Electronic Bullying and Victimization and Life Satisfaction in Middle School Students

Page Malmsjo Moore • E. Scott Huebner • Kimberly J. Hills

Accepted: 1 May 2011 / Published online: 25 May 2011 � Springer Science+Business Media B.V. 2011

Abstract This study examined the nature and prevalence of electronic bullying and victimization in a sample of middle school students in a southeastern USA school. Rela-

tionships among measures of electronic bullying and victimization and global and domain-

specific life satisfaction were also investigated. A total of 855 7th and 8th grade US

students responded to questions regarding global and domain-based life satisfaction,

electronic bullying and victimization behaviors. Although a majority of students reported

not engaging in or being the victim of electronic bullying, the small percentage of students

who did report these behaviors as being problematic indicated that the behaviors occurred

several times a week. Statistically significant correlates of electronic bullying were self-

reported grades in school, gender, and parent marital status. Significant correlates of

victimization were self-reported grades in school, parent marital status, and ethnicity. The

results suggested modest, but pervasive relationships between experiences of electronic

bullying and victimization and adolescents’ life satisfaction reports across a variety of

important life domains. When the effects of demographic variables were controlled, the

relationship between electronic victimization and global life satisfaction became non-

significant, suggesting that global life satisfaction reports may mask the effects of specific

life satisfaction domains.

Keywords Bullying � Electronic bullying � Electronic victimization � Life satisfaction

1 Introduction

On an annual basis in the USA, researchers estimate that more than 3.7 million students in

grades 6–10 engage in moderate or serious bullying while more than 3.2 million students

are victims of moderate or serious bullying (Nansel et al. 2001). Research in the United

Kingdom has also shown that during adolescence, a great deal of violence in schools is due

to students bullying their peers (Boulton 1999). One contemporary meta-analysis of studies

P. M. Moore � E. S. Huebner (&) � K. J. Hills Department of Psychology, University of South Carolina, Columbia, SC 29208, USA e-mail: [email protected]

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Soc Indic Res (2012) 107:429–447 DOI 10.1007/s11205-011-9856-z

of bullying behaviors spanning nine countries found that the prevalence of bullying others

or having been bullied (at least once in the last 2 months) was 20.8% for physical bullying,

53.6% for verbal bullying, 51.4% for social bullying, and 13.6% for electronic bullying

(Wang et al. 2009). A survey of almost 16,000 USA students in grades 6–10 found that

almost 30% of their sample reported frequent involvement in some form of bullying. More

specifically, approximately 13% were bullies, 10.6% were victims, and 6% were bully/

victims (i.e., bullying others as well as experience bullying; Nansel et al. 2001). Overall,

school bullying has been identified as a major concern among adolescents and school

professionals in multiple nations (Boulton et al. 2008; Hawker and Boulton 2000).

Based on research findings, it has been said that ‘‘bullying may be the most prevalent

form of violence in the schools’’ (Batsche and Knoff 1994, p. 166). One disturbing

reminder of potential violence associated with bullying is found in the research results of a

study conducted by the United States Secret Service. In an effort to better understand

bullying behavior and the potential consequences, the United States Secret Service

embarked on an in-depth investigation of 41 school shooters with incidents having

occurred between 1974 and 2000. Through interviews of both friends and family members,

it was found that 71% of the shooters had been targets of bullying (Vossekuil et al. 2002).

Unfortunately, as the previously mentioned research illustrates, bullying in schools is both

serious and pervasive in nature.

Although the number of students engaged in or targeted by bullying behaviors is

problematic in and of itself, the potential impact on outcomes such as school achievement,

prosocial skills, and psychological well-being for both the victims and perpetrators makes

this phenomenon even more significant (Boulton et al. 2008; Hawker and Boulton 2000).

Chronic victims of bullying report various physical and mental health problems, including

low self-esteem and depression. Victims are also more likely to bring weapons to school

and contemplate suicide as compared to their non-bullied peers (Olweus 1993). Interest-

ingly, negative outcomes associated with bullying behaviors are not limited to the victims

as many often believe. Research has also found that students who engage in bullying

behaviors are more likely to underachieve in school, drop out of school, engage in

delinquent or criminal acts, and become abusive spouses or parents (Olweus 1993).

Despite the fact that research on traditional bullying is vast in comparison, only a

handful of studies have focused specifically on electronic bullying among children and

youth (Kowalski and Limber 2007). In the USA alone, approximately 87% of children

aged 12–17 use the internet daily and 45% own cell phones (Lenhart et al. 2005). Even

though technology is a part of almost every student’s life, relatively little empirical

research related to electronic bullying has been done (Nansel et al. 2001; Williams and

Guerra 2007; Ybarra and Mitchell 2004a). Considered a contemporary form of bullying,

electronic bullying, often referred to as cyber-bullying or online social cruelty, includes

bullying through e-mail, instant messaging, websites, chat rooms, or through digital images

or messages sent via cell phone (Kowalski and Limber 2007). According to the Director for

the Center for Safe and Responsible Internet Use, electronic bullying is discourse that is

‘‘defamatory, constitutes bullying, harassment, or discrimination, discloses personal

information, or contains offensive, vulgar or derogatory comments’’ (Willard 2003, p. 66).

Essentially, youth utilize electronic means of bullying in order to insult, threaten, taunt,

harass, or intimidate a peer (Raskauskas and Stoltz 2007).

Hinduja and Patchin (2008) suggested that this newer form of bullying is the ‘‘unfor-

tunate by-product of the union of adolescent aggression and electronic communication, and

its growth is giving cause for concern’’ (p. 131). One recent survey indicated that more

than 13 million children in the USA aged 6–17 were victims of electronic bullying.

430 P. M. Moore et al.

123

Overall, approximately one-sixth of primary school age children and one-third of teens

reported that they had been threatened, called names, or embarrassed by information

shared about them on the internet (Fight Crime: Invest in Kids 2006). Although a large

portion of actual electronic bullying behaviors occur outside of the school setting,

researchers suggest that these incidents appear to relate to the functioning of students at

school as well as the school environment itself, highlighting the importance of investi-

gating this aggressive behavior within the school system (David-Ferdon and Hertz 2007).

Electronic bullying has been distinguished from traditional forms of bullying. To begin,

traditional bullying is typically defined as verbal or physical behaviors that occur

repeatedly over time, which are characterized by an imbalance of strength or power

(Olweus 1993). Bullying occurs when a student is repeatedly harmed in some way, either

psychologically and/or physically, by another student or a group of students. Typically,

bullies tend to be physically, psychologically, or socially stronger than the children they

bully. Traditional bullying can also include more overt physical acts such as shoving and

hitting, as well as verbal abuse, such as name-calling and taunting. Traditional bullying can

also take on more indirect forms, including rumor spreading and social exclusion (Olweus

1993, 1994).

Results of one anonymous web-based survey of 12–17 year old youth found that, within

a year’s time, 72% of respondents reported at least one online incident of bullying, 85% of

whom also experienced bullying in school (Juvonen and Gross 2008). Researchers found

that, when controlling for internet use, repeated experiences of school-based bullying

increased the likelihood of repeated electronic bullying, which indicates an overlap in

experiences across both contexts. An 85% overlap between online and in-school bullying

suggests that electronic space is not an independent environment, but rather it seems to be

another forum that essentially extends the school grounds (Juvonen and Gross 2008).

Interestingly, students’ roles in traditional bullying have also been found to predict the

same roles in electronic bullying (Raskauskas and Stoltz 2007). For example, traditional

bullies tend to also be electronic bullies while victims of traditional bullying are also likely

to be victims of electronic bullying (Beran and Li 2005). Approximately 64% of students

surveyed in another study reported that electronic bullying was most likely to start at

school as traditional bullying and subsequently continue at home by the same students

(Cassidy et al. 2009). For some victims of bullying, the internet may just be an ‘‘extension

of the schoolyard, with victimization continuing after the bell and on into the night’’

(Ybarra and Mitchell 2004a, p. 1313).

Although similar in many ways, the literature also establishes that meaningful differ-

ences exist between traditional bullying and electronic bullying, further highlighting the

need for additional research (Brown et al. 2006; Kowalski and Limber 2007). One of the

primary differences between these forms of bullying is the continuous, unrelenting nature

of electronic bullying. Essentially, traditional bullying is typically confined to a particular

place or time, whereas electronic bullying is almost limitless in nature (Kowalski et al.

2008). Victims of electronic bullying cannot easily escape as this form of harassment can

occur in almost any context, at any time of the day via electronic means (Brown et al.

2006; Willard 2006). Another significant difference between traditional bullying and

bullying via electronic means involves the component of anonymity (Brown et al. 2006;

Kowalski and Limber 2007; Ybarra and Mitchell 2004a). Unlike traditional forms of

bullying, research has found that almost half of the victims of electronic bullying do not

know the identity of the perpetrator (Kowalski and Limber 2007). Because individuals are

hidden behind the security and anonymity of a computer screen, youth engaged in online

bullying might act differently than they normally would, letting go of traditional

Electronic Bullying and Life Satisfaction 431

123

inhibitions (Berson and Berson 2005; Ybarra and Mitchell 2004b). Interestingly, the

internet may actually provide an opportunity for victims of electronic bullying to com-

municate without fear, allowing for possible revenge against perpetrators (Kowalski and

Limber 2007). Although very preliminary, some research has suggested that electronic

bullying may in fact be more damaging to youth compared to traditional bullying, resulting

in issues such as anxiety, anger, low self-esteem, depression, poor academic performance,

school absenteeism, and even suicide (Willard 2006).

Researchers have begun to explore the prevalence and correlates of electronic bullying

and victimization. A study conducted by the United States Department of Education found

that 90% of children ages 5–17 use computers, and 59% (31 million) have access to the

Internet (DeBell and Chapman 2003). With literally millions of children utilizing the

internet, it is critical to understand prevalence rates as well as possible factors that con-

tribute to perpetration and victimization. In general, prevalence rates indicate that internet

bullying and victimization rates are around 25%, and that this form of bullying has become

a global phenomenon (Aricak et al. 2008; Kowalski and Limber 2007; Willard 2006). One

study of electronic bullying among middle school students found that 22% of students

reported involvement in electronic bullying, including 4% as bullies, 11% as victims, and

7% as both bully-victim (Kowalski and Limber 2007). Results from a survey of 5th, 8th,

and 11th grade students found that 9.4% of the students admitted that they had bullied

others via e-mail or instant messaging (Williams and Guerra 2007). Overall, it has been

estimated that more than 13 million children in the USA ages 6–17 are victims of elec-

tronic bullying (Fight Crime: Invest in Kids 2006).

Understanding the nature and frequencies of electronic bullying is important. It is also

important to understand the correlates and potential warning signs associated with per-

petration and victimization. Warning signs related to victimization include withdrawing

from friends and family members, becoming upset about going to school or going outside,

avoiding discussions related to activities on the computer, showing feelings of anger,

anxiety, or depression following use of the computer, and suddenly not using the computer

anymore (Hinduja and Patchin 2007a). In addition, other signs of victimization include

having been a victim of traditional bullying at school, a decrease in academic performance,

and avoidance of school (Kowalski and Limber 2007). Warning signs related to offending

behavior include using the computer at all hours, creating multiple online accounts, and

quickly closing or switching screens in the presence of others, avoiding discussions related

to activities on the computer, and becoming unusually upset if access to the computer is

restricted (Hinduja and Patchin 2007a).

Research has suggested potential warning signs for electronic victimization as well.

Overall, research indicates that victims tend to be excluded and rejected by their peers

more than bullies (Hawker and Boulton 2000; Juvonen et al. 2003). Victims of electronic

bullying may also withdraw from school activities, and become ill, depressed, or even

suicidal (Willard 2006). As part of a statewide bullying prevention initiative in Colorado,

youth in grades 5, 8, and 11 were surveyed regarding internet bullying, physical bullying,

and verbal bullying. The results revealed that internet bullying peaked in middle school

and declined in high school, making adolescents a particularly vulnerable population.

Interestingly, all three forms of bullying were significantly related to negative peer support,

negative school climate, and normative beliefs condoning bullying, which may serve as

potential risk indicators (Williams and Guerra 2007). Furthermore, the amount of time a

youth spends on the internet as well as their level of computer proficiency have both been

implicated in victimization (Wang et al. 2009).

432 P. M. Moore et al.

123

A handful of studies has investigated the presumed outcomes of electronic bullying and

victimization. Electronic bullying has been linked to multiple maladaptive emotional,

psychological, and behavioral outcomes (Patchin and Hinduja 2006). Similar to traditional

bullying, victims of electronic bullying have been found to display more negative psy-

chological and emotional outcomes, particularly, feelings of anger, frustration, and

depression (Hinduja and Patchin 2007a). Victims of electronic bullying have also been

found to be more likely to report skipping school as well as receiving two or more

detentions or suspensions. Furthermore, youth who report being victims of internet

harassment were found to be eight times more likely than other youth to report carrying a

weapon to school (Wolak et al. 2007; Ybarra et al. 2007a, b).

Victims are not the only at risk population facing negative consequences in regards to

this modern form of bullying. Research suggests that students that engaging in internet

bullying also experience multiple psychosocial challenges including substance use,

delinquency, and poor parent–child relationships (Aricak et al. 2008; Raskauskas and

Stoltz 2007; Ybarra and Mitchell 2004a, b).

Although previous research has examined relationships between electronic bullying and

victimization and a variety of traditional indicators of adolescent mental health, there have

been few studies investigating relationships to individual differences in adolescents’ life

satisfaction (Willkins-Shurmer et al. 2003). Life satisfaction is defined as an individual’s

cognitive appraisal of the positivity of her or his own quality of life overall or with specific

domains, such as family, friends, or community experiences (Diener 1984). Although

related to measures of mental health, life satisfaction measures are distinguishable from

measures of depression, anxiety, and so forth. Contextualized within the emerging positive

psychology perspective, life satisfaction measures extend beyond assessments of the

presence of psychological symptoms or low levels of life satisfaction to assessments that

differentiate satisfaction levels above a neutral point (i.e., the absence of dissatisfaction).

Thus, life satisfaction measures can be designed to differentiate among satisfaction levels

that range from ‘‘low’’ to ‘‘neutral’’ to ‘‘mildly high’’ to ‘‘very high’’, and so forth. In this

manner, life satisfaction measures provide a more finely grained analysis of individuals’

well-being (Diener 1984).

The few studies that have investigated life satisfaction and bullying behaviors have

focused on the victimization component, excluding the possible link between life satis-

faction and perpetration. In one of the only empirical studies that examined the relation-

ships between bullying and adolescents’ life satisfaction, Flaspohler et al. (2009) found

that students who bully and/or are bullied experience reduced life satisfaction and support

from peers and teachers as compared to children who are neither victims nor perpetrators

of bullying. After controlling for gender and grade, students who were not engaged in

bullying reported higher levels of life satisfaction as compared to peers who were bullies or

who were bullied. In addition, results from this study found that students who were both

bullies as well as victims fared the worst in regard to life satisfaction, indicating a potential

additive effect of being both of a bully and victim (Flaspohler et al. 2009).

1.1 Aims of the Current Study

Despite the attention electronic bullying has gained in the popular media, little empirical

research on the antecedents and consequences of electronic bullying actually has been

undertaken (Cook et al. 2007). With millions of children using the internet and electronic

devices every day, it becomes apparent that continued research in the area of electronic

aggression and electronic bullying is imperative. To date, researchers have not examined

Electronic Bullying and Life Satisfaction 433

123

associations between electronic bullying and victimization and life satisfaction in ado-

lescents. Furthermore, while only a few studies have specifically examined bullying

behaviors and life satisfaction, the studies relied upon reports of global or overall life satisfaction. Recent findings suggest there may be benefits to using multidimensional

measures to fully assess life satisfaction. For example, in their examination of life satis-

faction among adolescents, Antaramian et al. (2008) found that family structure differences

(i.e., intact vs. non-intact families) were not related to adolescents’ reports of their general

life satisfaction but did relate to their reports of their satisfaction with their family life

suggesting that general life satisfaction reports may mask differences among various

specific life domains.

In an effort to better distinguish among these domains, a multi-faceted measure (i.e.,

Multidimensional Students’ Life Satisfaction Scale: Huebner 1994) and a global measure

of life satisfaction (Students’ Life Satisfaction Scale: Huebner 1991) were employed

together in this study. In this manner, an assessment of adolescents’ global life satisfaction

was obtained along with assessments across five important, specific domains, including

family, friends, school, living environment, and self. This approach was expected to

provide a more comprehensive, contextualized approach relative to previous studies of the

correlates of electronic bullying and victimization.

This exploratory study thus evaluated the relationships among electronic bullying and

victimization and global life satisfaction and satisfaction with specific life domains (e.g.,

family, school) in middle school students. In addition, the current study examined the

frequencies and demographic correlates of electronic bullying and victimization among

middle school students. As such, three major research questions were investigated,

including:

1. What are the frequencies of major forms of electronic bullying and electronic

victimization in a sample of middle school students?

2. What are the relationships among demographic variables (i.e., age, gender, ethnicity,

socio-economic status, self reported grades, and parent status) and electronic bullying

and electronic victimization?

3. What are the relationships among electronic bullying and electronic victimization and

adolescents’ reports of global and domain-specific life satisfaction (i.e., family, school,

friends, living environment, and self)?

2 Method

2.1 Participants

Students in a large middle school (grades 7 and 8) in the Southeastern USA completed

measures of life satisfaction and electronic bullying and electronic victimization as part of

a larger survey of school climate administered and conducted by school personnel. After

accounting for absences and students whose parents refused permission to participate

(n = 11), a total of 910 students were administered survey packets. After eliminating incomplete surveys, a total of 855 (409 boys and 446 girls) students were included in the

analyses. This sample included 443 seventh-grade (214 boys and 229 girls) and 412 eighth-

grade students (195 boys and 217 girls). The mean age of participants was 13

(SD = .76 years). A total of 59% of the participants were Caucasian, 28% were African

American, 3% were Asian American or Pacific Islander, and 2.6% were Hispanic.

434 P. M. Moore et al.

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Approximately 22% of students reported receiving free or reduced lunch, which was used

as an estimate of socio-economic status (SES). Also, 62.5% of students reported that they

lived with both their biological mother and father, while the remaining 37.5% reported

living with other combinations of adults (i.e., mother and step-father, father and step-

mother, or other adults). Finally, 59.1% of students reported that their parents were mar-

ried, 23.7% reported their parents were divorced, and the remaining 7.2% reported their

parents were separated, never married, or widowed.

2.2 Measures

2.2.1 Electronic Bullying and Victimization

For the purposes of this study, an adaptation of Kowalski and Limber’s (2007) Electronic

Bullying Questionnaire (EBQ) was used. The EBQ is a 23-item self-report measure that

was developed for the purpose of assessing electronic bullying among middle school

students. In the development of the EBQ, Kowalski and Limber (2007) defined electronic

bullying as ‘‘bullying through e-mail, instant messaging, in a chat room, on a website, or

through a text message sent to a cell phone.’’ The EBQ was patterned in part after the

Olweus Bully/Victim Questionnaire (Olweus 1996), a reliable and valid self-report mea-

sure that assesses participants’ experiences with bullying, both as victims and perpetrators

(Olweus 1996; Solberg and Olweus 2003). Similar to the Olweus measure, the EBQ

includes questions about participants’ experiences with bullying (i.e., both being bullied by

and bullying others). Important questions included, ‘‘How often have you been bullied

electronically in the past couple of months?’’ and ‘‘How often have you electronically

bullied someone in the past couple of months?’’

Because of space and time constraints, the original 23-item questionnaire was reduced

to nine core questions that assessed bullying (four questions), victimization (four ques-

tions), and fear of being bullied (one question), eliminating questions concerning how

bullying or victimization occurs (e.g., instant message, text, email). With the exception of

one question aimed at determining how often the participant is afraid of being bullied

electronically, students were asked to respond using the five-point response format from

the Olweus Bully/Victim Questionnaire (i.e., it hasn’t happened in the past couple of

months; only once or twice; two or three times a month; about once a week; several times a

week).

At the time of this study, data on the reliability and validity of the EBQ were not

available. For the current sample, however, coefficient alphas were .83 for the victim-

ization items and .86 for the bullying items, suggesting acceptable internal consistency

reliabilities for the measures. In addition, the mean inter-item correlation value was .41,

with values ranging from .17 to .71, suggesting modest to moderate relationships among

the items.

2.2.2 Multidimensional Students’ Life Satisfaction Scale

Adolescents’ life satisfaction judgments were assessed by the Multidimensional Students’

Life Satisfaction Scale (MSLSS: Huebner 1994). The MSLSS is a 40-item self-report scale

designed for children ages 8–18. Responses are made using a 6-point Likert scale, ranging

from 1 = strongly disagree to 6 = strongly agree. The MSLSS assesses satisfaction across

five important life domains, including family, friends, school, living environment, and self.

Total scores were obtained for each domain by summing the individual items within each

Electronic Bullying and Life Satisfaction 435

123

domain and then dividing by the total number of items within the domain. Support for the

reliability and validity of the MSLSS have been provided in prior studies (e.g., Huebner

1994; Huebner et al. 1998). Alpha coefficients for the domain-based scores have typically

been reported in the .70–.90 range (Gilman et al. 2000; Huebner 1994), with similar test–

retest coefficients for 2- and 4-week periods (Huebner et al. 1998). In addition, convergent

and discriminant validity has been demonstrated through appropriate correlations with

parent reports and other self-report measures (Gilman et al. 2000; Huebner 1994).

2.2.3 Students’ Life Satisfaction Scale

The Students’ Life Satisfaction Scale (SLSS: Huebner 1991) is a 7-item self report scale

designed to assess global life satisfaction in children and adolescents ages 8–18. Like the

MSLSS, students rate each item on a 6 point Likert scale response format from

1 = Strongly Disagree to 6 = Strongly Agree. In addition, two items on the scale are reverse scored. Responses were summed and averaged to obtain a mean global life sat-

isfaction score. The SLSS has consistently demonstrated high reliability and validity.

Internal consistency has been reported to range from .82 to .90, test–retest reliability has

been reported as .76 over a 2-week interval, and inter-item correlations have ranged from

.49 to .73 (Dew and Huebner 1994; Huebner 1991).

2.3 Procedures

During spring 2009, data collection was conducted by the school teachers in their respective

home rooms as part of a school-wide assessment of school climate. Passive consent was

obtained from parents, resulting in 910 students allowed to participate in the study. A total

of 11 students were not allowed to participate. The current study was conducted with

permission from the school district, allowing for use and analysis of their archival data.

Survey packets containing student names and unique identification numbers were dis-

tributed to each homeroom teacher at the middle school. The homeroom teachers dis-

tributed the surveys to their students at the start of the homeroom period as well as read

specific instructions regarding the purpose of the study and the confidentiality of student

responses in order to increase the likelihood of truthful responses. In an effort to control for

possible sequencing effects, a majority of the measures were counterbalanced across

individuals. However, two exceptions to this counterbalancing method were made. Paired

with demographic items, the SLSS was completed first by all students while the EBQ was

completed last. In order to guarantee confidentiality, student identification numbers were

used to ensure confidentiality.

2.4 Data Analysis

Descriptive statistics were calculated. Spearman rho and Pearson correlations were cal-

culated for demographic variables and predictor and criterion variables. The amount of

missing data for the MSLSS, SLSS, and EBQ was small, ranging from .5 to 4.5%. Given

the small amount of missing data, and in order to retain an adequate sample size and

statistical power, mean substitution procedures were used to handle missing data (Buhi

et al. 2008).

Hierarchical regression analyses were subsequently employed to determine the unique

relationships among electronic bullying and victimization and the life satisfaction scores,

436 P. M. Moore et al.

123

after partialling out the effects of demographic variables. Before proceeding to the

regression analyses, normality of criterion variables was assessed by plotting histograms.

Upon inspection, it was observed that friend satisfaction and self satisfaction scores were

not normally distributed and demonstrated excessive skew (-1.98 and -1.55 respectively)

and kurtosis (5.05 and 3.15 respectively). Despite violation of the normality assumptions,

parametric tests were utilized for several reasons. The effect of the violation of the nor-

mality assumption on significance tests depends on the sample size, with problems

occurring in smaller samples (Cohen et al. 2003). With larger sample sizes, such as the

current study, non-normality does not lead to serious problems with significance tests. In

addition, both square root and log transformations were conducted, neither of which

changed the shape of the distributions. The remaining criterion variables appeared

approximately normal and exhibited skew and kurtosis levels within acceptable limits

(between -1.0 and 1.0).

3 Results

Frequencies, means and standard deviations for life satisfaction, electronic victimization,

and electronic bullying are summarized in Tables 1, 2 and 3. When asked about bullying

and victimization in the past few months, 86% of participants reported that they did not

partake in any form of electronic bullying while 80% reported they were not victims.

Overall, participants self-reported moderate levels of global life satisfaction as measured

by the SLSS (M = 4.55, SD = 1.06). The MSLSS domain scores indicated that partici- pants were most satisfied with their friends (M = 5.31, SD = .87) and least satisfied with school (M = 4.37, SD = 1.27).

Electronic bullying was found to be significantly correlated with gender (r = .13, p \ .001), parent marital status (r = .10, p \ .005), and self-reported grades in school (r = -.18, p \ .001). Electronic victimization was significantly correlated with ethnicity (r = .08, p \ .05), grade (r = -.07, p \ .05), SES (r = .07, p \ .05), parent status (r = .09, p \ .01, and self-reported grades in school (r = -.23, p \ .001). Global life satisfaction (i.e., SLSS scores) was significantly correlated with parent custody (r = -.15 p \ .001), parent status (r = -.20, p \ .001) and self-reported grades in school (r = .29, p \ .001). Family satisfaction was correlated with parent custody (r = -.09, p \ .01), parent status (r = -.15, p \ .001) and self-reported grades in school (r = .20, p \ .001). Friend satisfaction was correlated with gender (r = .16, p \ .001), parent status (r = -.07, p \ .05) and self-reported grades in school (r = .11, p \ .05). Living satisfaction

Table 1 Descriptive statistics for measures

Scoring of SLSS: 1 = Strongly Disagree to 6 = Strongly Agree; Scoring of MSLSS: 1 = Strongly Disagree to 6 = Strongly Agree

Variable M SD

SLSS 4.55 1.06

Family satisfaction 4.76 1.20

Friend satisfaction 5.31 .87

Living satisfaction 4.80 1.19

Self satisfaction 5.14 .86

School satisfaction 4.37 1.27

Electronic bullying 1.36 .69

Electronic victimization 1.18 .49

Electronic Bullying and Life Satisfaction 437

123

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438 P. M. Moore et al.

123

was correlated with grade (r = -.08, p \ .01), age (r = -.09, p \ .05), parent status (r = -.11, p \ .01), and self-reported grades in school (r = .16, p \ .001). Self satis- faction was correlated with race (r = .24, p \ .001) and self -reported grades in school (r = .13, p \ .001). Finally, school satisfaction was correlated with gender (r = .09, p \ .01), SES (r = .22, p \ .001), and self- reported grades in school (r = .13, p \ .001).

Zero-order correlations among the major variables are presented in Tables 4 and 5.

There were modest, negative correlations between electronic bullying and the global life

satisfaction (r = -.22), and all of the domain-based measures of life satisfaction (ranging from r = -.15 to -.22). There were also modest, negative correlations between victim- ization and global life satisfaction (r = -.11) and all of the domain-based measures of life satisfaction (ranging from r = -.13 to -.18).

Table 3 Descriptive statistics for electronic bullying and victimization

N M SD

Electronic victimization

How often have you electronically bullied someone in the past couple of months? 857 1.22 .65

Have you made fun of someone or teased someone else in a hurtful way…? 856 1.27 .66 Have you told lies or spread rumors about someone else …? 857 1.17 .57 Have you used someone else’s computer username or screen-name to spread rumors or

lies about another person? 856 1.09 .48

Electronic Bullying

How often have you been bullied electronically in the past couple of months? 854 1.35 .85

Has anyone made fun of you or teased you in a hurtful way…? 857 1.35 .83 Has anyone told lies or spread rumors about you…? 857 1.58 1.02 Has anyone used your computer username or screen-name to spread rumors or lies

about another person? 857 1.17 .65

Response options for the EBQ are as follows: 1 = Hasn’t happened; 2 = Once or twice; 3 = 2 or 3 times a month; 4 = Once a week; 5 = Several times a week

Table 4 Correlations among demographic variables, bullying, victimization, and life satisfaction

Bully Victim SLSS Family Friend Living Self School

Grade -.04 -.07* .03 .002 .06 -.08* .01 -.03

Sex .13** .02 -.05 -.02 .16** -.03 .01 .09*

Race -.07 .08* -.02 .04 .02 .05 .24** .22**

SES .06 .07* -.05 -.06 -.05 -.06 .22** .05

Age .04 -.03 -.04 -.05 -.02 -.09** -.004 -.02

Custody .04 .05 -.152** -.093** -.034 -.06 .001 .02

Status .10** .09** -.20** -.15** -.07* -.11** -.04 -.03

Grades -.18** -.23** .29** .20** .11** .16** .13** .13**

Race is coded 1 = Minority Race/Ethnicity and 0 = Caucasian. Sex is coded 0 = Male and 1 = Female. SES is coded 0 = regular lunch and 1 = free or reduced rate lunch. Custody = Parent Custody. Status = Parent Status. Grades = Self reported grades

* p \ .05; ** p \ .01

Electronic Bullying and Life Satisfaction 439

123

Independent-samples t tests were also conducted in order to compare electronic bullying and victimization scores across gender, ethnicity, socioeconomic status, parent custody and

parent marital status (Table 6). Significant differences were found regarding electronic

bullying for gender (males M = 1.28, SD = .61; females M = 1.43, SD = .74; t (849) = -3.26, p \ .01, d = -.22), parent marital status (biological parents married M = 1.32, SD = .66; other marital status M = 1.42, SD = .72; t (842) = -2.15, p \ .01, d = -.14), and parent custody (live with both biological parents M = 1.32, SD = .65; live with other combination of adults M = 1.43, SD = .43; t (849) = -2.21, p \ .05, d = -.20). Significant differences were found regarding electronic victimization for gender

(males M = 1.22, SD = .61; females M = 1.15, SD = .35; t (849) = 1.97, p \ .05, d = -.60), ethnicity (Caucasian M = 1.16, SD = .41; African-American M = 1.24, SD = .58; t (743) = 2.02, p \ .05, d = .17), parent marital status (biological parents married M = 1.14, SD = .40; other marital status M = 1.24, SD = .60; t (843) = -2.96, p \ .01, d = -.20), and parent custody (live with both biological parents M = 1.15, SD = .43; live with other combination of adults M = 1.24, SD = .58; t (850) = -2.45, p \ .01, d = -.18).

Hierarchical multiple regression analyses were used to assess the relationship between

electronic bullying and victimization and life satisfaction, as measured by the MSLSS

domain-based scores and SLSS global score, after controlling for significant demographic

variables. In all, twelve regression analyses were run with electronic bullying and vic-

timization as predictor variables and global and domain-based life satisfaction measure as

criterion variables. After controlling for demographic variables in Step 1 of each of the

analyses, the electronic bullying or victimization scores were entered in Step 2 in order to

determine their unique effects on the criterion variables. The regression models are pre-

sented in Tables 7 and 8. Overall, after controlling for demographic relationships, elec-

tronic bullying related significantly to global life satisfaction (beta = -.14, p \ .001; DR2 = .02), family satisfaction (beta = -.17, p \ .001; DR2 = .03), friend satisfaction (beta = -.19, p \ .001; DR2 = .03), living satisfaction (beta = -.16, p \ .001; DR2 = .02), self satisfaction (beta = -.18, p \ .001; DR2 = .03), and school satisfaction (beta = -.14, p \ .001; DR2 = .02). Also, electronic victimization, related significantly to family satisfaction (beta = -.11, p \ .001; DR2 = .01), friend satisfaction (beta = -.10, p \ .005; DR2 = .01), living satisfaction (beta = -.11, p \ .005; DR2 = .01), self satis- faction (beta = -.17, p \ .001; DR2 = .03), and school satisfaction (beta = -.14, p \ .001; DR2 = .02).

Table 5 Correlations among life satisfaction, bullying, and victimization

Global Family Friend Living Self School Bully Victim

Global –

Family .60* –

Friend .40* .40* –

Living .53* .66* .53* –

Self .47* .55* .67* .56* –

School .43* .58* .46* .51* .58* –

Bully -.22* -.22* -.19* -.19* -.21* -.15* –

Victim -.11* -.15* -.13* -.14* -.18* -.16* .41* –

* p \ .01

440 P. M. Moore et al.

123

4 Discussion

This study explored experiences of electronic bullying and victimization among middle

school students in a suburban USA school. A total of 14% of the students reported

engaging in electronic bullying behaviors, while 20% reported being victims of electronic

bullying. Of more concern is the fact that of those students who reported victimization and

Table 6 Results of T tests and descriptive statistics

Group 95% CI for mean difference t df d

Male Female

M SD n M SD n

Victim 1.22 .61 407 1.15 .35 444 .000–.132 1.97* 849 -.03

Bully 1.28 .61 408 1.43 .74 443 -.001–.134 -3.25** 849 -.22

Caucasian Minority 95% CI for mean difference t df d

M SD n M SD n

Victim 1.16 .415 505 1.24 .578 240 .011–.157 2.27* 743 .17

Bully 1.37 .680 505 1.31 .626 239 -.161–.043 -1.13 742 -.09

7th Grade 8th Grade 95% CI for mean difference t df d

M SD n M SD n

Victim 1.21 .54 441 1.15 .44 410 .000–.127 1.80 849 .12

Bully 1.39 .72 441 1.33 .65 410 -.034–.149 1.23 849 .08

FRL No FRL 95% CI for mean difference t df d

M SD n M SD n

Victim 1.23 .61 184 1.17 .46 656 -.151–.010 -1.72 838 -.13

Bully 1.39 .64 183 1.35 .70 656 -.148–.072 -.623 837 -.05

Custody both Custody other 95% CI for mean difference t df d

M SD n M SD n

Victim 1.15 .43 533 1.24 .58 319 -.154–.017 -2.45** 850 -.18

Bully 1.32 .65 532 1.43 .43 319 -.203–.012 -2.21* 849 -.20

Bio married Other status 95% CI for mean difference t df d

M SD n M SD n

Victim 1.14 .40 500 1.24 .60 345 -.174–.029 -2.96** 843 -.20

Bully 1.32 .66 498 1.42 .72 346 -.198–.009 -2.15* 842 -.14

Race is coded 1 = Minority Race/Ethnicity and 0 = Caucasian. Sex is coded 0 = Male and 1 = Female. SES is coded 0 = regular lunch and 1 = free or reduced rate lunch. Custody is coded as 0 = live with both biological parents and 1 = other combination of adults. Status is coded as 0 = Married and 1 = Other status

* p \ .05; ** p \ .01

Electronic Bullying and Life Satisfaction 441

123

Table 7 Summary of regression analyses with predictor variable electronic bullying

B SEB b DR2 DF

Family satisfaction

Demographics .23 .04 .19 .07 8.16*

Demographics & victimization -.31 .06 -.17 .03 25.03*

Friend satisfaction

Demographics .06 .03 .07 .04 5.27*

Demographics & victimization -.24 .04 -.19 .03 30.00*

Living satisfaction

Demographics .18 .04 .14 .05 6.33*

Demographics & victimization -.27 .06 -.15 .02 19.43*

Self satisfaction

Demographics .12 .03 .14 .06 7.48*

Demographics & victimization -.23 .04 -.18 .03 26.70*

School Satisfaction

Demographics .17 .05 .13 .07 9.07*

Demographics & victimization -.26 .06 -.14 .02 15.84*

Global life satisfaction (SLSS)

Demographics .28 .04 .26 .13 16.19*

Demographics & victimization -.22 .05 -.144 .02 17.51*

* p \ .01

Table 8 Summary of regression analyses with predictor variable electronic victimization

B SEB b DR2 DF

Family satisfaction

Demographics .23 .04 .18 .07 8.14*

Demographics & victimization -.28 .09 -.11 .01 10.52*

Friend satisfaction

Demographics .06 .03 .07 .04 5.25*

Demographics & victimization -.18 .06 -.10 .01 8.11*

Living satisfaction

Demographics .18 .04 .14 .05 6.32*

Demographics & victimization -.27 .09 -.11 .01 9.53*

Self satisfaction

Demographics .12 .03 .14 .06 7.52*

Demographics & victimization -.30 .06 -.17 .03 22.95*

School satisfaction

Demographics .17 .05 .13 .07 9.13*

Demographics & victimization -.37 .09 -.14 .02 16.19*

Global life satisfaction (SLSS)

Demographics .28 .04 .26 .13 16.21*

Demographics & victimization -.08 .07 -.04 .001 1.17

* p \ .01

442 P. M. Moore et al.

123

bullying, 3% of students reported being victims of electronic bullying several times a week

while 1.4% reported engaging in electronic bullying several times a week, indicating that a

small portion of students engage in or suffer from chronic forms of electronic bullying.

Electronic bullying displayed statistically significant associations with student gender,

parent marital status, and self-reported grades in school. Electronic victimization showed

statistically significant associations with student ethnicity, grade level, SES, parent marital

status, and self-reported grades in school. Furthermore, students who did not live with both

biological parents were more likely to be both victims and perpetrators of electronic

bullying compared to students living with both biological parents. Similarly, students

whose biological parents were not married were more likely to be both victims and per-

petrators as compared to students whose biological parents were married. These differ-

ences suggest that both bullies and victims may be more likely to come from non-intact

family situations as compared to their peers.

Student gender also related significantly to experiences of electronic bullying and vic-

timization. In this sample, female students were more likely to engage in electronic bul-

lying, and females and minority students were more likely to be victims. These results were

not necessarily expected as previous studies have suggested that females are more likely to

be victims of electronic bullying whereas males are more likely to be aggressors (Kowalski

and Limber 2007; Wang et al. 2009). However, girls outnumbered boys (446–409) in this

sample, possibly accounting for the differences among studies. It may also be important to

consider that in regard to traditional bullying, girls tend to utilize relational aggressive acts

more than boys (Crick and Bigbee 1998; Crick and Grotpeter 1995; French et al. 2002).

Similarly, contrary to the findings of this study, previous research has suggested that

minority students are more often involved in electronic bullying behaviors as aggressors

rather than as victims (Wang et al. 2009). Thus, although generalizable demographic dif-

ferences may emerge as more research findings appear in the literature, it does appear safe to

conclude that individuals can be subjected to and engage in electronic bullying regardless of

age, gender, ethnicity, academic performance, and SES (Aricak et al. 2008).

The differences in the findings of studies of the experiences of early adolescents with

electronic bullying and victimization merit further consideration. The differences may be

due to various issues related to the novelty of the research area. These issues include

differences across studies in terms of the definitions of bullying and victimization, samples,

and measures. For example, little information is available regarding the psychometric

properties of the existing measures of electronic bullying and victimization. Because of the

unknown validity of the measures, students who have may been exposed to electronic

bullying may not recognize it as such due to how and what is being asked of them. These

students may not recognize that what they have experienced is, in fact, a form of bullying

(Aricak et al. 2008; Kowalski and Limber 2007). For another example, differences in the

age levels of student samples are likely important. As children progress through school,

their access to and use of electronic technologies and social networking cites is likely to

increase, which may in turn result in an increase in electronic bullying (Kowalski and

Limber 2007). Finally, differences in the modalities associated with electronic bullying are

likely critical to understand. Although the original questionnaire used in this research study

asked about bullying modalities (i.e., cell phone, emails, social network sites), these

questions had to be removed because of space and time limitations. Variation may occur

due to differences in access and therefore exposure to the type of bullying that occurs. For

example, many schools and public libraries in the USA now have computers available to

students, which may account for an increase in electronic bullying due to computer use as

compared to more personal, costly devices such as cell phones.

Electronic Bullying and Life Satisfaction 443

123

This study also investigated the relationship between electronic bullying and victim-

ization and adolescents’ reports of global and domain-specific life satisfaction (family,

school, friends, self, and living environment). The findings revealed modest, negative

correlations between electronic bullying and victimization and global life satisfaction and

satisfaction with family, friends, living environment, self, and school. Thus, the presumed

effects of electronic bullying and victimization although modest, appear quite pervasive,

occurring across multiple important life domains.

In general, these results are consistent with traditional bullying and life satisfaction

research, which indicates that students who report being bullies and victims of traditional

bullying have lower levels of life satisfaction compared to their peers (Flaspohler et al.

2009). Specifically, research examining on-line harassment suggests that those with lower

levels of self-esteem are more likely to respond maladaptively compared to their non -

victimized peers (Hinduja and Patchin 2007b). Similarly, research has found that both

overt victimization and relational victimization experiences correlate with reduced levels

of life satisfaction (Martin and Huebner 2007). In contrast, students who report higher

levels of life satisfaction tend to report better interpersonal, intrapersonal, and academic

outcomes. Youth who report higher levels of life satisfaction also report higher levels of

personal control, self-esteem, extraversion, hope, self-efficacy, and interpersonal skills.

These youth also report higher school grades, better peer relationships, and more positive

school experiences (Gilman and Huebner 2006; Suldo and Huebner 2006).

After controlling for significant demographic relationships, the results of the hierar-

chical multiple regression analyses, controlling for significant demographic relationships,

revealed comparable findings to those based on the zero-order correlations, with one

exception. With demographic variables were controlled, the relationship between elec-

tronic victimization and global life satisfaction became non-significant whereas relation-

ships with the domain-based measures remained significant. This finding suggests the

possibility that global measures of life satisfaction may mask important relationships on

occasion. The finding of the non-significant relationship with overall life satisfaction is

consistent with the previously mentioned study by Antaramian et al. (2008), in which

differences in family structure (i.e., intact vs. non-intact) related significantly to satisfac-

tion with family life, but not with overall life satisfaction. Thus, further research is needed

to determine the relative sensitivity of global and domain-based life satisfaction measures

in various contexts. Future research should also explore whether or not the modest rela-

tionships with the various life satisfaction reports generalize across different samples of

adolescents or whether there are potential moderators of the relationships (e.g., differences

in social support), such that some students experience more detrimental consequences that

others from this new form of bullying. For example, Flaspohler et al. (2009) found that the

relationships between victimization and life satisfaction were stronger for students with

low social support from peers and teachers.

Overall, this study has several major limitations. First, data were obtained from students

from a Southeastern USA middle school with characteristics that were not representative of

the USA as whole, which may limit the generalizability of the findings. More research is

needed in order to investigate the relationship between electronic bullying and life satis-

faction with more representative samples of students as well as with students from other

age ranges. Another limitation of this study was the cross-sectional design, which cannot

shed light on the directionality of the relationships between electronic bullying and life

satisfaction. Longitudinal analyses are needed to clarify the directionality of the rela-

tionships, including the possibility of bidirectional relationships.

444 P. M. Moore et al.

123

The findings of this exploratory research study have important implications for not only

youth engaging in and victimized by electronic bullying, but also for parents and human

services professionals alike. As previously discussed, bullying from peers has been iden-

tified as one of the most problematic behavioral concerns among adolescents (Boulton

1999; Boulton et al. 2008; Hawker and Boulton 2000). With the high prevalence rates of

electronic bullying and victimization, such experiences have become a global phenome-

non, meriting considerable concern (Aricak et al. 2008; Kowalski and Limber 2007;

Willard 2006). Given that a majority of students report that electronic bullying is most

likely to start at school and continue at home, it is important for parents and school and

community professionals to take such behavior seriously and educate themselves about its

nature, frequency, and correlates (Cassidy et al. 2009; Kowalski et al. 2008). Furthermore,

it is critical that preventative and palliative strategies are developed to address concerns

related to electronic bullying and victimization. The available evidence suggests that

electronic bullying and victimization are related to lower subjective well-being, in the form

of reduced life satisfaction, for both parties. As technology continues to progress, it is

likely that adolescents’ use of electronic communication technologies will increase,

therefore, continued research is critical to understand this new form of bullying and its

consequences.

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Willard, N. (2003). Off-campus, harmful online student speech. Journal of School Violence, 1, 65–93. Willard, N. (2006). Flame retardant. School Library Journal, 52, 55–56. Williams, K., & Guerra, N. (2007). Prevalence and predictors of internet bullying. Journal of Adolescent

Health, 41, S14–S21. Willkins-Shurmer, A., O’Callaghan, M., Najman, J., Bor, W., Williams, G., & Anderson, M. (2003).

Association of bullying with adolescent health-related quality of life. Journal of Pediatric Child Health, 39, 436–441.

Wolak, J., Mitchell, K., & Finkelhor, D. (2007). Does online harassment constitute bullying? An exploration of online harassment by known peers and online only contacts. Journal of Adolescent Health, 41, S51– S58.

Ybarra, M., Espelage, D., & Mitchell, K. (2007a). The co-occurrence of online verbal aggression and sexual solicitation victimization and perpetration: Association with psychosocial indicators. Journal of Adolescent Health, 41, S31–S41.

Ybarra, M., & Mitchell, K. (2004a). Online aggressor/targets, aggressors, and targets: A comparison of associated youth characteristics. Journal of Child Psychology and Psychiatry, 45, 1308–1316.

Ybarra, M., & Mitchell, K. (2004b). Youth engaging in online harassment: associations with caregiver-child relationships, Internet use, and personal characteristics. Journal of Adolescence, 27, 319–336.

Ybarra, M., West, M., & Leaf, P. (2007b). Examining the overlap in internet harassment and school bullying: Implications for school intervention. Journal of Adolescent Health, 41, S42–S50.

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ORIGINAL ARTICLES

Cyberbullying: The Challenge to Define

Colette Langos, B.A., L.L.B., GDLP, MComL

Abstract

Cyberbullying is a reality of the digital age. To address this phenomenon, it becomes imperative to understand exactly what cyberbullying is. Thus, establishing a workable and theoretically sound definition is essential. This article contributes to the existing literature in relation to the definition of cyberbullying. The specific elements of repetition, power imbalance, intention, and aggression, regarded as essential criteria of traditional face-to-face bullying, are considered in the cyber context. It is posited that the core bullying elements retain their importance and applicability in relation to cyberbullying. The element of repetition is in need of redefining, given the public nature of material in the online environment. In this article, a clear distinction between direct and indirect cyberbullying is made and a model definition of cyberbullying is offered. Overall, the analysis provided lends insight into how the essential bullying elements have evolved and should apply in our parallel cyber universe.

Introduction

What has become overwhelmingly apparent over thelast decade is just how extensively new information and communication technologies (ICTs) have become inter- twined with our everyday lives. The benefits of new tech- nology are undeniable, but along with the advantages comes the potential for technology to be misused. Cyberbullying is one of the negative by-products of the digital age.

Cyberbullying has proven difficult to define. To date, a universal definition has not been agreed upon. A literal ap- proach to interpreting the meaning may be to consider the words ‘‘cyber’’ and ‘‘bullying’’ quite separately, attaching ordinary, natural meaning to the words and then merging the two meanings to create a singular meaning.

Following this approach, ‘‘cyber’’ may be quite simply described as ‘‘generated by technology.’’ Defining ‘‘bullying’’ presents a more challenging task.1,2 Semantic differences may explain the varying conceptualizations of bullying,1 consid- ering linguistic differences that exist across disciplines and cultures. In general, national and international consensus exists3 that bullying is a subset of aggression defined as be- ing a ‘‘specific type of aggressive behaviour that is intended to cause harm, through repeated actions carried out over time, targeted at an individual who is not in a position to defend him/herself.’’4 It can be physical or nonphysical in form.5

The elements of repetition (a course of conduct as op- posed to a single incident); power imbalance (where the offender demonstrates power over the target); intention (conduct must be intended as opposed to accidental); and

aggression (conduct involves maliciousness on the part of the aggressor) are broadly considered as being the necessary elements differentiating bullying from mere aggression. A distinction can be made between direct and indirect tradi- tional bullying. Direct bullying may include physical bul- lying (e.g., hitting and kicking), damaging the personal property of a victim, or verbally bullying the victims (e.g., name calling). Indirect bullying in the traditional sense may include behaviors such as spreading false rumors about the victim behind their back.

The four core bullying elements are encapsulated within several descriptive cyberbullying definitions.6,7 The element unique to a cyberbullying definition relates to use of ICTs through which repeated, aggressive online acts are facilitated. Cyberbullying can occur through a variety of technological media, such as computers, mobile phones (smart phones), or any other ICTs. Cyberbullying is bullying transposed on a technological platform.

Traditional Bullying Elements in the Cyber Context

There is some academic debate as to the importance of the four foundation elements of traditional bullying in the cyber context. This being the case, the ordinary meanings of repe- tition, power imbalance, intention, and aggression will need revising/redefining to tailor their meanings to the cyber en- vironment if society is to develop a satisfactory response to the phenomenon.

To assist in understanding how the elements may apply in the cyber context, it is necessary to differentiate between di- rect and indirect cyberbullying.

Centre for Regulation and Market Analysis, and School of Law, University of South Australia, Adelaide, South Australia, Australia.

CYBERPSYCHOLOGY, BEHAVIOR, AND SOCIAL NETWORKING Volume 15, Number 6, 2012 ª Mary Ann Liebert, Inc. DOI: 10.1089/cyber.2011.0588

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Direct cyberbullying occurs where the cyberbully ‘‘directs the electronic communications directly at the victim. It en- compasses a cyberbully’s use of instant messaging, text or multimedia messaging, or email intended to have a direct, immediate effect on the victim.’’8 Direct cyberbullying is limited to the context where the cyberbully directs commu- nications to the victim only, as opposed to communications that are posted to more public areas of cyberspace. Direct cyberbullying occurs in the private domain.

Indirect cyberbullying occurs where the cyberbully ‘‘does not direct the electronic communication that constitutes the bullying at his/her victim directly. Instead, the bully posts them on MySpace, Facebook, a specially created Website or blog, or some other reasonably public area of cyberspace.’’8

Public forums such as social media sites, blogs, Web pages, and video-sharing Web sites are obvious examples of plat- forms that fall within the public cyberspace arena. The con- cept of the public domain in cyberspace extends to situations where the victim has knowledge of multiple recipients being privy to a personal communication transmitted via ICTs. The nature of this technology is such that the sender has no con- trol over to whom the original communication is forwarded. Because multiple parties are directly privy to the original electronic communication, the communication has the po- tential to spread to an infinite audience. Thus, once any other recipient has access to the information, it should be consid- ered material falling within the public arena.

Repetition

Repetition is firmly established as being a key criterion in cyberbullying.9,10 Without the presence of this element, con- duct may arguably be described as mere face-to-face joking or jovial teasing in the traditional sense, or cyberjoking or playful cyberteasing in the virtual world. Teasing is specifically re- ferred to as playful or jovial in nature. Olweus comments that some forms of ‘‘repeated teasing of a degrading and offensive character continued in spite of clear signs of distress or op- position on the part of the target qualifies as bullying.’’11 Re- petition is an important criterion to allow for differentiation between a joke or jovial teasing and an intentional attack.12

The presence of repetition demonstrates systematic conduct. The nature of cyberspace alters the way in which repetition

should be understood in some instances. One act in cyber- space, such as one posting of a photo or video, one posting on a blog, on a Web site, one e-mail sent, one twitter tweeted, or one SMS sent, has the unique ability to remain in cyberspace indefinitely, as photos, videos, e-mails, tweets, and phone messages can be archived or forwarded by anyone who gains access. A single act could be considered repetitive each time the blog, Web site, video, e-mail, photo, or text message is accessed/viewed.13 In the cyber context, it is necessary to consider the element of repetition differentiating between direct and indirect cyberbullying.

Direct cyberbullying occurs in the private arena. It involves electronic communications directed from the perpetrator to the victim only. Direct cyberbullying could include, but is in no way limited to, calls from the perpetrator’s mobile phone to the victim’s mobile phone, SMS messaging between the perpetrator’s mobile phone and the victim’s mobile phone, or e-mails sent to a victim’s personal e-mail account from the perpetrator’s personal e-mail account. In the direct cyber-

bullying context, for conduct to qualify as cyberbullying, the victim would need to be subjected to a course of conduct to establish the element of repetition. The negative conduct needs to occur on more than one occasion so as to distinguish it from a one-off act of aggression. In this manner, the element of repetition in the direct cyberbullying context is defined in the same way as it is defined in the traditional face-to-face bullying context.

Indirect cyberbullying occurs in the public cyber arena. It refers to material that has been posted to areas in cyberspace that are publically accessible. In circumstances where a perpetrator posts an electronic communication into a public forum, such as a public blog, a social media forum, or a video- sharing Web site, it is no longer necessary for the victim to prove a course of conduct to satisfy the element of repetition. Repetition occurs by virtue of the arena in which the behavior occurs. Material can remain in the public cyber arena indefi- nitely. It can be viewed publically countless times. It can be distributed, and it can be saved and re-posted at a later time. In the instance where an electronic communication has been sent directly to the victim but has, to the victim’s knowl- edge, been copied/forwarded to other people, the act of distribution propels the material out of the private domain and into the public arena. This negates the victim’s onus to establish a course of conduct to establish the element of repetition.

For the purpose of the definition of cyberbullying, repeti- tion in the private context (electronic communication between the perpetrator and the victim only) occurs as a result of multiple contacts; in the public arena (electronic communi- cation that has been distributed to persons other than the victim only), it can be established simply by its appearance in that forum.

Power Differential

Power imbalance (power differential) is another element considered by many researchers as an essential criterion to the cyberbullying definition. In the traditional bullying con- text, a power imbalance relates to the ‘‘demonstration or in- terpretation of power by the offender over the target.’’7 The meaning is not altered in the cyber context. Although a power imbalance may be achieved in various new ways in cyber- space, this does not alter the fact that, in order for conduct to qualify as cyberbullying, the conduct must place the vic- tim in a position where he/she cannot easily defend him/ herself.

In the physical world, a person’s characteristics such as popularity, height, intelligence, physical strength, age, sex, and socioeconomic status can give a perpetrator perceived or actual power over a victim.7 It is not uncommon to hear of instances where a larger student bullies a smaller student. The power imbalance between the two students is likely to result from the smaller student feeling defenseless against the physically much larger student. Additionally, factors such as low social integration, low self-esteem, a problematic parent– child relationship, or school-related behavioral problems have been established as determinates of school victimiza- tion.14 In the physical world, it is not uncommon to hear of situations where a bully targets a victim who displays signs of low social integration. This aspect makes the target a per- ceived easy target for the bully. There is a power imbalance

286 LANGOS

between the perpetrator and the target that defines the rela- tionship: where the perpetrator is perceived as the stronger party and the victim (the social outcast) as the weaker party who cannot easily defend him/herself against the bully. Known determinates of school victimization, along with a person’s physical characteristics, can act as ammunition a perpetrator uses to exploit power over a victim. Studies conducted on school children in Sweden, Germany, and Belgium demonstrate that targets of traditional bullying are more likely to become targets of cyberbullying.13–15 This would suggest that determinates of traditional bullying that enable a perpetrator to demonstrate actual or perceived power over a victim may also be determinates of cyberbul- lying. (The fact that a victim is perceived as a social outcast in the physical world may continue to be a reason for the con- tinued bullying of the victim in the parallel cyber world.) However, it is also possible that a perpetrator in cyberspace does not know his/her victim in a physical social context. Electronic media provide a novel platform for individuals to connect with strangers. In such cases, physical characteristics or other determinates of school victimization are unlikely to be the trigger for the cyberbullying.

In addition, cyberspace presents a bully with new oppor- tunities in which to flaunt their power over a perceived weaker victim. It has been suggested that varying degrees of technological skill may create a power differential between a perpetrator and a victim in the digital world.15 In this sense, a victim could feel powerless in defending him or herself against a perpetrator’s online actions as a result of the per- petrator’s perceived or actual greater technological expertise. Once online material enters the public online environment, as material can be disseminated, archived, reposted, or altered by people other than the victim or the perpetrator. This fact plays to a perpetrator’s perceived and actual power over the victim in the cyber context given the complexities associated with controlling material in cyberspace.

A perpetrator may feel emboldened to engage in cyber- bullying as a result of the perceived anonymity cyberspace presents. Cyberbullies are able to create pseudonyms and provisional e-mail addresses and to block their telephone number to conceal their identity. A victim is likely to feel increased feelings of powerlessness by not knowing the per- son behind the cyber aggression.15 In this manner, the victim could be interpreted as the weaker party.

The seemingly limitless nature of technology means a cy- berbully (as opposed to a schoolyard bully or a workplace bully) can penetrate the home environment. There are no spatial or time limitations. This factor awards a perpetrator the upper hand and ensures the victim feels powerless in comparison.16

Additionally, a victim may feel less able (and therefore more powerless) to defend him or herself against a potentially infinite cyber audience. In the physical world, the number of witnesses to bullying is likely to be far fewer.

The cyber environment creates a variety of new opportu- nities that can give rise to an exploitation of power in a perpetrator/victim relationship. The element of power imbalance remains and therefore an essential criterion that applies equally in both the private and public contexts. In either setting, physical or virtual, a victim’s lack of perceived or actual power comparative to the perpetrator’s possession of power is crucial to the definition.

Aggression and Intention

The bullying context

In the bullying context, the elements of intention and ag- gression are intrinsically linked. Defined as a subset of ag- gression,17 bullying inherently contains the same elements that frame the definition of aggression. What propels bullying out of the broad pool of merely aggressive behaviors into a new realm (or subset of aggression) are the necessary ele- ments of repetition and power imbalance.

Arguments for and against the inclusion of intention in a definition of bullying relate to the arguments advanced in the context of aggression.18–21 Those who argue against inclusion maintain the weaker argument. Without its inclusion, joking, jovial teasing, and inadvertent/accidental behaviors are captured in an overly broad meaning of bullying. In the same way, inadvertent online behaviors and common behaviors such as playful cyberteasing and cyberjoking, which do not require the elements of repetition, power imbalance, or in- tention to cause harm to the target, would be labeled ag- gressive cyber acts. An exclusion of the element of intention suggests that acts carried out in an attempt to cause a victim harm will not be deemed aggressive if harm does not mate- rialize.19 To differentiate behaviors, acts (online or otherwise) should only be deemed aggressive where the action was di- rected toward the goal of producing a negative consequence for a victim which that victim is motivated to avoid.

Intention in the Cyberbullying Context

Direct cyberbullying

It is necessary to consider the element of intention in re- lation to direct and indirect cyberbullying. Direct cyberbul- lying requires the perpetrator to engage in a course of conduct to fulfill the criterion of repetition. The repetitive conduct, in turn, may illustrate an intention to harm, as the conduct is not an inadvertent or isolated incident. Behavior demonstrated as a course of conduct is likely to implicate the perpetrator as having the desire and the knowledge that the victim would be harmed by the conduct. In this manner, repetition and intention may be considered related elements. The context of the conduct and form of words, images or sound used need to be taken into account.

Indirect cyberbullying

Let us presume that a perpetrator has posted material via ICTs into a public area of cyberspace. Brenner and Rehberg appropriately posit that two issues unique to indirect cyber- bullying arise in that instance. The first issue relates to the extent to which the cyberbully intentionally directed the on- line communication at the victim; the second issue relates to the extent to which the cyberbully intended the communi- cation to have a negative impact (harm) the victim.8

Thus, where material is posted in a public forum, it may be possible to determine the extent to which the cyberbully in- tentionally directed the online communication at the victim. For example, addressing the victim in the public forum by name may be considered reasonably strong evidence that the cyberbully intentionally directed the communication at the victim. There may be instances, however, where it is much more difficult to make this determination. Where material is

CYBERBULLYING: THE CHALLENGE TO DEFINE 287

posted to a public forum, but either restricted to a particular audience by virtue of privacy settings, or posted to an area of cyberspace where it would not readily come to the victim’s attention, establishing intention becomes problematic. The perpetrator has posted the material to an area where it is unlikely to become known to the victim.

Where the victim is deemed to be the intended target of the aggression, particularly hostile/malicious material is more likely to be deemed material that is intended to have a negative impact on the victim. Where the material posted is not of the type that is clearly intended to harm the victim, it will be more arduous to fulfill the criterion of intention. The context of the cyberbullying and the form of words, images or sound used will be relevant.

How Intention Could Be Established

It is clear that the subjective nature of intention can make this element difficult to establish in some instances. To assist in making a determination, it may be appropriate to take into account the age of a perpetrator.8 A younger child is likely to have a reduced capacity to appreciate the consequences of his/her actions than an adult because of a child’s less- developed stage of maturity.8 Research findings suggest that the relationship between victim and perpetrator plays an im- portant role in the way conduct is interpreted.15 Others suggest it is a victim’s perception of the incident rather than the in- tention of the other that should be considered.12,20 It is the view of the author that intention is best determined based on how a reasonable person would perceive the perpetrator’s conduct.

The reasonable person approach is an objective test that measures the conduct of the perpetrator against conduct of a hypothetical reasonable person placed in a similar position as the victim. This approach is widely adopted in both criminal law and law of torts. In Australia, it is not uncommon for offences to be defined by the reasonable person test in relation to harassment or workplace bullying.22 Applying the reason- able person standard to the cyberbullying context would set some boundaries to an establishing intention. It would serve as a practical tool for diminishing the level of subjectivity from a finding of intention. By introducing the reasonable person standard as an objective measurement of conduct, intention becomes a practicable element of the definition.

A Suggested Descriptive Definition

In light of the above, an appropriate descriptive definition is suggested:

Cyberbullying involves the use of ICTs to carry out a series of acts as in the case of direct cyberbullying, or an act as in the case of indirect cyberbullying, intended to harm another (the victim) who cannot easily defend him or herself.

Direct cyberbullying involves a perpetrator repeatedly di- recting unwanted electronic communications to a victim who cannot easily defend him or herself with the intent to harm the victim.

Indirect cyberbullying involves directing a single or repeated unwanted electronic communications to a victim who cannot easily defend him or herself with the intent to harm the victim.

An intention to harm is established where a reasonable person, adopting the position of the victim and having regard to all the circumstances, would regard the series of acts or an act as acts or an act intended to harm to the victim.

Electronic communication includes (but is not limited to) any transfer of signs signals, writing, images, sounds, data transferred whole or in part by wire, radio, a photo electronic or photo optical system, including electronic mail, Internet communications, instant messages, and facsimile communi- cations.

Harm refers to emotional harm. The elements of power imbalance, aggression, and inten-

tion (which are intrinsically linked) and the use of ICTs are all included in the above description. The altered meaning of repetition in the indirect cyberbullying context is captured by differentiating between direct and indirect cyberbullying.

Conclusion

To address the phenomenon of cyberbullying, it is imper- ative to know what it is. A workable definition is crucial. This article has presented a model definition that encompasses both direct and indirect cyberbullying. The definition high- lights the importance and applicability of traditional elements of bullying in relation to cyberbullying. Traditional face-to- face bullying requires a course of conduct to be established before the criterion of repetition is satisfied, and this aspect is retained in the model definition. The meaning of repetition in the cyber context is, however, altered in relation to indirect cyberbullying because of the public nature of the material once it enters the public online domain. Power imbalance is an equally essential criterion to cyberbullying and is pre- served in the cyber context. The elements of intention and aggression are intrinsically linked and are fundamental as- pects of this proposed cyberbullying definition.

Disclosure Statement

No competing financial interests exist.

References

1. Espelage D, Swearer S. Research on school bullying and victimization: what have we learned and where do we go from here? School Psychology Review 2003; 3:365–383.

2. Monks C, Smith P. Definitions of bullying: age differences in understanding of the term, and the role of experience. British Journal of Development Psychology 2006; 24:801–821.

3. Cross D, Shaw T, Hearn L, et al. (2009) Australian covert bullying prevalence study. Edith Cowan University, Perth: Child Health Promotion Research Centre.

4. Olweus D. Familial and temperamental determinants of aggressive behavior in adolescent boys: a causal analysis. Developmental Psychology 1980; 16:644–660.

5. Rigby K. Effects of peer victimisation in schools and per- ceived social support on adolescent well-being. Journal of Adolescence 2000; 23:57–68.

6. Smith PK, Mahdavi J, Carvalho M, et al. Cyberbullying: its nature and impact in secondary school pupils. Journal of Child Psychology and Psychiatry 2008; 49:376–385.

7. Hinduja S, Patchin JW. (2009) Bullying beyond the schoolyard: preventing and responding to cyberbullying. Thousand Oaks, CA: Corwin Press.

8. Brenner SW, Rehberg M. ‘‘Kiddie Crime’’? The utility of criminal law. First amendment law review 2009; 8:1–85.

9. Patchin JW, Hinduja S. Bullies move beyond the schoolyard: a preliminary look at cyberbullying. Youth Violence & Ju- venile Justice 2006; 4:148–169.

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10. Li Q. New bottle but old wine: a research of cyberbullying in schools. Computers in Human Behavior 2007; 23:1777–1791.

11. Olweus D. Bully/victim problems in school: knowledge base and an effective intervention program. Irish Journal of Psychology 1997; 18:170–190.

12. Nocentini A, Calmaestra J, Schultze-Krumbholz A, et al. Cyberbullying: labels, behaviors and definition in three european countries. Australian Journal of Guidance and Counselling 2010; 20:129–142.

13. Slonje R, Smith PK. Cyberbullying: another main type of bullying? Scandinavian Journal of Psychology 2008; 49:147– 154.

14. Katzer C, Fetchenhauer D, Belschak F. Cyberbullying: who are the victims? A comparison of victimization in Internet chatrooms and victimization in school. Journal of Media Psychology 2009; 21:25–36.

15. Vandabosch H, Cleemput K. Defining cyberbullying: a qualitative research into perceptions of youngsters. Cy- berpsychology & Behavior 2008; 11:499–503.

16. Dooley J, Pyzalski J, Cross D. Cyberbullying versus face-to- face bullying: a theoretical and conceptual review. Journal of Psychology 2009; 217:182–188.

17. Smith PK, Cowie H, Olafsson RF, et al. Definitions of bul- lying: a comparison of terms used, and age and gender differences, in a fourteen-country international comparison. Child Development 2002; 73:1119–1133.

18. Geen RG. (2001) Human aggression. Buckingham, England; Philadelphia, PA: Open University Press.

19. Baron RA. (1977) Human aggression. New York: Plenum Press. 20. Tattum D. A whole-school response: from crisis manage-

ment to prevention. Irish Journal of Psychology 1997; 18: 221–232.

21. Guerin S, Hennessy E. Pupils’ definitions of bullying. European Journal of Psychology of Education 2002; 17:249– 261.

22. Equal Opportunity Act 1984 (SA), s 87(9) (Austl); Sex Dis- crimination Act 1984 (Cth), s 28A(1) (Austl.); Criminal Code Act 1995 (Cth), s 474.17 (1)(b) (Austl.); Occupational Health Safety and Welfare Act 1986 (SA), s 55 A(1) (Austl.).

Address correspondence to: Colette Langos

Centre for Regulation and Market Analysis and School of Law

University of South Australia GPO Box 2471

Adelaide South Australia 5001

Australia

E-mail: [email protected]

CYBERBULLYING: THE CHALLENGE TO DEFINE 289

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Psychology of Popular Media Culture

Anonymously Hurting Others Online: The Effect of Anonymity on Cyberbullying Frequency Christopher P. Barlett Online First Publication, November 4, 2013. doi: 10.1037/a0034335

CITATION Barlett, C. P. (2013, November 4). Anonymously Hurting Others Online: The Effect of Anonymity on Cyberbullying Frequency. Psychology of Popular Media Culture. Advance online publication. doi: 10.1037/a0034335

Anonymously Hurting Others Online: The Effect of Anonymity on Cyberbullying Frequency

Christopher P. Barlett Gettysburg College

Cyberbullying (CB) has recently become a significant issue in today’s society. Given the myriad negative consequences to the cyber-victim, it is important to determine what variables predict CB frequency. Based on broader psychological and communication theory, I predict that anonymity will (a) directly predict CB frequency, (b) moderate the relation between positive attitudes toward CB and CB frequency, and (c) mediate the relation between instant messaging frequency and CB behavior. Participants (N � 181) completed measures designed to assess these aforementioned variables. Results showed that positive attitudes toward CB, CB reinforcement, and anonymity strongly predicted CB frequency. Furthermore, moderation tests confirmed that CB was highest when positive attitudes and anonymity were both high. Finally, mediation tests revealed anonymity mediated the relation between instant messaging frequency and CB behav- ior. These results are important at elucidating what variables predict CB to hopefully inform intervention efforts aimed at reducing CB.

Keywords: cyberbullying, anonymity, attitudes

Violent and aggressive behaviors are not new behavioral phenomena. However, the method by which aggressive acts are delivered has changed with increased technology. For exam- ple, Anderson and Huesmann (2003) stated that violent behaviors rose dramatically with the ac- cessibility of handguns. In today’s technology- based culture, individuals are now turning to electronic means (e.g., Internet, texting) to harm others, termed cyberbullying (CB) (defined as, “. . . the use of information and communication technologies such as e-mail, cell phone and pager text messages, instant messaging, defam- atory personal Web sites, and defamatory online personal polling Web sites to support deliberate, repeated, and hostile behavior by an individual or group, that is intended to harm others” [cited in Li, 2007, p. 1779]). CB is a serious societal issue owing to the extensive harm it can cause

the victim. Indeed, research has shown that those who are cyber-victimized are at risk for heightened negative psychological (fearful [Be- ran & Li, 2005], depressed [Patchin & Hinduja, 2006], suicide ideation [Hinduja & Patchin, 2010], and anger [Beran & Li, 2005]) and be- havioral (drug abuse [Hinduja & Patchin, 2008] and poor school grades [Beran & Li, 2007]) outcomes.

To date, the majority of the CB literature has focused on the victim. Although important, a better understanding of the predictors of CB is needed to not only understand why people harm others using electronic methods, but also to inform interventions aimed at reducing CB. Relative to the literature focusing on the cyber- victim, there is a paucity of research testing what factors enhance or reduce the likelihood of CB. Consistent with broader aggression theory, research has shown positive correlations be- tween CB frequency and traditional bullying frequency (Smith et al., 2008), normative ag- gressive beliefs (Ang, Tan, & Mansor, 2011), and low empathy (Ang & Goh, 2010; Steffgen, Konig, Pfetsch, & Melzer, 2011). However, many additional factors can influence CB, such as one’s attitudes toward CB, reinforcement, and identification. The objective of the current study is to elucidate on these aforementioned

Christopher P. Barlett, Department of Psychology, Get- tysburg College.

Correspondence concerning this article should be ad- dressed to Christopher P. Barlett, Department of Psychol- ogy, Gettysburg College, Campus Box 0407, 300 North Washington Street, Gettysburg, PA 17325. E-mail: [email protected]

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Psychology of Popular Media Culture © 2013 American Psychological Association 2013, Vol. 2, No. 4, 000 2160-4134/13/$12.00 DOI: 10.1037/a0034335

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factors. In doing so, the results of this study may be important in indentifying the predictors of CB to guide intervention efforts at reducing this harmful “newer” form of aggression.

The Role of Anonymity

In the online world, an aggressor will not be face-to-face with their victim. This would imply that anonymity should increase CB behavior; however, research has shown that traditional bullying is more common than CB (Olweus, 2012), and traditional bullies can harm others using covert aggressive tactics (e.g., gossiping, rumor spreading). Therefore, it is possible that anonymity can increase both traditional bully- ing and CB. Indeed, literature from broader social psychological and communication theo- ries have shown that anonymity is related to aggressive behavior (Diener, 1976; see also An- derson & Bushman, 1997) owing to deindividu- ation processes. However, the focus of the cur- rent study was to understand what variables may predict CB behavior, and there is a paucity of research empirically testing anonymity’s contribution.

In the mediated world, anonymity is pro- nounced because a) the aggressor is not as iden- tifiable and can use fake usernames, b) the bully does not need to have a previous relationship with the victim, and c) no physical scars or marks are inflicted on the victim from the bully. In other words, the aggressor’s anonymity may enhance the frequency of which CB (vs. tradi- tional bullying) occurs. It should be noted that anonymity is not a necessary condition for CB. It is likely the case that the cyber-victim also knows the cyberbully; however, that is not al- ways the case. Furthermore, a cyberbully may not truly be anonymous. Phone numbers can be traced and IP addresses can be identified, lead- ing to low anonymity. However, feeling anon- ymous and being anonymous are not identical and even if the cyber-victim can identify their aggressor, the bully may still feel anonymous, which may predict CB frequency.

Surveys using adolescent samples have indi- cated that 29% of adolescent cyber-victims could not identify their aggressor (Patchin & Hinduja, 2006). Furthermore, in 2011, the Cen- ter for Disease Control (CDC, 2011) conducted a survey of adolescents who reported being cyberbullied. Their report indicated that of

those cyberbullied, 67% of the CB occurred on instant messenger (IM), whereas only 17% oc- curred via text messaging and 21% using e-mail (percentages were not mutually exclusive). IM may enhance anonymity to the aggressor through the use of handles (made up electronic names) rather than one’s actual name, compared with texting or e-mailing where one’s name (and phone number/e-mail address) are easily accessible, decreasing the likelihood of ano- nymity. Although, it is hypothesized that IM frequency will better predict CB than texting or e-mail frequency, a cyberbully can create a fake e-mail address to attack others online. However, using IM as a means to aggress may still feel anonymous relative to e-mail frequency. No research has explicitly tested this claim and will be tested in the current study.

Theoretical Predictors of CB

To date, several researchers have suggested that one defining characteristic that differenti- ates CB from traditional bullying is enhanced anonymity for the aggressor (Li, 2007; Smith et al., 2008; Vandebosch & Van Cleemput, 2008). Indeed, Herring (2001) stated that the perceived anonymity afforded in the mediated world in- creases the likelihood of aggressive and hostile acts, as evident by the research showing that the majority of cyber-victims do not know their aggressor (Kowalski & Limber, 2007). Despite this wealth of research and speculation regard- ing anonymity’s influence on CB, there is a paucity of research empirically testing these relations and few theoretical postulations to make informed predictions to suggest how an- onymity is related to CB.

Recently, Barlett and Gentile (2012) tested a theoretical model that focused on the distal learning processes involved in CB. Drawing on broader social–cognitive learning theories of aggression (e.g., General Aggression Model; Anderson & Bushman, 2002), their model pos- its that each successful positively reinforced instance of CB is a learning trial. Continued learning is related to the development of learned knowledge structures that predict CB. In other words, Barlett and Gentile (2012) posited that when one continues to cyberbully another, the aggressor will ascertain certain knowledge re- garding the outcomes. Barlett and Gentile (2012) postulated and found evidence to sug-

2 BARLETT

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gest that continued and successful learned CB is related to the development of two specific learned associations: anonymity and the lack of power differential. The former construct (ano- nymity) is the focus of the current research. According to Barlett and Gentile (2012), cyber- bullies believe that they are perceived as anon- ymous in the mediated world after they success- fully harm another several times. Also, in their model, Barlett and Gentile (2012) found that perceived anonymity directly predicts both CB frequency and positive attitudes toward CB. Mediation tests of their model showed that anonymity is related to CB frequency because of positive attitudes toward CB (the mediator). In other words, perceived anonym- ity predicts the development of positive atti- tudes toward CB, which in turn predicts CB frequency (see Figure 1).

As seen in Figure 1, anonymity can serve as both a mediator and moderator when predicting CB. Notably, when learning is the primary in- dependent variable, anonymity can serve as a mediator in the path to CB frequency. However, anonymity can also serve as a moderator vari- able in the relation between positive attitudes toward CB and CB frequency. Thus, depending on what part of the model one is addressing, anonymity serves different roles. The current study will test both the mediating role of ano- nymity in the relation between media usage and CB frequency, as well as the moderating role of anonymity in the relation between positive atti- tudes toward CB and CB frequency. The inves- tigation of how anonymity is related to CB frequency is of theoretical importance. Barlett and Gentile (2012) showed that anonymity is an important predictor in CB frequency without testing whether anonymity mediates or moder-

ates the relations predicted in the Barlett and Gentile (2012) model. This is the purpose of the current study.

Overview of the Current Study

The purposes of the study was to further test and validate the Barlett and Gentile (2012) model focusing on how anonymity is related to CB frequency. It is hypothesized that instant messaging (rather than e-mail) would be related to CB and anonymity would mediate this rela- tionship. Furthermore, anonymity should mod- erate the relation between positive attitudes to- ward CB and CB frequency.

Method

Participants

Data were collected in the Fall of 2010. One hundred and eighty-one (57% female) under- graduate students from a large Midwestern Uni- versity participated in the study for partial course credit in their psychology classes. The average age of the sample was 19.47 (SD � 1.56) years. The majority (79%) were Cauca- sian. The majority of participants were in their first or second year of undergraduate education (80%).

Materials and Procedure

On completion of the informed consent, par- ticipants completed the following question- naires and then were thanked and fully de- briefed.

CB frequency. The past research in the CB literature has used dozens of different question-

Anonymity

Posi�ve A�tudes towards

Cyberbullying

Cyberbullying Frequency

Learned Cyberbullying

Behaviors

Figure 1. Extensions of the Barlett and Gentile (2012) model.

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naires to assess CB frequency. According to Rivers and Noret (2010), such diversity in mea- sures is one (of several) reason why CB fre- quency percentages vary from study to study. The diverse numbers of measures each differ in important respects. For instance, some research- ers use a Likert-like rating scale (e.g., Ybarra, Diener-West, & Leaf, 2007), whereas others use dichotomous estimates of CB (e.g., Li, 2007). Furthermore, some researchers define CB to the participant (e.g., Li, 2007), whereas others do not (e.g., Ang & Goh, 2010). Overall, there is no current “gold standard” measure of CB fre- quency. The CB frequency questionnaire used in the current study (see below for details) was used because it measured CB behavior ade- quately; it was based on a valid measure of media exposure of TV, movie, and video game violence (Gentile, Lynch, Linder, & Walsh, 2004). The CB scale used in the current study had participants indicate their level of CB with- out being explicit regarding what was being measured, akin to other measures that did not use definitions (although participants could probably infer what was being measured).

For the purposes of the current research, CB frequency was calculated using an adapted ver- sion of the Media Habits Questionnaire (Gentile et al., 2004). Participants were instructed to list their three favorite Web sites. For each Web site they listed, they rated it on how often they visited the Web site, how often they write mean messages to others on this Web site, and how often they posted mean comments about others on the Web site on a 1 (rarely) to 5 (all the time) rating scale.1 If participants only listed two, rather than three, favorite Web sites, for exam- ple, then the items designed for the third Web site were assigned a value of zero (see Anderson & Dill, 2000). The frequency rating was multi- plied by the write mean messages rating and then averaged across all three Web sites to get a CB via writing mean messages estimate. The same formula was applied to the posting mean comments ratings. These two estimates (posting mean messages and writing mean messages) were averaged to produce an estimate of CB via the Internet (� � .87). Higher scores indicate more CB. Akin to other measures of CB, the data for this were positively skewed; however, given the sample size, no corrections (e.g., log transforming) were done.

Traditional bullying. The Ybarra et al. (2007) traditional bullying scale was used to assess frequency of traditional, or face-to-face, bullying. This is a three-item questionnaire that asks participants how often they aggressed against others using a 1 (never) to 6 (everyday/ almost everyday) rating scale (� � .75). A sample item includes, “Made rude comments or mean comments to anyone.” The three items were summed such that higher scores indicated higher reported frequency of face- to-face bullying.

Positive Attitudes Toward CB. The re- searcher-created Positive Attitudes toward Cy- berbullying questionnaire (Barlett & Gentile, 2012) was used (� � .95). This is a 20-item questionnaire that asks participants their level of agreement with the items on a 1 (strongly disagree) to 5 (strongly agree) rating scale. A sample item includes, “It is OK to bully others online if they deserve it.” These items were summed, such that higher scores indicate more positive attitudes toward CB.

Anonymity. The researcher-created Atti- tudes toward Anonymity questionnaire (Barlett & Gentile, 2012) was used (� � .71). This is a five-item questionnaire that asks participants their level of agreement with the items on a 1 (strongly disagree) to 5 (strongly agree) rating scale. A sample item includes, “I feel comfort- able sending mean text messages or e-mails to anybody no matter if I know them or not.”

1 The original version of this questionnaire asks partici- pants to list their three favorite movies, TV shows, and video games. Thus, the adapted version used here only asked participants to list their three favorite Web sites. The term “Web site” was not defined for participants; however, that is a trivial absence. The primary focus for using this questionnaire was to ascertain how frequently participants visited the Web site and how often they cyberbullied using this Web site. This measure afforded the researchers a wide variety of options. For instance, a score of 0 could indicate that a) the Web site participant’s visited does not allow for CB (e.g., www.iastate.edu), or b) the Web site participant’s visited does afford possible CB opportunities (e.g., www .Facebook.com; the most favored Web site in this sample), but no such behavior is reported. Conversely, if the favored Web site does afford CB opportunities, then it is likely through these two options (posting mean comments or writ- ing mean messages to others). Other methods of CB can exist on several Web sites that are not measured here (e.g., social exclusion, posting videos, etc.); however, based on the definition of CB used in this study and knowledge that social networking Web sites would most likely be favored over other Web sites, this was a valid measure of CB.

4 BARLETT

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These items were summed, such that higher scores indicate more positive attitudes toward anonymity in CB.

Demographic questionnaire. A demo- graphic questionnaire was used to assess sex, ethnicity, year in school, age, and other relevant demographic information.

Media frequency. To estimate weekly av- erages of instant messaging and e-mailing, an adapted version of the Media Habits Question- naire (Gentile et al., 2004) was used.2 To com- pute weekly e-mail frequency, participants in- dicated how many hours they e-mailed others (and checked e-mail) on an average weekday and weekend day during the following times: 6 a.m. to noon, noon to 6 p.m., 6 p.m. to midnight, and midnight to 6 a.m. The weekday times were added and multiplied by five. This estimate was added to the product of the week- end days multiplied by two. This formula was applied to instant messaging time. Thus, the range of possible scores was from 0 to 168 with higher scores indicating more frequency. Al- though results showed that these data were pos- itively skewed, no data transformations were conducted, because with a high sample size, the population distribution of scores approximates a normal distribution.

Results

Zero-Order Correlations

Table 1 displays the zero-order correlations between relevant variables. As expected, CB

frequency was positively correlated with posi- tive attitudes toward CB (r � .60, p � .001), perceived anonymity (r � .52, p � .001), and instant messaging frequency (r � .40, p � .001). CB was uncorrelated with e-mail fre- quency. This latter finding suggests that instant messaging is likely to be the method by which CB is manifested, rather than e-mail. Indeed, instant messaging frequency was also positively correlated with anonymity (r � .20, p � .001) and positive attitudes toward CB (r � .23, p � .001). E-mail frequency was uncorrelated with these aforementioned variables (rs � .11, ns).

Difference in Correlation Test

Prior to testing the moderating and mediating influence of anonymity in the relation between CB, it was of theoretical importance to show evidence that perceived anonymity was more strongly associated with CB than traditional bullying. A difference in correlation test for dependent samples was conducted (Cohen & Cohen, 1983). Results show a significant differ- ence, t(177) � 2.99, p � .05, in the magnitude of the relation between CB and anonymity (r � .52) and traditional bullying and anonymity (r � .30), while controlling for the colinearity of traditional bullying and CB (r � .31). This suggests that although the relation between tra- ditional bullying and anonymity was significant, this relation was stronger when CB was the predictor.

Moderation Test

Next, moderation tests were conducted to test the hypotheses of the current study. The Hayes and Matthes (2009) moderation MACRO for SPSS was used. This analysis tests the relation- ship between the independent variable (positive attitudes toward CB) and the dependent variable (CB frequency) at high (�1 SD) and low (�1 SD) level of the moderator (anonymity).

Results showed significant moderation, b � .01, se � .002, t(171) � 3.883, p � .001. The relation between positive attitudes toward CB and CB was significant when anonymity was high, b � .09, se � .01, t(171) � 6.14, p �

2 This measure was adapted by asking participants how many hours they were on IM and e-mail. The original version asked identical questions, but about video game use not IM or e-mail.

Table 1 Correlations Between Relevant Variables

1 2 3 4 5 6 7

1 — 2 .52�� — 3 .60�� .69�� — 4 .40�� .20�� .23�� — 5 .04 �.03 �.03 .53�� — 6 .31�� .30�� .40�� .09 �.02 — 7 .10 .07 .21�� .00 �.005 .17� — Mean 4.61 10.57 34.67 8.62 15.57 5.44 �0.16 SD 2.81 4.12 15.47 19.20 16.79 2.53 0.99

Note. 1 � Cyberbullying; 2 � Anonymity; 3 � Positive Attitudes toward Cyberbullying; 4 � Instant Messaging Frequency; 5 � E-mail Frequency; 6 � Traditional Bully- ing; 7 � Sex (1 � male; �1 � female). � p � .05. �� p � .01.

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.001, but not when anonymity was low b � .03, se � .02, t(171) � 1.66, p � .05 (see Figure 2).

Path Model

To test the mediating mechanisms within the Barlett and Gentile (2012) model, path analysis using MPLUS was used. The raw data were used for analysis (rather than inputting the correlation or covariance matrix). Instant mes- saging and e-mail frequency were correlated independent variables predicting anonymity, positive attitudes toward CB, and CB fre- quency. Anonymity and positive attitudes to- ward CB also predicted CB frequency. Finally, anonymity predicted positive attitudes toward CB (see Figure 3). Because all possible paths and correlations were estimated, the estimated variance–covariance matrix was identical to the actual variance–covariance matrix, making the model a perfect fit of the data (i.e., no degrees of freedom to estimate model fit indices; �2 � 0.00, Comparative Fit Index (CFI) � 1.00, Tucker-Lewis Index (TLI) � 1.00, Root Mean Square Error of Approximation (RMSEA) � 0.00, Standardized Root Mean Square Residual (SRMR) � 0.00, which is better than the base- line model in which all variables are uncorre- lated, �2 � 241.385 (df � 9), p � .00001).

Examination of the path coefficients showed that instant messaging frequency (� � .34, p � .001), positive attitudes toward CB (� � .41, p � .001), and anonymity (� � .16, p � .001) positively predicted CB frequency. E-mail fre- quency was negatively related to CB frequency (� � �.13, p � .05). Both e-mailing and instant messaging frequency predicted anonymity (� � �.18, p � .04; � � .29, p � .001, respectively); however, only instant messaging frequency (not e-mail frequency) predicted positive attitudes toward CB (� � .14, p � .04). Finally, ano- nymity predicted positive attitudes toward CB (� � .66, p � .001). The correlation between e-mail and IM frequency was significant, r � .53, p � .001. Indirect tests confirmed that the path from instant messaging frequency to ano- nymity to positive attitudes toward CB to CB frequency was significant (Indirect b � .08, t � 2.96, p � .01). The same indirect test involving e-mail frequency showed the opposite pattern (Indirect b � �.05, t � �1.97, p � .05).3

E-mail Versus Instant Messaging Frequency

The previous results show strong support for the importance of how different media outlets (i.e., IM and e-mail) influence anonymity, which, in turn, predicts CB frequency. How- ever, some may suggest that these results are driven by the fact that some individuals may simply use IM more frequently than e-mail. If true, such an explanation may provide an alter- native explanation to the previous findings. To test this, a repeated measures ANOVA was run to compare the frequency for IM to e-mail. Results showed that people spent significantly, F(1, 183) � 28.70, p � .001, partial 2 � .14, more time on e-mail (M � 15.57, SD � 16.79) than IM (M � 8.62, SD � 19.20). This pro- vides further support for the findings in the path model.

Conclusion

Overall, results support the hypotheses of the current study and show strong support that an- onymity is an important predictor of CB behav- ior. Consistent with the learning postulations of the Barlett and Gentile (2012) model, anonym- ity was both a mediator in the relation between instant messaging frequency and CB, but also a moderator in the relation between positive atti- tudes toward CB and CB frequency. This sug- gests that when individuals learn that CB is anonymous and the negative consequences are rare (given said anonymity), CB is likely to occur.

General Discussion

CB is an emerging societal problem. As sug- gested by Barlett and Gentile (2012), the liter- ature in this domain has been mostly descriptive and atheoretical. The purpose of the current research was to further our understanding of what variables predict CB behaviors in an at- tempt to (a) further advance theory by testing

3 Postexamination of the path coefficients showed one nonsignificant path (positive attitudes toward CB regressed onto e-mail frequency; see Figure 3). This path was set to 0 to estimate model fit indices. Results showed that this model was a good fit for the data (�2 � 1.38 (df � 1), p � .24, CFI � 1.00, TLI � 0.99, RMSEA � 0.05, SRMR � 0.01).

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how anonymity is important to CB, (b) eluci- date on the predictors related to CB behaviors, and (c) use these findings to help inform future interventions aimed at reducing CB.

CB and Theory

Results from the current study support the postulations of the Barlett and Gentile (2012)

0.00

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12.00

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Figure 2. The moderating influence of anonymity in the relation between positive attitudes toward CB and CB frequency.

Instant Messaging Frequency

Emailing

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Positive Attitudes of

Cyberbullying Cyberbullying

Frequency

.34***

.41***

.29***

-.18*

.53***

Anonymity .67***

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.14*

-.13* -.08

Figure 3. Mediated path model. � p � .05, ��� p � .001. Single headed arrows are regression coefficients whereas double headed arrows are correlations. Dashed lines indicate nonsignif- icant (p � .05) relations.

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model. This model posits that with continued CB experiences, individuals are likely to learn that they are more likely to be anonymous. Accompanied with the lack of power differen- tial, such anonymity leads to the development of positive attitudes toward CB, which predicts subsequent CB behavior. Support for the role of anonymity in CB was found in myriad ways. First, results showed that anonymity was corre- lated with both positive attitudes toward CB and CB frequency. Second, results showed that an- onymity moderated the relation between posi- tive attitudes toward CB and CB behavior. This suggests that CB is more likely when positive attitudes are high and anonymity is high. Third, anonymity significantly mediated the relation between instant messaging frequency and CB. This suggests that the reason why instant mes- saging frequency was positively related to CB was because individuals feel anonymous. Fi- nally, e-mail frequency was negatively related to anonymity and positive attitudes toward CB whereas instant messaging frequency was pos- itively related to such attitudes and behaviors. If theory is correct, this finding can be explained by the hypothesis that e-mail may be more identifiable than instant messaging.

Although these results regarding the impor- tance of anonymity are important to understand- ing the variables that predict CB behavior, the questionnaire used in the current research mea- sures anonymity attitudes. It has been argued that perceived anonymity may be more impor- tant than actual anonymity; however, that is speculative and future research should test this empirically. In the real-world, a cyberbully’s anonymity is not assured especially when be- haviors escalate to very aggressive or violent behaviors. The current study provided empirical data to suggest that perceived anonymity is an important contributing factor to predict CB, and, clearly, future work is needed to test under what conditions perceived versus real anonym- ity differentially affects such social behaviors.

Limitations and Future Research

Like all psychological research, limitations do exist that need be studied in future research. First, these data are limited by their correla- tional nature, and causal claims regarding the relations in this study cannot be made. Future research should use either an experimental or

longitudinal research design to test these hy- potheses. However, recent work by Barlett and Gentile (2012) used a longitudinal design to test similar hypotheses regarding the causal mecha- nisms of CB, and results were consistent to what was reported in this study. However, these studies have their limitations too. For example, Barlett and Gentile (2012) only used a two- month lag between scale administrations in their longitudinal study. Future research is des- perately needed in this domain.

Second, the current study used a college-aged sample. It could be argued that the frequency of CB peaks during junior high and high school years; however, no published work has tested such age comparisons. However, if significant relations can be found that test important theo- retical postulations in a population that uses CB less frequently, then it could be argued that the relations would be stronger for adolescents. However, future research should test these re- lations on adolescents to see whether the rela- tions reported herein with a college-aged sam- ple are similar or different.

Third, the measure of CB behavior was lim- ited to only measuring CB over the Internet. A complete definition of CB should consist of other means of technology (text messaging, over video game consoles, etc.). However, text messaging is not as anonymous as other forms of media (e.g., instant messaging), and the pur- pose of the study was to use a measure of CB that would have variance captured by the ano- nymity construct. Under certain circumstances, any social media communication can be anon- ymous (e.g., phone numbers can be withheld, video gamers can create avatars, people can create e-mail accounts with fake names, etc.). Future research should attempt to create and validate a measure of anonymity across various platforms to get a more comprehensive measure of anonymity in the cyber-world. Additionally, the measure of CB used in the current study is similar to other validated CB scales that ask how frequently people harm others while “on- line” (Ybarra et al., 2007). Future research should use other CB questionnaires to deter- mine whether the results replicate, and based on past research it should. For instance, Barlett and Gentile (2012) used the Ybarra et al. (2007) measure of CB and showed correlations similar to those presented in Table 1.

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Fourth, related to the measure of CB used in the current study, no definitions or content of “mean messages” were provided. Further for ethical reasons, participants were not asked to indicate exactly what they would write if they indicated they had, in fact, written a mean on- line message. It was presumed that participants who score high on CB using this measure may not even remember every mean message or post. However, writing what participants con- sider mean messages fits the definition of CB.

Finally, future research should attempt to measure the impact of anonymity (or perceived anonymity) with other face-to-face measures. Olweus (2012) suggested that traditional bully- ing and CB are similar to one another; however, the reported frequency of CB is lower than traditional bullying. If that is true, then per- ceived anonymity should correlate with both forms of bullying to the same degree. This would specifically test whether anonymity is one defining characteristic of online versus of- fline aggression. However, caution must be used in doing such an analysis, because of (a) the high correlation between CB and traditional bullying (Barlett & Gentile, 2012), (b) the dif- ficulty in measuring anonymity given the constantly shifting online-world, and (c) the dif- ficulty in differentiating between traditional bullying from an anonymous source from CB from a known source. This is clearly an area of future work that needs attention. Furthermore, specifically related to the previous comment, future work should also attempt to develop valid and reliable measures of perceived anonymity (rather than attitudes toward anonymity) that can be assessed at the time the CB occurs.

Final Comments

Examining the predictors of CB is important. If such predictors can be tested, results repli- cated, and theory enhanced, then interventions can be formulated to reduce CB behavior. The current study is an important step in elucidating on what factors predict CB processes. It is clear that attitudes toward anonymity and CB rein- forcement are strong predictors of CB that should be targeted in future work and interven- tions.

References

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Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53, 27– 51. doi:10.1146/annurev.psych.53.100901.135231

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9CYBERBULLYING

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Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementa- tions. Behavior Research Methods, 41, 924–936. doi:10.3758/BRM.41.3.924

Herring, S. (2001). Gender and power in online com- munication. Retrieved from https://scholarworks. iu.edu/dspace/bitstream/handle/2022/1024/WP01- 05B.html. Retrieval date: 8-22-13.

Hinduja, S., & Patchin, J. W. (2008). Cyberbullying: An exploratory analysis of factors related to of- fending and victimization. Deviant Behavior, 29, 129–156. doi:10.1080/01639620701457816

Hinduja, S., & Patchin, J. W. (2010). Bullying, cy- berbullying, and suicide. Archives of Suicide Re- search, 14, 206–221. doi:10.1080/13811118.2010 .494133

Kowalski, R. M., & Limber, S. P. (2007). Electronic bullying among middle school students. Journal of Adolescent Health, 41, S22–S30. doi:10.1016/j .jadohealth.2007.08.017

Li, Q. (2007). New bottle but old wine: A research of cyberbullying in schools. Computers in Human Behavior, 23, 1777–1791. doi:10.1016/j.chb.2005 .10.005

Olweus, D. (2012). Cyberbullying: An overrated phenomenon? European Journal of Developmen- tal Psychology, 9, 520 –538. doi:10.1080/ 17405629.2012.682358

Patchin, J. W., & Hinduja, S. (2006). Bullies move beyond the schoolyard: A preliminary look at cy-

berbullying. Youth Violence and Juvenile Justice, 4, 148–169. doi:10.1177/1541204006286288

Rivers, I., & Noret, N. (2010). ‘I h 8 u’: Findings from a five-year study of text and email bullying. British Educational Research Journal, 36, 643– 671. doi:10.1080/01411920903071918

Smith, P. K., Mahdavi, J., Carvalho, M., Fisher, S., Russell, S., & Tippett, N. (2008). Cyberbullying: Its nature and impact in secondary school pupils. Journal of Child Psychology and Psychiatry, 49, 376–385. doi:10.1111/j.1469-7610.2007.01846.x

Steffgen, G., Konig, A., Pfetsch, J., & Melzer, A. (2011). Are cyberbullies less empathic? Adoles- cents’ cyberbullying behavior and empathic re- sponsiveness. Cyberpsychology, Behavior, and So- cial Networking, 14, 643–648. doi:10.1089/cyber .2010.0445

Vandebosch, H., & Van Cleemput, K. (2008). Defin- ing cyberbullying: A qualitative research into the perceptions of youngsters. Cyberpsychology and Behavior, 11, 499 –503. doi:10.1089/cpb.2007 .0042

Ybarra, M. L., Diener-West, M., & Leaf, P. J. (2007). Examining the overlap in Internet harassment and school bullying: Implications for school interven- tion. Journal of Adolescent Health, 41, 42–50. doi: 10.1016/j.jadohealth.2007.09.004

Received October 31, 2012 Revision received June 17, 2013

Accepted July 2, 2013 �

10 BARLETT

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Psychological Bulletin

Bullying in the Digital Age: A Critical Review and Meta-Analysis of Cyberbullying Research Among Youth Robin M. Kowalski, Gary W. Giumetti, Amber N. Schroeder, and Micah R. Lattanner Online First Publication, February 10, 2014. http://dx.doi.org/10.1037/a0035618

CITATION Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014, February 10). Bullying in the Digital Age: A Critical Review and Meta-Analysis of Cyberbullying Research Among Youth. Psychological Bulletin. Advance online publication. http://dx.doi.org/10.1037/a0035618

Bullying in the Digital Age: A Critical Review and Meta-Analysis of Cyberbullying Research Among Youth

Robin M. Kowalski Clemson University

Gary W. Giumetti Quinnipiac University

Amber N. Schroeder Western Kentucky University

Micah R. Lattanner Duke University

Although the Internet has transformed the way our world operates, it has also served as a venue for cyberbullying, a serious form of misbehavior among youth. With many of today’s youth experiencing acts of cyberbullying, a growing body of literature has begun to document the prevalence, predictors, and outcomes of this behavior, but the literature is highly fragmented and lacks theoretical focus. Therefore, our purpose in the present article is to provide a critical review of the existing cyberbullying research. The general aggression model is proposed as a useful theoretical framework from which to understand this phenomenon. Additionally, results from a meta-analytic review are presented to highlight the size of the relationships between cyberbullying and traditional bullying, as well as relationships between cyberbullying and other meaningful behavioral and psychological variables. Mixed effects meta-analysis results indicate that among the strongest associations with cyberbullying perpetration were normative beliefs about aggression and moral disengagement, and the strongest associations with cyberbullying victimization were stress and suicidal ideation. Several methodological and sample characteristics served as moderators of these relationships. Limitations of the meta-analysis include issues dealing with causality or directionality of these associations as well as generalizability for those meta-analytic estimates that are based on smaller sets of studies (k � 5). Finally, the present results uncover important areas for future research. We provide a relevant agenda, including the need for understanding the incremental impact of cyberbullying (over and above traditional bullying) on key behavioral and psychological outcomes.

Keywords: cyberbullying, bullying, perpetration, victimization, general aggression model

As more people turn to the Internet for school, work, and social use, so too do more people turn to the Internet to take out their frustrations and aggression. One form of cyber aggression has been gaining the attention of both researchers and the public in recent years: cyberbullying. Cyberbullying is typically defined as aggres- sion that is intentionally and repeatedly carried out in an electronic context (e.g., e-mail, blogs, instant messages, text messages) against a person who cannot easily defend him- or herself (Ko- walski, Limber, & Agatston, 2012; Patchin & Hinduja, 2012). Many researchers have noted that cyberbullying is occurring at widespread rates among youth and adults, with some studies showing nearly 75% of school-age children (Juvonen & Gross, 2008; Katzer, Fetchenhauer, & Belschak, 2009) experiencing this

form of aggression at least once in the last year. The experience of cyberbullying has been linked with a host of negative outcomes for both individuals and organizations (e.g., schools), including anx- iety, depression, substance abuse, difficulty sleeping, increased physical symptoms, decreased performance in school, absenteeism and truancy, dropping out of school, and murder or suicide (Beran & Li, 2005; Mitchell, Ybarra, & Finkelhor, 2007; Privitera & Campbell, 2009; Ybarra, Diener-West, & Leaf, 2007).

Our purpose in the current article is threefold: (a) to provide a narrative review of the extant research on cyberbullying among youth,1 including a look into the prevalence and antecedents of this behavior and associated outcomes; (b) to synthesize the relation- ships among cyberbullying, cybervictimization, and meaningful behavioral and psychological variables with meta-analytic tech- niques; and (c) to critique the existing research, noting areas where findings conflict and gaps remain, thereby allowing us to provide

1 Although research has been conducted on cyberbullying in the work- place, we focus on adolescents and young adults herein. First, the majority of the research under review has focused on this particular group of individuals. Second, because so little research has examined cyberbullying in the workplace, we do not know whether the predictors/consequences of cyberbullying are similar across the different samples.

Robin M. Kowalski, Department of Psychology, Clemson University; Gary W. Giumetti, Department of Psychology, Quinnipiac University; Amber N. Schroeder, Department of Psychology, Western Kentucky Uni- versity; Micah R. Lattanner, Department of Psychology and Neuroscience, Duke University.

Correspondence regarding this article should be addressed to Robin M. Kowalski, Department of Psychology, Clemson University, Clemson, SC 29634. E-mail: [email protected]

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Psychological Bulletin © 2014 American Psychological Association 2014, Vol. 140, No. 2, 000 0033-2909/14/$12.00 DOI: 10.1037/a0035618

1

future researchers with directions where additional attention is needed.

Electronic Communication and the Importance of Studying Cyberbullying

There is no question that the Internet and related technologies have revolutionized the way that our world operates (Li, Smith, & Cross, 2012; Ybarra, Diener-West, & Leaf, 2007). The popularity of the Internet among school-age children and adolescents has become apparent to most, as nearly all youth between 12 and 17 use the Internet, and 68% of school pupils use the Internet at school (Hitlin & Rainie, 2005; Lenhart, 2010). Further, youth spend an average of about 17 hours per week on the Internet, with some spending more than 40 hours per week online (Center for Digital Future at the USC Annenberg School, 2010). Although most youth spend time communicating with their friends online, including forging new online friendships (Katzer et al., 2009), online interpersonal interactions can be particularly valuable for those who experience anxiety in face-to-face interactions.

Although the Internet has certainly provided many benefits, it may be responsible for a host of negative outcomes as well (Holfeld & Grabe, 2012). Among youth who venture online, almost a third report being contacted by someone they did not know through the Internet, and many report that this contact made them feel uncomfortable (Kowalski, Giumetti, Schroeder, & Re- ese, 2012). Other research has found a link between duration of Internet use and psychiatric symptoms, with those reporting more Internet use also experiencing more depression, obsessive compul- sion, and anxiety (Kelleci & Ìnal, 2010; Madden & Jones, 2008). The question of directionality with respect to this association clearly bears scrutiny, but the association appears robust. Further- more, the Internet has provided some with an avenue through which to commit various counterproductive behaviors, such as cyber-hacking (i.e., using the Internet to gain access to information or resources illegally), cyber-stalking (i.e., using the Internet to spy on or watch another person), and various forms of cyber aggres- sion including cyberbullying (i.e., using the Internet to harm an- other person; Kowalski, Limber, & Agatston, 2012). Additionally, some individuals may develop “pathological technology use” (PTU; Gentile, Coyne, & Bricolo, 2013). PTU refers to obsessive and addictive behaviors in response to technological media, such as the Internet or gaming, that resemble behaviors characteristic of addictions to alcohol or drugs.

Certain features of online communications, including reproduc- ibility, lack of emotional reactivity, perceived uncontrollability, relative permanence, and 24/7 accessibility, make it more likely for online misbehavior to occur (Kiesler, Siegel, & McGuire, 1984; Pearson, Andersson, & Porath, 2005). With regard to repro- ducibility, the core issue is that a person can easily copy all of his or her friends on a message or forward gossip to his or her entire address book. This reproducibility may make it easy for deviant individuals to harm others and to repeat the harm over and over again with the click of a button. Communications over the Internet also feature a lack of emotional reactivity. When people commu- nicate face-to-face, they provide many verbal and nonverbal cues about how they are feeling. For example, frowns or eyebrow raises are common nonverbal cues that are used when a conversation has upset the receiver. If such a cue is accurately perceived by the

message sender, the sender might soften his or her message or seek clarifying feedback. In an online context, communicators do not have this instant emotional reactivity, and they might more easily offend others in their communications (Kowalski, Giumetti, et al., 2012; Kowalski, Limber, & Agatston, 2012).

There is also a perception of uncontrollability on the Internet. Many modes of communicating online do not have a moderator to intervene if an interaction becomes aggressive, whereas in a face- to-face context, other people might be more likely to step in. Additionally, online communications, especially those on discus- sion boards or blogs, feature relative permanence because the messages can remain online indefinitely or until someone erases them, perhaps after downloading them. Finally, online communi- cations feature 24/7 accessibility that makes it possible to send and receive harmful messages at all hours of the day, which may make it seem as though one cannot escape (Kowalski, Limber, & Agat- ston, 2012). Each of these features might help to explain why cyberbullying is becoming more of a problem in today’s society.

Defining Cyberbullying

As noted earlier, most researchers agree that cyberbullying involves the use of electronic communication technologies to bully others. However, as will be seen, assessments of the prevalence of cyberbullying have proven difficult because there is a lack of consensus regarding the more specific parameters by which cy- berbullying should be defined (Olweus, 2013; P. K. Smith, del Barrio, & Tokunaga, 2012; Ybarra, Boyd, Korchmaros, & Oppen- heim, 2012). Table 1 presents an expansive although not exhaus- tive list of research in the field and reports on both the assessment methods and prevalence rates of cyberbullying across varying samples.2 As noted in the table, although there are commonalities across operational definitions, they differ in terms of specificity versus generality. Whereas some simply define cyberbullying as bullying that occurs via the Internet or mobile phones, others are more specific in terms of the taxonomy of technology, with clear implications for measurement, as discussed later.

Conceptualizing cyberbullying is compounded by the fact that cyberbullying can take so many different forms and occur through so many different venues. Willard (2007) has created a taxonomy of types of cyberbullying that includes flaming (i.e., an online fight), harassment (i.e., repetitive, offensive messages sent to a target), outing and trickery (i.e., soliciting personal information from someone and then electronically sharing that information with others without the individual’s consent), exclusion (i.e., blocking an individual from buddy lists), impersonation (i.e., pos- ing as the victim and electronically communicating negative or inappropriate information with others as if it were coming from the victim), cyber-stalking (i.e., using electronic communication to stalk another person by sending repetitive threatening communi- cations), and sexting (i.e., distributing nude pictures of another individual without that person’s consent).

The media through which cyberbullying can occur are equally diverse, including instant messaging, e-mail, text messages, web pages, chat rooms, social networking sites, digital images, and online games. Which of these media is the most frequently used

2 Table 1 includes only published, empirical studies in which cyberbul- lying was assessed.

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ts di

sl ik

e hi

m or

he r

on lin

e; do

ot he

r hu

rt fu

l th

in gs

lik e

th at

on lin

e

✓ a

L as

t 3

m on

th s

46 3

M id

dl e

an d

hi gh

sc ho

ol

So ut

hw es

te rn

U .S

. 17

.1 –3

0. 7a

— —

A oy

am a

et al

. (2

01 2)

C yb

er bu

lly in

g Po

st [i

ng ]

na m

e- ca

lli ng

m es

sa ge

s to

In te

rn et

bu lle

tin bo

ar ds

or bl

og s

.. .

[o r]

be [i

ng ]

m ea

n to

so m

e pe

er s

us in

g th

e In

te rn

et (S

tu dy

1) ;

se nd

[i ng

] m

ea n

or na

st y

[e -m

ai l/t

ex t]

m es

sa ge

s to

so m

eo ne

.. .

[o r]

pu t[

tin g]

do w

n so

m eo

ne on

lin e

by se

nd in

g or

po st

in g

cr ue

l m

es sa

ge s,

go ss

ip ,

ru m

or s,

or ot

he r

ha rm

fu l

m at

er ia

ls (S

tu dy

2)

✓ a

L if

et im

e/ no

ne pr

ov id

ed (S

tu dy

1) ;

L as

t 6

m on

th s

(S tu

dy 2)

48 7

(S tu

dy 1)

; 27

5 (S

tu dy

2) 13

–1 5

ye ar

s (S

tu dy

1) ;

m ea

n of

16 .5

ye ar

s (S

tu dy

2)

Ja pa

n an

d so

ut hw

es te

rn U

.S .

7. 0b

(J ap

an ,

St ud

y 1)

; 11

.5 –2

4. 6a

(U .S

., St

ud y

2) ;

5. 0–

9. 4a

(J ap

an ,

St ud

y 2)

8. 0b

(J ap

an ,

St ud

y 1)

; 10

.3 –

21 .4

a

(U .S

., St

ud y

2) ;

4. 3–

5. 0a

(J ap

an ,

St ud

y 2)

18 .0

b (J

ap an

, St

ud y

1)

A ri

ca k

et al

. (2

00 8)

C yb

er bu

lly in

g C

yb er

bu lly

in g

on th

e In

te rn

et an

d vi

a ce

ll ph

on es

✓ L

if et

im e/

no ne

pr ov

id ed

26 9

12 –1

9 ye

ar s

T ur

ke y

5. 9b

35 .7

b 11

.9 b

B ar

le tt

& G

en til

e (2

01 2)

C yb

er bu

lly in

g M

ea su

re m

en t

ap pr

oa ch

un cl

ea r

✓ L

as t

ye ar

49 3

(S tu

dy 1)

; 18

1 (S

tu dy

2) M

ea n

of 19

.4 ye

ar s

M id

w es

te rn

U .S

. —

— —

B au

m an

(2 01

0) C

yb er

bu lly

in g

M ea

su re

m en

t ap

pr oa

ch un

cl ea

r ✓

C ur

re nt

sc ho

ol ye

ar 22

1 G

ra de

s 5–

8 So

ut hw

es te

rn U

.S .

3. 0b

1. 5b

8. 6b

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

4 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

B au

m an

& Pe

ro (2

01 0)

C yb

er bu

lly in

g M

ea su

re m

en t

ap pr

oa ch

un cl

ea r

✓ Si

nc e

th e

st ar

t of

sc ho

ol ye

ar (3

m on

th s

ea rl

ie r)

52 G

ra de

s 7–

12 So

ut hw

es te

rn U

.S .

6. 0

(d ea

f) ;

0. 0

(h ea

ri ng

)b

0. 0

(d ea

f) ;

10 .0

(h ea

ri ng

)b

3. 0

(d ea

f) ;

5. 0

(h ea

ri ng

)b

B en

ne tt

et al

. (2

01 1)

E le

ct ro

ni c

ag gr

es si

on E

le ct

ro ni

c ho

st ili

ty ,

el ec

tr on

ic in

tr us

iv en

es s,

el ec

tr on

ic hu

m ili

at io

n, an

d el

ec tr

on ic

ex cl

us io

n

✓ L

as t

ye ar

43 7

18 –2

2 ye

ar s

U .S

. 92

.0 —

—

B er

an &

L i

(2 00

5) C

yb er

-h ar

as sm

en t/

cy be

rb ul

ly in

g W

he n

a st

ud en

t, or

se ve

ra l

st ud

en ts

, sa

ys m

ea n

an d

hu rt

fu l

th in

gs or

m ak

es fu

n of

an ot

he r

st ud

en t

or ca

lls hi

m or

he r

m ea

n an

d hu

rt fu

l na

m es

, co

m pl

et el

y ig

no re

s or

ex cl

ud es

hi m

or he

r fr

om th

ei r

gr ou

p of

fr ie

nd s

or le

av es

hi m

or he

r ou

t of

th in

gs on

pu rp

os e,

te lls

lie s

or sp

re ad

s fa

ls e

ru m

or s

ab ou

t hi

m or

he r,

se nd

s m

ea n

no te

s an

d tr

ie s

to m

ak e

ot he

r st

ud en

ts di

sl ik

e hi

m or

he r,

an d

ot he

r hu

rt fu

l th

in gs

lik e

th at

.. .

[t ha

t] ha

pp en

re pe

at ed

ly ,

an d

it is

di ff

ic ul

t fo

r th

e st

ud en

t be

in g

ha ra

ss ed

to de

fe nd

hi m

se lf

or he

rs el

f ..

. [a

nd ]

tw o

st ud

en ts

[a re

no t]

of ab

ou t

eq ua

l st

re ng

th or

po w

er

✓ L

if et

im e/

no ne

pr ov

id ed

43 2

12 –1

5 ye

ar s

C an

ad a

57 .7

25 .5

—

B er

an &

L i

(2 00

7) C

yb er

bu lly

in g

H ar

as si

ng be

ha vi

or s

in vo

lv in

g te

ch no

lo gy

✓ L

if et

im e/

no ne

pr ov

id ed

43 2

12 –1

5 ye

ar s

C an

ad a

57 .7

25 .5

—

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

5CYBERBULLYING REVIEW AND META-ANALYSIS

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

B er

an et

al .

(2 01

2) C

yb er

-h ar

as sm

en t

R ep

ea te

dl y

do in

g on

e or

m or

e of

th e

fo llo

w in

g to

an ot

he r

pe rs

on fo

r w

ho m

it w

as di

ff ic

ul t

to de

fe nd

hi m

/h er

se lf

: (1

) sa

yi ng

m ea

n an

d hu

rt fu

l th

in gs

, te

as in

g, m

ak in

g fu

n, or

ca lli

ng hi

m /h

er m

ea n

an d

hu rt

fu l

na m

es ;

(2 )

ig no

ri ng

or ex

cl ud

in g

hi m

/ he

r; (3

) te

lli ng

lie s

or sp

re ad

in g

fa ls

e ru

m or

s ab

ou t

hi m

/h er

; or

(4 )

tr yi

ng to

m ak

e ot

he r

pe op

le di

sl ik

e hi

m /h

er ..

. us

[i ng

] te

ch no

lo gy

✓ L

if et

im e/

no ne

pr ov

id ed

1, 36

8 M

ea n

of 21

.1 ye

ar s

U .S

. an

d C

an ad

a 13

.8 (h

ig h

sc ho

ol );

8. 6

(c ol

le ge

)

8. 0

(h ig

h sc

ho ol

); 4.

1 (c

ol le

ge )

—

B er

so n

et al

. (2

00 2)

C yb

er -m

is co

nd uc

t T

he ex

ch an

ge of

su gg

es tiv

e or

th re

at en

in g

e m

ai l

m es

sa ge

s

✓ L

if et

im e/

no ne

pr ov

id ed

10 ,8

00 12

–1 8

ye ar

s O

nl in

e re

cr ui

tm en

t 15

.0 3.

0 —

B os

sl er

& H

ol t

(2 01

0) O

n- lin

e ha

ra ss

m en

t So

m eo

ne ha

ra ss

in g

yo u

in a

ch at

ro om

, In

te rn

et re

la y

ch at

, or

in st

an t

m es

sa gi

ng

✓ L

as t

ye ar

57 3

C ol

le ge

So ut

he as

te rn

U .S

. 18

.8 —

—

B ri

gh i,

G ua

ri ni

, et

al .

(2 01

2) C

yb er

bu lly

in g

B ul

ly [i

ng ]

vi a

a m

ob ile

ph on

e or

th e

In te

rn et

✓ L

as t

2 m

on th

s 2,

32 6

11 –2

1 ye

ar s

It al

y 12

.8 —

—

B ri

gh i,

M el

ot ti,

et al

. (2

01 2)

C yb

er bu

lly in

g B

ul ly

[i ng

] vi

a a

m ob

ile ph

on e

or th

e In

te rn

et

✓ L

if et

im e/

no ne

pr ov

id ed

5, 86

2 G

ra de

s 8,

10 ,

an d

12

It al

y, Sp

ai n,

an d

U ni

te d

K in

gd om

9. 9

— —

C al

ve te

et al

. (2

01 0)

C yb

er bu

lly in

g B

ul ly

[i ng

] vi

a th

e us

e of

th e

In te

rn et

an d

ce ll

ph on

es

✓ L

if et

im e/

no ne

pr ov

id ed

1, 43

1 12

–1 7

ye ar

s Sp

ai n

— 44

.1 —

C as

si dy

et al

. (2

01 2)

C yb

er bu

lly in

g M

ea su

re m

en t

ap pr

oa ch

un cl

ea r

✓ L

if et

im e/

no ne

pr ov

id ed

17 N

ot re

po rt

ed C

an ad

a —

— —

C et

in et

al .

(2 01

2) C

yb er

bu lly

in g

M ea

su re

m en

t ap

pr oa

ch un

cl ea

r ✓

L if

et im

e/ no

ne pr

ov id

ed 25

8 15

–1 8

ye ar

s T

ur ke

y —

— —

C et

in ,

Pe ke

r, et

al .

(2 01

1) C

yb er

bu lly

in g

M ea

su re

m en

t ap

pr oa

ch un

cl ea

r ✓

L if

et im

e/ no

ne pr

ov id

ed 35

0 M

ea n

of 15

.2 ye

ar s

T ur

ke y

— —

—

Ç et

in ,

Y am

an ,

& Pe

ke r

(2 01

1) C

yb er

bu lly

in g

C yb

er fo

rg er

y, cy

be r

ve rb

al bu

lly in

g, [a

nd ]

hi di

ng id

en tit

y

✓ ✓

L if

et im

e/ no

ne pr

ov id

ed 40

4 14

–1 9

ye ar

s T

ur ke

y —

— —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

6 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

C he

ng et

al .

(2 01

1) C

yb er

bu lly

in g

Sp re

ad in

g ru

m or

s on

lin e,

cr iti

ci zi

ng ot

he rs

on lin

e, an

d po

st in

g di

sg ra

ce fu

l ph

ot os

on lin

e w

ith ou

t pe

rm is

si on

✓ L

as t

6 m

on th

s 86

0 (s

ca le

de ve

lo pm

en t

st ag

e) ;

3, 94

1 (s

ca le

va lid

at io

n st

ag e)

12 –1

8 ye

ar s

C hi

na —

— —

C oy

ne et

al .

(2 00

9) G

ri ef

in g

In te

nt io

na l,

pe rs

is te

nt ,

un ac

ce pt

ab le

be ha

vi or

th at

di sr

up ts

a re

si de

nt ’s

ab ili

ty to

en jo

y Se

co nd

L if

e an

d w

hi ch

m ay

ha ve

ne ga

tiv e

co ns

eq ue

nc es

fo r

re si

de nt

s bo

th in

Se co

nd L

if e

an d

Fi rs

t (o

r R

ea l)

lif e.

M os

tly ,

th is

be ha

vi or

is di

re ct

ed at

a re

si de

nt w

ho ca

nn ot

ea si

ly de

fe nd

hi m

or he

rs el

f

✓ L

as t

ye ar

86 M

ea n

of 37

.1 ye

ar s

8 co

un tr

ie s

95 .0

20 .0

—

C ro

ss et

al .

(2 00

9) C

yb er

bu lly

in g

[B ul

ly in

g vi

a] In

te rn

et or

m ob

ile ph

on e

✓ C

ur re

nt sc

ho ol

te rm

7, 41

8 8–

14 ye

ar s

A us

tr al

ia 6.

6 3.

5 —

D ’A

nt on

a et

al .

(2 01

0) C

yb er

bu lly

in g

M ea

n or

hu rt

fu l

te xt

m es

sa ge

s ✓

L if

et im

e/ no

ne pr

ov id

ed 83

5 G

ra de

s 3–

5 N

or th

ea st

er n

U .S

. 6.

3 —

—

D eh

ue et

al .

(2 00

8) C

yb er

bu lly

in g

B ul

ly in

g on

th e

In te

rn et

or vi

a te

xt m

es sa

ge s

✓ C

ur re

nt sc

ho ol

ye ar

1, 21

1 M

ea n

of 12

.7 ye

ar s

N et

he rl

an ds

22 .9

17 .3

—

D eh

ue et

al .

(2 01

2) C

yb er

bu lly

in g

D oi

ng na

st y

an d

m ea

n th

in gs

to so

m eo

ne el

se us

in g

a co

m pu

te r

or ce

ll ph

on e

.. .

[w ith

a] la

ck of

po w

er on

th e

pa rt

of th

e vi

ct im

, ..

. an

on ym

ity of

th e

bu lly

, an

d th

e ex

cl us

io n

of jo

ke s

✓ C

ur re

nt sc

ho ol

ye ar

1, 18

4 10

–1 4

ye ar

s N

et he

rl an

ds 13

.8 b

7. 7b

8. 2b

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

7CYBERBULLYING REVIEW AND META-ANALYSIS

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

D em

ps ey

et al

. (2

01 1)

C yb

er -a

gg re

ss io

n Se

nd [i

ng ]

a st

ud en

t a

te xt

m es

sa ge

or in

st an

t m

es sa

ge th

at w

as m

ea n

or th

at th

re at

en ed

th at

st ud

en t;

po st

[i ng

] a

co m

m en

t on

a st

ud en

t’ s

w eb

sp ac

e w

al l

th at

w as

m ea

n or

th at

th re

at en

ed th

at st

ud en

t; se

nd [i

ng ]

a st

ud en

t an

e- m

ai l

th at

w as

m ea

n or

th at

th re

at en

ed th

at st

ud en

t; cr

ea t[

in g]

a w

eb pa

ge ab

ou t

a st

ud en

t th

at ha

d m

ea n

or em

ba rr

as si

ng in

fo rm

at io

n an

d/ or

ph ot

os

✓ L

as t

30 da

ys 1,

67 2

G ra

de s

6– 8

So ut

he as

te rn

U .S

. —

10 .0

—

D em

ps ey

et al

. (2

00 9)

C yb

er vi ct

im iz

at io

n Pe

er ag

gr es

si on

in vo

lv in

g in

st an

t m

es sa

gi ng

, te

xt m

es sa

gi ng

, pe

rs on

al iz

ed w

eb si

te s,

w eb

po st

s, an

d e-

m ai

l

✓ L

as t

30 da

ys 1,

68 4

11 –1

6 ye

ar s

So ut

he rn

U .S

. 14

.0 —

—

D id

de n

et al

. (2

00 9)

C yb

er bu

lly in

g B

ul ly

in g

.. .

vi a

In te

rn et

an d

ce ll

ph on

e

✓ a

L as

t 3

m on

th s

11 4

12 –1

9 ye

ar s

N et

he rl

an ds

4. 0–

7. 0a

b 0.

0– 4.

0a b

3. 0–

5. 0a

b

D ilm

ac (2

00 9)

C yb

er bu

lly in

g T

he us

e of

in fo

rm at

io n

an d

co m

m un

ic at

io n

te ch

no lo

gi es

to su

pp or

t de

lib er

at e,

re pe

at ed

, an

d ho

st ile

be ha

vi or

by an

in di

vi du

al or

gr ou

p, th

at is

in te

nd ed

to ha

rm ot

he rs

✓ L

if et

im e/

no ne

pr ov

id ed

66 6

18 –2

2 ye

ar s

T ur

ke y

35 .7

b 3.

0b 19

.5 b

D oo

le ye

t al

. (2

01 0)

C yb

er bu

lly in

g B

ul ly

[i ng

] vi

a th

e In

te rn

et or

m ob

ile ph

on e

✓ L

as t

3 m

on th

s (A

us tr

al ia

); la

st 2

m on

th s

(A us

tr ia

)

7, 48

9 10

–1 5

ye ar

s A

us tr

al ia

an d

A us

tr ia

— —

—

D oo

le ye

t al

. (2

01 2)

C yb

er bu

lly in

g B

ul ly

in g

vi a

th e

In te

rn et

or m

ob ile

ph on

e

✓ M

os t

re ce

nt sc

ho ol

te rm

51 6

10 –1

6 ye

ar s

A us

tr al

ia —

— —

E rd

ur -B

ak er

(2 01

0) C

yb er

bu lly

in g

B ul

ly in

g vi

a th

e In

te rn

et or

ce ll

ph on

e

✓ L

as t

se m

es te

r 27

6 14

–1 8

ye ar

s T

ur ke

y —

— —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

8 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

E rd

ur -B

ak er

& K

av şu

t (2

00 7)

C yb

er bu

lly in

g B

ul ly

in g

vi a

th e

In te

rn et

or ce

ll ph

on e

✓ a

L if

et im

e/ no

ne pr

ov id

ed 22

8 14

–1 9

ye ar

s T

ur ke

y 3.

1– 30

.1 a

4. 4–

28 .3

a —

E rd

ur -B

ak er

& T

an ri

ku lu

(2 01

0)

C yb

er bu

lly in

g B

ul ly

in g

vi a

th e

In te

rn et

or ce

ll ph

on e

✓ Pa

st se

m es

te r

16 5

10 –1

4 ye

ar s

T ur

ke y

— —

—

E re

nt ai

tė et

al .

(2 01

2) C

yb er

bu lly

in g

B ul

ly [i

ng ]

vi a

ce ll

ph on

e (s

ho rt

m es

sa ge

s (S

M S)

, cl

ip s/

pi ct

ur es

an d

ca lls

) [o

r] vi

a e-

m ai

l, ch

at ,

in st

an t

m es

sa gi

ng (I

M ),

an d

w eb

si te

s

✓ L

as t

fe w

m on

th s

1, 66

7 15

–1 9

ye ar

s L

ith ua

ni a

29 .3

— —

E st

év ez

et al

. (2

01 0)

C yb

er bu

lly in

g B

ul ly

in g

vi a

th e

In te

rn et

, ce

ll ph

on es

, ph

ot os

, or

vi de

os

✓ L

if et

im e/

no ne

pr ov

id ed

1, 43

1 12

–1 7

ye ar

s Sp

ai n

7. 4b

25 .0

b 22

.8 b

Fa nt

i et

al .

(2 01

2) C

yb er

bu lly

in g

Se nd

[i ng

] ..

. a

th re

at en

in g

or ha

ra ss

in g

e- m

ai l,

in st

an t

m es

sa ge

, m

es sa

ge in

a ch

at ro

om or

so ci

al ne

tw or

ki ng

si te

s, an

d sh

or t

te xt

m es

sa ge

(S M

S)

✓ L

if et

im e/

no ne

pr ov

id ed

1, 41

6 11

–1 4

ye ar

s C

yp ru

s —

— —

Fi nn

(2 00

4) O

nl in

e ha

ra ss

m en

t R

ep ea

te d

us e

of e-

m ai

l an

d in

st an

t m

es sa

gi ng

to in

su lt,

ha ra

ss ,

th re

at en

, or

se nd

in ap

pr op

ri at

e m

at er

ia l

su ch

as po

rn og

ra ph

y

✓ a

D ur

in g

te nu

re at

cu rr

en t

un iv

er si

ty

33 9

M ea

n of

20 .3

ye ar

s

N or

th ea

st er

n U

.S .

9. 6–

58 .7

a —

—

Fl em

in g

et al

. (2

00 6)

O nl

in e

bu lly

in g

E xp

os ur

e to

bu lly

in g

[o nl

in e]

✓ L

if et

im e/

no ne

pr ov

id ed

69 2

13 –1

6 ye

ar s

A us

tr al

ia 36

.8 —

—

Fr ed

st ro

m et

al .

(2 01

1) E

le ct

ro ni

c vi

ct im

iz at

io n

B ul

ly in

g [v

ia ]

e- m

ai lin

g, ch

at ro

om in

g, te

xt m

es sa

gi ng

, ph

on e

ca lli

ng ,

on lin

e po

st in

g, or

pi ct

ur e/

vi de

o cl

ip

✓ L

as t

ye ar

80 2

G ra

de 9

So ut

he as

te rn

U .S

. 27

.1 —

—

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

9CYBERBULLYING REVIEW AND META-ANALYSIS

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

G oe

be rt

et al

. (2

01 1)

C yb

er bu

lly in

g R

ec ei

v[ in

g] a

th re

at en

in g

or m

ea n

te xt

m es

sa ge

; re

ce iv

[i ng

] a

th re

at en

in g

or m

ea n

e- m

ai l;

ha v[

in g]

em ba

rr as

si ng

, th

re at

en in

g or

m ea

n in

fo rm

at io

n po

st ed

ab ou

t th

em on

a w

eb si

te ;

ha v[

in g]

a da

tin g

pa rt

ne r

go th

ro ug

h th

ei r

ce ll

ph on

e to

ch ec

k on

ca lls

or te

xt m

es sa

ge s;

an d

ha v[

in g]

a pa

rt ne

r go

th ro

ug h

th ei

r pe

rs on

al w

eb si

te to

ch ec

k up

on th

em

✓ L

as t

ye ar

67 7

G ra

de s

9– 12

H aw

ai i

56 .1

— —

G ra

di ng

er ,

St ro

hm ei

er ,

Sc hi

lle r,

et al

. (2

01 2)

C yb

er -

vi ct

im iz

at io

n B

e[ in

g] in

su lte

d or

hu rt

by re

ce iv

in g

m ea

n ca

lls ,

te xt

m es

sa ge

s, e-

m ai

ls ,

ch at

co nt

ri bu

tio ns

, di

sc us

si on

bo ar

d co

nt ri

bu tio

ns ,

in st

an t

m es

sa ge

s, vi

de os

or ph

ot os

✓ L

as t

2 m

on th

s 66

5 M

ea n

of 11

.6 ye

ar s

A us

tr ia

— —

—

G ra

di ng

er et

al .

(2 00

9) C

yb er

bu lly

in g

O ft

en us

[i ng

] th

e m

ob ile

ph on

e or

th e

co m

pu te

r to

se nd

m ea

n te

xt m

es sa

ge s,

e- m

ai ls

, vi

de os

, or

ph ot

os to

ot he

rs

✓ L

if et

im e/

no ne

pr ov

id ed

76 1

14 –1

9 ye

ar s

A us

tr ia

7. 1

5. 3

—

G ra

di ng

er ,

St ro

hm ei

er ,

& Sp

ie l

(2 01

2)

C yb

er bu

lly in

g In

su lt[

in g]

or hu

rt [i

ng ]

ot he

r st

ud en

ts by

se nd

in g

m ea

n te

xt m

es sa

ge s,

e- m

ai ls

, vi

de os

, or

ph ot

os to

th em

✓ L

as t

2 m

on th

s 1,

46 1

10 –1

5 ye

ar s

A us

tr ia

10 .4

6. 9

—

H ay

& M

el dr

um (2

01 0)

C yb

er bu

lly in

g [B

ei ng

] th

e ta

rg et

of “m

ea n”

te xt

m es

sa ge

s; se

nt th

re at

en in

g or

hu rt

fu l

st at

em en

ts or

pi ct

ur es

in an

e- m

ai l

or te

xt m

es sa

ge ;

an d

m ad

e fu

n of

on th

e In

te rn

et

✓ L

as t

ye ar

42 6

10 –2

1 ye

ar s

So ut

he as

te rn

U .S

. —

— —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

10 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

H ay

, M

el dr

um ,

& M

an n

(2 01

0)

C yb

er bu

lly in

g [B

ei ng

] th

e ta

rg et

of “m

ea n”

te xt

m es

sa ge

s; se

nt th

re at

en in

g or

hu rt

fu l

st at

em en

ts or

pi ct

ur es

in an

e- m

ai l

or te

xt m

es sa

ge ;

an d

m ad

e fu

n of

on th

e In

te rn

et

✓ L

as t

ye ar

42 4

M ea

n of

15 .0

ye ar

s

So ut

he as

te rn

U .S

. —

— —

H em

ph ill

et al

. (2

01 2)

C yb

er bu

lly in

g B

ul ly

[i ng

] an

ot he

r st

ud en

t us

in g

te ch

no lo

gy ,

su ch

as m

ob ile

te le

ph on

es ,

th e

In te

rn et

, co

m pu

te rs

, an

sw er

in g

m ac

hi ne

s, or

ca m

er as

✓ L

as t

ye ar

69 6

11 –1

4 ye

ar s

(t im

e 1)

; 14

–1 6

ye ar

s (t

im e

2)

A us

tr al

ia —

15 .0

—

H in

du ja

& Pa

tc hi

n (2

00 7)

C yb

er bu

lly in

g [B

ei ng

] ig

no re

d by

ot he

rs ,

di sr

es pe

ct ed

by ot

he rs

, ca

lle d

na m

es ,

th re

at en

ed ,

m ad

e fu

n of

by ot

he rs

, pi

ck ed

on by

ot he

rs ,

sc ar

ed fo

r sa

fe ty

, an

d [h

av in

g] ru

m or

s sp

re ad

by ot

he rs

✓ L

if et

im e/

no ne

pr ov

id ed

1, 38

8 6–

17 ye

ar s

O nl

in e

re cr

ui tm

en t

34 .4

— —

H in

du ja

& Pa

tc hi

n (2

00 8)

C yb

er bu

lly in

g B

ot he

ri ng

so m

eo ne

on lin

e, te

as in

g in

a m

ea n

w ay

, ca

lli ng

so m

eo ne

hu rt

fu l

na m

es ,

in te

nt io

na lly

le av

in g

pe rs

on s

ou t

of th

in gs

, th

re at

en in

g so

m eo

ne ,

an d

sa yi

ng un

w an

te d

se xu

al ly

-r el

at ed

th in

gs to

so m

eo ne

✓ L

as t

6 m

on th

s 1,

37 8

� 18

ye ar

s O

nl in

e re

cr ui

tm en

t 34

.6 16

.8 —

H in

du ja

& Pa

tc hi

n (2

01 0)

C yb

er bu

lly in

g O

nl in

e ag

gr es

si on

[v ia

] co

m pu

te r

te xt

m es

sa ge

s, M

yS pa

ce or

si m

ila r

si te

[s ],

e- m

ai l,

in st

an t

m es

sa ge

[s ],

ch at

ro om

[s ],

or ot

he r

w eb

pa ge

s

✓ L

as t

30 da

ys 1,

96 3

10 –1

6 ye

ar s

U .S

. 29

.4 21

.8 —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

11CYBERBULLYING REVIEW AND META-ANALYSIS

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

H ol

fe ld

& G

ra be

(2 01

2) C

yb er

bu lly

in g

T he

in te

nt io

na l

an d

re pe

at ed

ha rm

of ot

he rs

th ro

ug h

th e

us e

of co

m pu

te rs

, ce

ll ph

on es

, an

d ot

he r

el ec

tr on

ic de

vi ce

s

✓ L

if et

im e/

no ne

pr ov

id ed

, la

st ye

ar ,

an d

la st

30 da

ys

38 3

M ea

n of

13 .5

ye ar

s

N or

th er

n U

.S .

17 .0 (l

if et

im e)

; 16

.0 (l

as t

ye ar

)

11 .0 (l

if et

im e)

; 9.

0 (l

as t

ye ar

)

—

H ua

ng &

C ho

u (2

01 0)

C yb

er bu

lly in

g Il

l- in

te nd

ed be

ha vi

or s

in cy

be rs

pa ce

(i .e

., e-

m ai

ls ,

in st

an t

m es

se ng

er s,

ch at

ro om

s, on

lin e

po lls

, w

eb fo

ru m

s, w

eb lo

gs ,

an d

ce ll-

ph on

e te

xt m

es sa

ge s)

[t ha

t] in

cl ud

e th

re at

s, ha

ra ss

m en

t, hu

m ili

at io

n, in

su lts

, an

d an

y ot

he r

em ot

io na

l pu

t- do

w ns

by m

ea ns

of w

or ks

, fa

ke pi

ct ur

es ,

pe ep

in g-

T om

vi de

os ,

or an

y co

m bi

na tio

n of

di gi

ta l

co nt

en t

✓ L

if et

im e/

no ne

pr ov

id ed

54 5

G ra

de s

7– 9

T ai

w an

34 .9

20 .4

—

H un

t et

al .

(2 01

2) C

yb er

bu lly

in g

O th

er ki

ds sa

y[ in

g] na

st y

th in

gs to

m e

by SM

S, th

re at

en [i

ng ]

m e

ov er

th e

ph on

e, se

nd [i

ng ]

m e

na st

y e-

m ai

ls ,

ha ra

ss [i

ng ]

m e

ov er

th e

ph on

e, sa

y[ in

g] na

st y

th in

gs ab

ou t

m e

on w

eb si

te s,

se nd

[i ng

] m

e co

m pu

te r

vi ru

se s

on pu

rp os

e, sa

y[ in

g] na

st y

th in

gs ab

ou t

m e

on an

in st

an t

m es

se ng

er or

ch at

ro om

, an

d m

ak [i

ng ]

pr an

k ca

lls to

m e

✓ L

if et

im e/

no ne

pr ov

id ed

94 3

8– 16

ye ar

s A

us tr

al ia

— —

—

Jo se

et al

. (2

01 2)

C yb

er bu

lly in

g Se

nd [i

ng ]

a m

ea n

te xt

m es

sa ge

to so

m eo

ne [o

r] bu

lly [i

ng ]

ot he

rs on

lin e

✓ L

as t

m on

th 1,

77 4

11 –1

6 ye

ar s

N ew

Z ea

la nd

— —

—

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

12 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

Ju vo

ne n

& G

ro ss

(2 00

8) C

yb er

bu lly

in g

A ny

th in

g th

at so

m eo

ne do

es th

at up

se ts

or of

fe nd

s so

m eo

ne el

se ,

in cl

ud in

g na

m e-

ca lli

ng ,

th re

at s,

se nd

in g

em ba

rr as

si ng

/ pr

iv at

e pi

ct ur

es ,

an d

sh ar

in g

pr iv

at e

in fo

rm at

io n

w ith

ou t

pe rm

is si

on ..

. vi

a e-

m ai

l, in

st an

t m

es sa

gi ng

, ce

ll ph

on e

te xt

m es

sa gi

ng ,

in a

ch at

ro om

, bl

og ,

pe rs

on al

pr of

ile si

te ,

an d/

or m

es sa

ge bo

ar ds

✓ L

as t

ye ar

1, 45

4 12

–1 7

ye ar

s O

nl in

e re

cr ui

tm en

t 72

.0 —

—

K at

ze r

et al

. (2

00 9)

C yb

er bu

lly in

g B

ul ly

in g

in In

te rn

et ch

at ro

om s

✓ a

L if

et im

e/ no

ne pr

ov id

ed 1,

70 0

M ea

n of

14 .1

ye ar

s

G er

m an

y 4.

3– 44

.0 a

— —

K es

se l

Sc hn

ei de

r et

al .

(2 01

2) C

yb er

bu lly

in g

U s[

in g]

th e

In te

rn et

, a

ph on

e, or

ot he

r el

ec tr

on ic

co m

m un

ic at

io ns

to bu

lly ,

te as

e, or

th re

at en

yo u

✓ L

as t

ye ar

20 ,4

06 G

ra de

s 9–

12 N

or th

ea st

er n

U .S

. 15

.8 —

—

K ite

et al

. (2

01 0)

C yb

er bu

lly in

g B

ul ly

in g

be ha

vi or

on bo

th M

yS pa

ce an

d in

st an

t m

es se

ng er

si te

s

✓ a

L if

et im

e/ no

ne pr

ov id

ed 58

8 G

ra de

s 7–

8 N

or th

ea st

er n

U .S

. 10

.0 6.

0– 10

.0 a

—

K lo

m ek

et al

. (2

00 8)

C yb

er bu

lly in

g U

s[ in

g] e-

m ai

l or

In te

rn et

to be

m ea

n to

yo u

✓ L

as t

4 w

ee ks

2, 34

1 13

–1 9

ye ar

s N

or th

ea st

er n

U .S

. 7.

3 —

—

K ön

ig et

al .

(2 01

0) C

yb er

bu lly

in g

Fl am

in g,

ha ra

ss m

en t,

de ni

gr at

io n,

im pe

rs on

at io

n, ou

tin g/

tr ic

ke ry

, ex

cl us

io n

an d

cy be

r- st

al ki

ng

✓ L

as t

6 m

on th

s 47

3 11

–1 7

ye ar

s O

nl in

e re

cr ui

tm en

t (G

er m

an fo

ru m

)

— 79

.3 —

K ow

al sk

i &

Fe di

na (2

01 1)

C yb

er bu

lly in

g B

ul ly

[i ng

] th

ro ug

h e-

m ai

l, in

st an

t m

es sa

gi ng

, in

a ch

at ro

om ,

on a

w eb

si te

, or

th ro

ug h

a te

xt m

es sa

ge se

nt to

a ce

ll ph

on e

✓ c

Pa st

co up

le of

m on

th s

42 10

–2 0

ye ar

s U

.S .

21 .4

5. 8

—

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

13CYBERBULLYING REVIEW AND META-ANALYSIS

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

K ow

al sk

i &

L im

be r

(2 00

7)

E le

ct ro

ni c

bu lly

in g

B ul

ly [i

ng ]

th ro

ug h

e- m

ai l,

in st

an t

m es

sa gi

ng ,

in a

ch at

ro om

, on

a w

eb si

te ,

or th

ro ug

h a

te xt

m es

sa ge

se nt

to a

ce ll

ph on

e

✓ c

Pa st

co up

le of

m on

th s

3, 76

7 G

ra de

s 6–

8 So

ut he

as te

rn an

d no

rt hw

es te

rn U

.S .

11 .1

b 4.

1b 6.

8b

K ow

al sk

i &

L im

be r

(2 01

3)

C yb

er bu

lly in

g B

ul ly

[i ng

] th

ro ug

h e-

m ai

l, in

st an

t m

es sa

gi ng

, in

a ch

at ro

om ,

on a

w eb

si te

, or

th ro

ug h

a te

xt m

es sa

ge se

nt to

a ce

ll ph

on e

✓ c

Pa st

co up

le of

m on

th s

93 1

11 –1

9 ye

ar s

N or

th ea

st er

n U

.S .

14 .2

b 16

.8 b

18 .6

b

K ow

al sk

i, M

or ga

n, &

L im

be r

(2 01

2)

C yb

er bu

lly in

g B

ul ly

[i ng

] th

ro ug

h e-

m ai

l, in

st an

t m

es sa

gi ng

, in

a ch

at ro

om ,

on a

w eb

pa ge

, or

th ro

ug h

a te

xt m

es sa

ge se

nt to

a ce

ll ph

on e

✓ Pa

st co

up le

of m

on th

s 4,

53 1

11 –1

9 ye

ar s

U .S

. 10

.9 b

4. 5b

6. 4b

L am

& L

i (2

01 3)

E -B

ul ly

in g

T ea

s[ in

g] ,

ca ll[

in g]

so m

eo ne

ba d

na m

es ,

sa y[

in g]

m ea

n th

in gs

ab ou

t so

m eo

ne ,

sa y[

in g]

yo u

ar e

go in

g to

hi t/h

ur t

so m

eo ne

, th

re at

en [i

ng ]

so m

eo ne

, [o

r] m

ak [i

ng ]

up so

m et

hi ng

ab ou

t so

m eo

ne to

m ak

e ot

he rs

no t

lik e

hi m

/h er

an ym

or e

us in

g e-

m ai

ls ,

te xt

in g,

sh or

t m

es sa

ge s,

on a

w eb

si te

su ch

as R

en re

n, et

c.

✓ L

as t

7 da

ys 48

4 11

–1 6

ye ar

s C

hi na

— —

—

L aw

, Sh

ap ka

, D

om en

e, &

G ag

né (2

01 2)

C yb

er bu

lly in

g/ on

lin e

ag gr

es si

on

M ea

n th

in gs

, ru

m or

s, or

go ss

ip be

in g

sa id

th ro

ug h

th e

In te

rn et

w eb

si te

s, e-

m ai

l, or

te xt

m es

sa gi

ng an

d ..

. em

ba rr

as si

ng pi

ct ur

es or

vi de

o cl

ip s

of yo

ur se

lf or

pe op

le yo

u kn

ow be

in g

se nt

or po

st ed

on th

e In

te rn

et

✓ ✓

L if

et im

e/ no

ne pr

ov id

ed 73

3 10

–1 8

ye ar

s C

an ad

a —

— —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

14 KOWALSKI, GIUMETTI, SCHROEDER, AND LATTANNER

T ab

le 1

(c on

ti nu

ed )

St ud

y

C on

ce pt

ua liz

at io

n M

ea su

re m

en t

T im

e pa

ra m

et er

Sa m

pl e

ch ar

ac te

ri st

ic s

Pr ev

al en

ce

C on

ce pt

O pe

ra tio

na l

de fi

ni tio

n Si

ng le

ite m

(s )

M ul

ti- ite

m Q

ua lit

at iv

e N

A ge

or gr

ad e

L oc

at io

n %

V %

P %

V /P

L aw

, Sh

ap ka

, H

ym el

, et

al .

(2 01

2)

C yb

er bu

lly in

g M

ea n

th in

gs ,

ru m

or s,

or go

ss ip

be in

g sa

id th

ro ug

h th

e In

te rn

et w

eb si

te s,

e- m

ai l,

or te

xt m

es sa

gi ng

an d

.. .

em ba

rr as

si ng

pi ct

ur es

or vi

de o

cl ip

s of

yo ur

se lf

or pe

op le

yo u

kn ow

be in

g se

nt or

po st

ed on

th e

In te

rn et

✓ L

if et

im e/

no ne

pr ov

id ed

17 ,5

51 1

14 –1

8 ye

ar sd

C an

ad a

8. 0

6. 0

—

L en

ha rt

(2 00

7) C

yb er

bu lly

in g

R ec

ei vi

ng th

re at

en in

g m

es sa

ge s;

ha vi

ng ..

. pr

iv at

e e-

m ai

ls or

te xt

m es

sa ge

s fo

rw ar

de d

w ith

ou t

co ns

en t;

ha vi

ng an

em ba

rr as

si ng

pi ct

ur e

po st

ed w

ith ou

t pe

rm is

si on

; or

ha vi

ng ru

m or

s ..

. sp

re ad

on lin

e

✓ L

if et

im e/

no ne

pr ov

id ed

93 5

12 –1

7 ye

ar s

U .S

. 32

.0 —

—

L es

te r

et al

. (2

01 2)

C yb

er bu

lly in

g M

ea n

an d

hu rt

fu l

te xt

(S M

S) m

es sa

ge s

(t ex

t m

es sa

ge s,

pi ct

ur es

or vi

de o

cl ip

s) an

d m

ea n

an d

hu rt

fu l

m es

sa ge

s on

th e

In te

rn et

(e -m

ai l;

pi ct

ur es

, w

eb ca

m or

vi de

o cl

ip s;

ch at

ro om

s; M

SN m

es se

ng er

or an

ot he

r fo

rm of

in st

an t

m es

se ng

er ;

so ci

al ne

tw or

ki ng

si te

s lik

e M

yS pa

ce ;

In te

rn et

ga m

e; w

eb lo

g/ bl

og or

w eb

pa ge

/w eb

si te

)

✓ Pr

ev io

us sc

ho ol

te rm

1, 78

2 M

ea n

of 12

(t im

e 1)

; m

ea n

of 14

(T im

e 2)

A us

tr al

ia —

— —

L i

(2 00

6) C

yb er

bu lly

in g

C yb

er bu

lly in

g [v

ia ]

e- m

ai l,

ch at

ro om

, ce

ll ph

on e

✓ c

L if

et im

e/ no

ne pr

ov id

ed 26

4 G

ra de

s 7–

9 C

an ad

a 16

.9 25

.3 —

(t ab

le co

nt in

ue s)

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an Ps

yc ho

lo gi

ca l

A ss

oc ia

tio n

or on

e of

its al

lie d

pu bl

is he

rs .

T hi

s ar

tic le

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

15CYBERBULLYING REVIEW AND META-ANALYSIS