barlinska, Szuster, & Winiewski, 2013; Bastiaensens et al., 2014; Macháčková, Dedkova, Sevcikova, & Cerna, 2013). Bystander intervention in college students is poorly understood, though one study showed that during a simulated cyberbullying scenario, bystander intervention was low (Shultz, Heilman, & Hart, 2014). Given our results showing the high prevalence of bystanders, further work is needed to evaluate the roles bystanders could play during cyberbullying incidents in a college population.

Our study is not without limitations. Our sample was largely ethnically homogenous; in addition, our sample size was relatively small in comparison to some college epidemiologic studies. Nevertheless, given the multisite design of the study, results may be applicable to the four universities sampled as well as others with similar demographics. Future studies on this topic should seek to capture perspectives of students from a wider range of campus communities in order to determine whether demographic characteristics make it more likely for certain college students to be cyberbullied.

Despite these limitations, our study has important implications. To our knowledge, there have not been studies with this population examining witnessing of the specific cyberbullying behaviors experienced by college students. The behaviors that we discovered to be most common could be used to develop a screening instrument that may be a more accurate way of measuring cyberbullying in this population. In particular, screening for behaviors could address the idea that college students may not identify with the term “cyberbullying;” much media attention around this topic has occurred in middle and high school students, and college students may not recognize the phenomenon as one that could continue in college (Kupczynski, Mundy, & Green, 2013). This is also important to consider because if left unaddressed, these habits may continue into the workplace (R. Kowalski, Giumetti, Schroeder, & Reese, 2012). Workplace bullies are often characterized as manipulative and are described as using subtle techniques that are not necessarily openly hostile; such characteristics bear similarities to cyberbullies (Zapf et al., 2003).

Our results imply that cyberbullying is a valid concern among female college students, especially for behaviors such as hacking into other students’ profiles, sending or receiving unwanted sexual advances through the internet, and posting degrading comments and/or hate speech. Interventions to combat these behaviors should be developed, especially to address bystander impact on cyberbullying.

Acknowledgments

This research was partially supported by the Ruth L. Kirschstein National Research Service Award grant 2T32MH020021-16 from the National Institutes of Health. Additional funding was provided by the University of Wisconsin Department of Pediatrics.

APPENDIX: SURVEY QUESTION

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Contributor Information

Ellen M. Selkie, Fellow, Division of Adolescent Medicine, University of Washington Department of Pediatrics.

Rajitha Kota, University of Wisconsin School of Medicine and Public Health.

Megan Moreno, Seattle Children’s Research Institute.

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