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Correlates and Consequences of Peer Victimization: Gender Differences in Direct and Indirect Forms of Bullying

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Research on school-based violence and bullying suggests that males are more likely to be both perpetrators and victims of bullying. Because of this, until recently, the experiences of females have been somewhat overlooked. Evidence suggests, however, that definition and measurement issues may be at play; girls, for instance, are more likely than boys to experience indirect forms of bullying such as teasing. To what extent have the correlates and consequences of bullying victimization been misspecified due to an emphasis on direct forms of bullying, such as physical violence, which disproportionately affects boys? The authors use data from two waves of a longitudinal panel study of 1,222 youths in 15 schools across the United States to address this question by examining the correlates and consequences for both boys and girls of two forms of bullying. Findings suggest a number of important gender similarities and differences in indirect and direct bullying victimization.
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Youth Violence and Juvenile
http://yvj.sagepub.com/content/8/4/332
The online version of this article can be found at:
DOI: 10.1177/1541204010362954
2010 8: 332 originally published online 22 April 2010Youth Violence and Juvenile Justice
Kristin Carbone-Lopez, Finn-Aage Esbensen and Bradley T. Brick
Indirect Forms of Bullying
Correlates and Consequences of Peer Victimization: Gender Differences in Direct and
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Correlates and Consequences
of Peer Victimization: Gender
Differences in Direct and
Indirect Forms of Bullying
Kristin Carbone-Lopez,
1
Finn-Aage Esbensen,
1
and Bradley T. Brick
2
Abstract
Research on school-based violence and bullying suggests that males are more likely to be both
perpetrators and victims of bullying. Because of this, until recently, the experiences of females have
been somewhat overlooked. Evidence suggests, however, that definition and measurement issues
may be at play; girls, for instance, are more likely than boys to experience indirect forms of bullying
such as teasing. To what extent have the correlates and consequences of bullying victimization been
misspecified due to an emphasis on direct forms of bullying, such as physical violence, which dispro-
portionately affects boys? The authors use data from two waves of a longitudinal panel study of 1,222
youths in 15 schools across the United States to address this question by examining the correlates
and consequences for both boys and girls of two forms of bullying. Findings suggest a number of
important gender similarities and differences in indirect and direct bullying victimization.
Keywords
bullying, school victimization, gender differences, consequences of victimization
A great deal of attention in recent years has been paid to violence within schools, particularly bully-
ing. Likely due, at least in part, to intense media coverage following a number of school shooting
incidents in the United States and Europe, the research community has sought a greater understand-
ing of school violence with the goal of preventing such tragedies. Media exposure and the resulting
flurry of research have largely focused on the more dramatic victimization experiences, such as
school shootings, or on other forms of serious violence such as assault and robbery, despite the fact
that these are relatively rare occurrences.
Other forms of victimization, including teasing and relational aggression, may actually present a
greater threat within schools because they tend to be much more prevalent. For example, the School
1
Department of Criminology and Criminal Justice, University of Missouri, St. Louis, USA
2
Department of Sociology and Criminal Justice, Old Dominion University, Norfolk, VA, USA
Corresponding Author:
Kristin Carbone-Lopez, Department of Criminology and Criminal Justice, University of Missouri, 324 Lucas Hall, One Uni-
versity Boulevard, St. Louis, MO 63121, USA.
Email: carbonelopezk@umsl.edu
Youth Violence and Juvenile Justice
8(4) 332-350
ª The Author(s) 2010
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Crime Supplement to the National Crime Victimization Survey suggests that prevalence rates of
these indirect forms of victimization are, in some cases, more than twice the rates of physical
violence occurring within schools (Dinkes, Cataldi, Lin-Kelly, & Snyder, 2007). Yet, the
disproportionate attention to the most extreme forms of violence has resulted in greater focus on the
experiences of boys as they are more likely to be involved as both perpetrators and victims in overt
physical forms of victimization. The ‘more insidious threats’ to safety—including the indirect
forms of bullying that girls are more likely to experience—have received somewhat less attention
by academics and school officials alike (Stein, Tolman, Porche, & Spencer, 2002).
The current study examines both direct and indirect bullying in an effort to understand bullying
victimization more fully. Longitudinal panel data allow us to separate repeated experiences of vic-
timization (i.e., across multiple data points) from those that occur more intermittently. Using data
collected from a sample of American students attending 15 schools in nine cities across four states,
we explore gender differences in the correlates and consequences of bullying victimization among
middle-school aged students. First, we question whether known correlates of bullying victimization,
such as race/ethnicity and school-level contextual effects, are similar or unique for boys and girls.
Second, we explore a range of outcomes or consequences of such victimization for both boys and
girls, focusing specifically on whether such consequences differ by gender and type of victimization.
Of particular interest are the consequences that bullying experiences have for involvement in
delinquent behavior.
Answers to these questions have potentially important implications for school safety policies and
programming. Current efforts largely focus on the prevention of physical violence, particularly the
use of weapons, in schools and zero tolerance policies (indeed, even metal detectors) have become
standard practice in most school districts for ensuring school safety. The existing focus on overt
forms of aggression and violence within schools may mean that interventions predominantly target
boys, whether intentionally or not. Other aspects of safety within schools, which may in fact be more
salient to students themselves, such as threats to their ‘psychological and social safety,’ are largely
ignored (Stein et al., 2002). If, in fact, other types of victimization have similar or greater negative
consequences on victims’ well-being, this focus on physical violence may be misguided. Moreover,
gender and racial differences in the experiences of various forms of bullying victimization may
indicate the need for more tailored programming for specific target groups.
Bullying Victimization and Its Correlates
Although there is still some debate concerning what specifically constitutes bullying, more
researchers are adopting the definition advocated by Olweus (1993). His definition includes the fol-
lowing criteria: (a) physically harming a person (e.g., hitting, kicking, and pushing) or indirect forms
of victimization including making fun of, excluding, and/or spreading rumors about a person;
(b) victimization that occurs repeatedly over time; and (c) victims who do not have equal strength
or power to the bully (see also Berthold & Hoover, 2000; Olweus, 1996; Solberg, Olweus, &
Endreson, 2007; Sourander, Helstela, Helenius, & Piha, 2000).
1
While early research largely relied
on students’ answers to a generic question asking whether they had ever been ‘bullied,’ more recent
research relies on multiple behavior-specific questions measuring both indirect and direct forms to
better identify victims of bullying (Andreou, 2000; Baldry & Farrington, 1999; Borg, 1999; Boulton,
Trueman, & Flemington, 2002; Esbensen & Carson, 2009; Mouttapa, Valente, Gallaher, Rohrbach,
& Unger, 2004; Seals & Young, 2003; Unnever & Cornell, 2003).
Most analyses of bullying victimization have found that students more commonly report
experiencing teasing, being picked on, or having rumors spread about them as opposed to the direct,
physical forms of bullying (e.g., Baldry & Farrington, 1999; Borg, 1999; Dinkes et al., 2007; Rivers
& Smith, 1994). This relational aggression is generally more covert than physical threats and
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typically involves the exclusion of students from peer groups or other behaviors that intentionally harm
individuals through the manipulation of social relationships (Crick & Grotpeter, 1995). Such experi-
ences may be particularly detrimental to adolescents during a time in their life course in which peer
relationships are central to individual perceptions of self (Marini, Dane, Bosacki, & YLC-CURA,
2006). Increased attention to such forms of bullying in recent years has broadened the scope of children
identified as victims of bullying and, consequently, potential targets for intervention; a substantial
proportion of those identified by casting a ‘wider net’ are girls (Putallaz et al., 2007).
Gender is one of the strongest correlates of bullying, with boys at greater risk of both offending and
victimization (e.g., Berthold & Hoover, 2000; Nansel et al., 2001; Spriggs, Iannotti, Nansel & Haynie,
2007). However, there are important gender differences when distinguishing between direct and indirect
forms of bullying victimization: boys are consistently found to be at greater risk of direct forms of
bullying, whereas girls tend to be equally or more likely to experience indirect forms of bullying
(e.g., Baldry & Farrington 1999; Borg 1999; Putallaz et al., 2007; Rivers & Smith, 1994).
2
Girls are also
more likely to experience other forms of gendered violence such as sexual harassment in schools, includ-
ing sexually based jokes, insults and gestures, unwanted sexual attention, sexual touching, and sexual
coercion (e.g., American Association of University Women 1993, 2001; Hand & Sanchez, 2000).
Although it is unclear whether bullying differs by race, there is some evidence that race and gender
interact to produce bullying risk.
3
For example, Sawyer and colleagues (2008) found that among ele-
mentary students, compared to White students, Black girls and boys had higher odds of experiencing
direct physical and indirect forms of bullying victimization. In middle school, Black and Hispanic girls
were more likely to experience direct physical victimization than were White girls, but only boys of
other races/ethnicities had greater odds of direct physical victimization than White boys (Sawyer,
Bradshaw, & O’Brennan, 2008). There is also some suggestion that an ‘in-group’ bias operates within
ethnically diverse schools such that members of the minority group may be at greater risk of victimi-
zation (Schreck, Miller, & Gibson, 2003). For example, Hanish and Guerra (2000) found that attending
ethnically integrated schools was associated with greater risk of victimization for White students but
lower risk for Black students; integration was not related to risk among Hispanic students. Yet, little
other research has examined the interactions between race, gender, and bullying victimization.
There is also evidence that school disadvantage is related to risk of school-based victimization
more generally. For example, Burrow and Apel (2008) found that youth attending more disordered
schools—those with greater presence of factors such as gangs and hate-related graffiti and increased
availability of drugs and guns—were at significantly greater risk of experiencing assault. Children
who attend schools located in more economically disadvantaged areas are also at higher risk of
exposure to violence at school (Menacker, Weldon, & Hurwitz, 1990) and Wilcox and colleagues
found that students who receive free or reduced-cost lunch are at greater risk of physical violence,
theft, or sexual harassment victimization (Wilcox, Augustine, & Clayton, 2006). Whether such
school characteristics are differentially tied to particular types of bullying victimization or charac-
teristics of victims, however, is unknown.
In sum, similar to victimization more generally, a number of factors are related to the risk of
bullying victimization. However, it is unclear whether such factors operate similarly across gender;
indeed, there is some evidence that they do not. Evidence of significant gender differences in the
correlates of bullying victimization would underscore the importance of comparative analyses in this
area and provide further evidence that a gender-neutral approach to bullying is misguided, as others
have argued elsewhere (Brown, Chesney-Lind, & Stein, 2007).
Consequences of Bullying Victimization
Bullying victimization has a number of negative consequences for victims, both emotionally and
behaviorally. For example, research has found an association between experiences of bullying
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and subsequent psychological distress, low self-esteem, depression and anxiety, and avoidance
behavior (e.g., Austin & Joseph, 1996; Esbensen & Carson, 2009; Kaltiala-Heino, Rimpela¨, &
Rantanen, 2000; Nansel et al., 2001; Olweus, 1993; for reviews see: Hawker & Boulton, 2000;
Rigby, 2003). There is some evidence that bullying victimization may also be related to poor social
adjustment and behavioral problems as well, including the use of illegal drugs (Furlong, Caas,
Corral, Chung, & Bates, 1997; Reid, Peterson, Hughley, & Garcia-Reid, 2006) and others have
found a correlation between bullying victimization and subsequent violent behavior including fight-
ing and bringing weapons to school (e.g., Nansel, Overpeck, Haynie, Ruan, & Scheidt, 2003).
4
Much
of the research, however, on the consequences of bullying has been cross-sectional and thus causal
ordering issues arise. Such results may suggest certain characteristics of ‘victim-proneness;’ in
other words, it is equally likely that individuals with existing behavioral or self-esteem issues are
targeted as victims of bullying. Nevertheless, the findings generally suggest a correlation between
bullying victimization and behavioral and emotional problems.
Extant research also suggests that there may be differences in outcomes based on victim charac-
teristics and type of bullying victimization. There is some indication that girls may suffer a broader
range of and more negative consequences of bullying than boys, including more negative psycho-
logical effects and more severe health problems (Gruber & Fineran, 2008). Such gender differences
may be partly due to the differences in type of victimization that boys and girls experience; girls are
more likely to experience indirect forms of bullying—including spreading rumors and name-call-
ing—which may have a greater negative impact on health and mental well-being. Although rela-
tional aggression is considered indirect in its action, it appears to be quite direct in its
consequences, affecting levels of distress and psychological harm (Crick & Nelson, 2002); this
appears to be particularly true for girls as they are socialized to preserve and protect relationships.
Research generally has not addressed the extent to which various forms of bullying victimization
affect individuals differently. Thus, it is unclear whether direct or indirect forms of victimization
have greater or more long-lasting effects on psychological and behavioral outcomes and whether
those effects are more pronounced among girls or boys.
Current Study
In this research, we examine whether the correlates and consequences of bullying victimization
among middle-school students are similar across gender and type of victimization. We first explore
the extent to which direct and indirect forms of bullying have common correlates and whether these
correlates differ depending on victim gender. Second, we examine a number of consequences of
victimization, focusing on the extent to which the consequences of direct and indirect bullying
are similar or different. Are victims of direct bullying more likely to ‘act out’ by engaging in delin-
quent or criminal behavior while victims of indirect bullying are more likely to internalize their vic-
timization, thus suffering reduced psychological well-being? As we are interested in similarities and
differences between girls and boys, we also investigate whether there are differential consequences
of bullying by gender. The fact that our data are longitudinal provides greater confidence in
determining temporal ordering and allows us to focus on the potential consequences of previous
victimization experiences.
Data
The data used in this study were gathered as part of an evaluation of a school-based law-related
education program. As such, a purposive sample of schools was selected for inclusion in the
evaluation; only schools offering the targeted program were eligible for inclusion. The following
summarizes our efforts to select study sites:
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1) Records of program implementation provided by the program national office were reviewed and
more than 250 schools were identified as offering the targeted program. All of these schools
were contacted to determine the status of program delivery;
2) 18 schools met the evaluation criteria (i.e., confirmation that the program was actually being
taught in its entirety, teaching of a sufficient number of classes to allow for matching of treat-
ment and comparison groups while also being cost-effective in terms of travel to the school for
data collection, a willingness to withhold the program from some classes, and agreement to
adhere to the evaluation design);
3) 3 schools declined the opportunity to participate;
4) 15 schools in 9 cities in 4 states agreed to the evaluation design and participated in the outcome
evaluation.
The evaluation design included matching of classrooms (either by teacher or by team of teachers)
and agreement to a 4-year study design that included pre and posttest questionnaire administration
during the first year and then three annual follow-up surveys with students. The selection of schools
was obviously purposive and the final sample of 15 schools (nine in Arizona, one in New Mexico,
two in Massachusetts, and three in South Carolina) reflects the fact that program adoption was more
pronounced in Arizona. Classrooms were selected based on the grade in which the program was
taught (ranging from 6th to 9th grade).
All students in the selected classrooms (N ¼ 2,353) were asked to participate in the evaluation.
Due to the nature of the study, active parental consent was required before students could participate
in the evaluation. Consent letters were sent home with students and collected by teachers. Our col-
laborative efforts with the teachers resulted in an impressive 72% active consent rate (N ¼ 1,686):
12% of parents refused their child’s participation and 16% of students failed to return consent forms.
This loss rate (28%) is well below other comparable panel studies currently being used to examine
factors related to school victimization (e.g., Wilcox et al., 2006) and is in line with general
recommendations for consent rates needed to ensure low sample bias (Babbie, 1973; Lueptow,
Mueller, Hammes, & Master, 1977; Sewell & Hauser, 1975).
5
The first wave of data was collected prior to the delivery of the evaluated curriculum
6
during the
2004–2005 school year, and data were collected a second time directly following the completion of
the program, generally 3–6 months later. Both waves of survey data were collected using group-
administered self-report methods, whereby subjects answered questions individually as they were
read out loud by members of the research team in the classroom. The approximate time needed for
completion of the survey was 40–45 min.
Because this study uses two waves of data (pre and posttests), only those individuals who
participated in both waves of data collection are included in these analyses; this led to the elimina-
tion of 218 participants.
7
We further restricted the analyses to those students who identified as either
White, Black, or Hispanic. A total of 1,222 students met the criteria necessary to be included in the
final sample for this study.
Measures
Direct and indirect bullying victimization. Students were asked in the initial wave of data collection
how many times in the previous 6 months they had experienced each of the five types of bullying. At
the second data collection, they were then asked to indicate the number of times they had such
experiences in the previous 3 months. Response categories for each wave included: never, once, and
two or more times within the reference period. The 5 bullying items were then classified into two
distinct types of victimization: direct and indirect forms of bullying. Direct bullying is measured via
two questions tapping physical violence or threats of violence: (a) ‘Have you been attacked or
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threatened on your way to or from school’ and (b) ‘Have you been threatened or attacked at
school?’ Indirect bullying includes three questions: (a) ‘Have you had mean rumors or lies spread
about you at school;’ (b) ‘Have you been made fun of at school because of your looks or the way
you talk; and (c) ‘Have you had sexual jokes, comments, or gestures made to you at school?’
8
The direct and indirect bullying items were then summed within each wave to capture multiple
instances of victimization. Next, these wave-specific measures were combined across waves. This
resulted in three categories of direct bullying: (a) those who reported no direct bullying victimization
across both waves; (b) intermittent victims—students who reported multiple instances of direct bul-
lying during only one data collection period or those who experienced direct forms of bullying once
during each reporting period; and (c) repeat victims—those who experienced direct bullying two or
more times during both reporting periods. Similar categories—no victimization, intermittent, and
repeat victimization—were created for indirect bullying. This allowed us to assess whether different
levels of bullying victimization have unique correlates as well as the influence of different levels of
each type of bullying (i.e., intermittent or repeat) on the consequences of being bullied. In other
words, does bullying that occurs on multiple occasions across multiple waves of data produce more
negative consequences than does intermittent victimization?
Correlates of victimization. A number of relevant correlates of victimization were included in our
models predicting experiences of bullying. First, because previous research (e.g., Burrow & Apel,
2008; Wilcox et al., 2006) suggests that school-level factors or context may be related to students’
likelihood of victimization, we included a measure of school climate, which taps student perceptions
of problems within their school. The 6 items included in the scale were measured at Wave 1 and
asked students how much a problem the following things were in their schools: (a) ‘Kids bullying
or teasing other children at your school,’ (b) ‘Places in your school where some students are afraid
to go,’ (c) ‘Students beating up or threatening other students at your school,’ (d)’’Kids of different
racial or cultural groups not getting along,’ (e) ‘Students bringing guns to school,’ and (f) ‘Having
things stolen at school.’ Response categories ranged from ‘not at all a problem’ to a ‘big prob-
lem’’. Factor analysis indicated that these 6 items loaded on a single factor and scale analyses per-
formed at the individual level on the school climate scale indicated high reliability (a ¼ .80). The
individual-level measure of school climate was then aggregated for each of the 15 schools repre-
sented in the sample and the corresponding measure represents the average school climate for each
school according to survey respondents in each school (range 1–3). We also included a school vic-
timization rate using our survey data—the percentage of respondents at Wave 1 in each school, who
report various types of victimization including attacks or threats at or en route to or from school and
thefts of property occurring at school. In addition to our survey data, we obtained information from
the National Center for Education Statistics (NCES; 2008) regarding the percentage of students at
each school who received free or reduced-cost lunch to serve as a proxy measure for school poverty.
Finally, we also controlled for whether the student is a minority within his or her school based on the
racial distribution within each school. This dichotomous indicator was created by comparing respon-
dent self-identification of race/ethnicity to the racial/ethnic composition of the schools as reported
by NCES. If a student was in the clear minority in the school they were coded as a 1, if the student
was in the majority (i.e., Hispanic student in a school with a large Hispanic population) that student
was coded as 0.
We controlled for various demographic factors associated with victimization, including age and
students’ self-reported race (White, Black, or Hispanic). In models predicting bullying victimiza-
tion, we also included delinquent behavior measured at Wave 1 (described below) because of the
potential overlap between delinquent activity and various forms of victimization by peers. Finally,
we examined separate models for boys and girls, which allowed for a direct comparison of the
correlates and consequences of bullying victimization for males and females.
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Consequences of victimization. One of our primary objectives was to examine the consequences of
direct and indirect bullying including self-esteem, delinquent behavior, drug use, and gang member-
ship. The self-esteem scale, modified from Rosenberg (1965), consisted of 10 items including ‘I’m a
useful person to have around’ and ‘I feel good about myself.’ Response categories ranged from
almost never to almost always (range 1–5; a ¼ .82). Delinquency involvement is a 14-item summa-
tion index from Esbensen, Osgood, Taylor, Peterson, and Freng (2001). At Wave 1, respondents
were asked to indicate how often in the previous 6 months they had engaged in a number of activ-
ities, ranging from ‘skipped classes without an excuse’ and ‘avoided paying for things such as
movies, bus, or subway rides’ to ‘attacked someone with a weapon’ and ‘sold marijuana or other
illegal drugs.’ During Wave 2, respondents were asked how often in the previous 3 months they had
engaged in the same activities. Five categorical responses of delinquent behavior included never,
1 time, 2–5 times, 6–10 times, and more than 10 times. Higher scores indicate more frequent invol-
vement in delinquency (range 0–56). Use of illicit substances was measured by students’ responses
to four questions, regarding the use of (a) tobacco products, (b) alcohol, (c) marijuana or other illegal
drugs, and (d) paint, glue, or other things a person inhales to get high. Five categorical responses of
frequency of drug use included: never, 1–2 times, about once a month, about once a week, and every
day. The 4 items were then summed to create an overall frequency score of substance use (range
0–16; Esbensen, Osgood et al., 2001). Finally, gang membership is a dichotomous indicator
measured by responses to a single item—‘‘Do you consider your group of friends to be a gang?’
9
Analytic Strategy
To determine whether there are gender differences in the correlates of bullying victimization, we
first present results from a series of multinomial logistic regression models predicting both direct
and indirect forms of victimization. In particular, we are interested in whether the correlates of dif-
ferent levels of bullying victimization are similar across gender. The models shown compare
repeated victimization versus intermittent or no victimization; the contrasting model (not shown)
is intermittent bullying versus no victimization. Because of nonindependence in the model (i.e., stu-
dents are grouped together in schools), we calculated robust standard errors using the cluster func-
tion in STATA 9.
10
To address our second research question, we estimated the effect of bullying
victimization on each of four outcomes using ordinary least squares (OLS) regression. In both cases,
we used Z tests to assess whether the coefficients for the factors differ significantly across boys and
girls (Clogg, Petkova, & Haritou, 1995).
Results
As indicated in Table 1, slightly more than half (53%) of the students in our sample are female and
the average age of students at Wave 1 is approximately 12.25 years. Hispanic students are somewhat
overrepresented in our sample (50%) because of the large number of participating schools located in
the Southwest, but there are relatively large proportions of White students (37%) and Black students
(13%) as well. In terms of bullying victimization, our results in Table 1 are consistent with previous
research suggesting that indirect bullying rates are approximately twice those of direct bullying.
Males are significantly more likely to experience direct bullying than are girls, particularly in terms
of repeat victimization. Although a majority of both boys (63.8%) and girls (70.3%) report never
being physically attacked or threatened, boys are more likely to be classified as both intermittent
and repeat victims of direct bullying than are girls. In contrast, we find that girls are significantly
more likely to experience indirect forms of bullying victimization and are more likely to be repeat
victims as well; indeed, more than one third of girls report repeated experiences of indirect
bullying.
11
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Correlates of Bullying Victimization
In Table 2, which presents the results for direct bullying, we see that, at the individual level, involve-
ment in delinquency increases the likelihood of males being repeat victims of direct bullying, rela-
tive to nonvictims. School context is also important for boys, but only in accounting for differences
between repeat and intermittent victims; repeat victimization of boys is more likely in schools with
higher overall victimization rates. Among girls, older girls are less likely to be repeat victims. Sim-
ilar to the case for boys, girls involved in delinquency are also more likely to be repeat victims of
direct bullying relative to nonvictims and intermittent victims. Whether a cause or effect, those girls
who view their schools as unsafe are more likely to be repeat victims than those reporting no direct
bullying. Overall, however, based on the z tests, we find no significant differences in the correlates
of direct bullying across gender. In terms of our original research question, this suggests that there
are not gender-specific correlates of direct bullying victimization.
Turning to the results of the regression models predicting indirect bullying in Table 3, we see a
number of important differences from the previous models. Race has a significant impact on the
Table 1. Descriptive Characteristics of the Sample
Total Sample Boys Girls
%/Mean (SD) %/Mean (SD) %/Mean (SD)
Gender
Male 46.7%
Female 53.3%
Race
White 37.0% 40.4% 34.1%
*
Black 13.2% 12.0% 14.2%
Hispanic 49.9% 47.5% 51.7%
School minority 27.8% 28.7% 27.1%
Age 12.25 (.97) 12.31 (.99) 12.21 (.95)
*
School context
School victimization rate 44.91 (8.25) 44.17 (8.33) 45.53 (8.12)
*
School climate 1.87 (.12) 1.86 (.12) 1.87 (.12)
Free/reduced-cost lunch 70.98 (22.84) 70.55 (22.49) 71.28 (23.15)
Consequences
Delinquency, Wave 1 2.52 (4.55) 3.28 (5.35) 1.85 (3.60)
*
Delinquency, Wave 2 3.73 (5.75) 4.37 (6.81) 2.52 (4.47)
*
Gang membership, Wave 1 7.0% 8.6% 5.4%
*
Gang membership, Wave 2 9.0% 10.8% 7.4%
*
Self-esteem, Wave 1 3.85 (.66) 3.84 (.67) 3.87 (.66)
Self-esteem, Wave 2 3.88 (.68) 3.89 (.66) 3.87 (.70)
Substance use, Wave 1 0.55 (1.46) 0.60 (1.53) 0.50 (1.40)
Substance use, Wave 2 0.27 (1.00) 0.35 (1.12) 0.21 (.84)
*
Indirect bullying victimization
Never 29.4% 35.9% 24.1%
*
Intermittent 38.2% 37.2% 38.9%
Repeated 32.4% 26.9% 37.0%
*
Direct bullying victimization
Never 67.2% 63.8% 70.3%
*
Intermittent 27.6% 29.4% 26.0%
Repeated 5.2% 6.8% 3.7%
*
*
Significant gender differences at p < .05.
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likelihood of victimization; both White and Black males are more likely than Hispanic males to be
repeat victims of indirect bullying. Increased involvement in delinquent behavior is also consistently
related to repeated indirect bullying among boys whereas age is related to a decreased likelihood of
repeated indirect bullying. Interestingly, boys who are part of the ethnic minority in their schools are
less likely to experience repeated, compared to no, indirect bullying. School factors are also related
to boys’ experiences; school poverty levels are associated with an increase in the risk of repeated
Table 2. Multinomial Logistic Regression, Direct Bullying Victimization
Repeated vs. Never
a
Repeated vs. Intermittent
Boys Girls Boys Girls
b (SE)
b
b (SE)
b
b (SE)
b
b (SE)
b
Individual characteristics
White .611 (.593) .946 (.583) .332 (.590) 1.005 (.611)
Black .305 (.969) 1.836 (1.717) .277 (.924) 2.481 (1.708)
Age .558 (.289) .608 (.294)* .458 (.251) .694 (.322)*
Delinquency
c
.188 (.040)* .168 (.004)* .075 (.022)* .071 (.025)*
Minority status in school .219 (.570) 1.305 (1.152) .111 (.554) 1.822 (1.180)
School characteristics
Free/reduced-cost lunch .006 (.013) .006 (.013) .010 (.012) .022 (.013)
School climate .435 (1.849) 3.353 (1.419)* .492 (1.781) .528 (1.628)
School victimization rate .045 (.027) .035 (.050) .044 (.022)* .032 (.047)
Constant 1.014 (5.541) 4.879 (8.059) 3.016 (4.997) 1.713 (8.713)
a
Reference category is Intermittent vs. Never.
b
Standard errors (SE) are adjusted for clustering within 15 schools.
c
Delinquency is measured at Wave 1.
* p < .05.
Table 3. Multinomial Logistic Regression, Indirect Bullying Victimization
Repeated vs. Never
a
Repeated vs. Intermittent
Boys Girls Boys Girls
b (SE)
b
b (SE)
b
b (SE)
b
b (SE)
b
Individual characteristics
White .848 (.226)* .516 (.398) .917 (.385)* .035 (.236)
Black 1.124 (.447)* .479 (.480) 1.535 (.646)* .112 (.344)
Age .499 (.123)* .010 (.131) .456 (.090)* .056 (.093)
Delinquency
c
.132 (.050)* .432 (.098)* .053 (.022)* .156 (.039)*
Minority status in school .656 (.250)* .193 (.242) .463 (.448) .073 (.238)
School characteristics
Free/reduced-cost lunch .010 (.008) .0002 (.008) .022 (.008)* .007 (.005)
School climate .127 (1.341) 1.477 (.932) 1.359 (1.186) .486 (.638)
School victimization rate .009 (.019) .039 (.013)* .0002 (.016) .020 (.006)*
Constant 3.759 (2.901) .519 (2.487) 5.578 (2.273) .987 (1.838)
Note: Coefficients in boldface represent significant gender differences at p < .10.
a
Reference category is Intermittent vs. Never.
b
Standard errors (SE) are adjusted for clustering within 15 schools.
c
Delinquency is measured at Wave 1.
* p < .05.
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versus intermittent indirect bullying. As is the case for boys, girls who are involved in delinquent
activity are at greater risk of repeated indirect bullying. Finally, the overall school victimization rate
is also significantly and positively related to girls’ likelihood of repeated indirect bullying.
A number of significant gender differences emerge and are also shown in Table 3. Various indi-
vidual factors are related to boys’, but not girls’, experiences of repeated indirect bullying victimi-
zation. For example, being Black and attending schools in which a greater proportion of students
receive free or reduced-cost lunch are related to increased victimization among boys but not among
girls. In contrast, older boys and those who are minorities in the school context have decreased risks
of victimization, but neither age nor race affects the risks of indirect bullying among girls. Interest-
ingly, the effect of delinquent involvement is significant for both boys and girls, but has a greater
impact on girls’ likelihood of repeated indirect bullying.
Consequences of Bullying Victimization
Next, we turn to our second research question—a comparison of the consequences of bullying vic-
timization across gender. In Table 4, we see that there is no effect of bullying on boys’ self-esteem,
net of controls (Model 1). In contrast, repeated—but not intermittent—indirect bullying is associated
with a significant reduction in self-esteem for girls. For both boys and girls, direct and indirect bul-
lying victimization is related to increased involvement in delinquent behavior (Model 2) at the sec-
ond wave of data collection, net of other factors. Intermittent, but not repeated, bullying—including
both direct and indirect forms—increases boy’s involvement in delinquency. However, intermittent
direct bullying and repeated indirect forms of bullying are related to girls’ participation in delin-
quency. As shown, the effect of intermittent indirect bullying victimization is significantly different
for boys than girls; specifically, intermittent indirect bullying appears to increase boys’ risk of enga-
ging in delinquent activity but there is no corresponding risk among girls (although repeated forms
of indirect bullying are indeed significant for girls). We see in Model 3 that, among boys, intermit-
tent direct bullying victimization is related to an increase in drug use at the second data collection yet
repeated indirect forms of bullying are associated with decreased drug use. In contrast, repeated
indirect bullying victimization increases girls’ drug use at the second wave of data collection. The
effect of repeated indirect bullying is significantly different for girls compared to boys. Finally,
Model 4 shows the effects of direct and indirect forms of bullying victimization on gang member-
ship, net of other factors. For boys, similar to the results for delinquency, those who experienced
intermittent—but not repeated—direct bullying were more likely to report membership in a gang
at the second data collection. There was no effect of indirect bullying on gang membership among
boys. In contrast, only repeated indirect bullying victimization is related to gang membership for
girls, and again this effect is significantly greater among girls.
12
Discussion and Conclusion
Research on bullying and its consequences has garnered a great deal of public attention in recent
years. Concerns over the sheer number of students affected, as well as the resulting effects on vic-
tims, have brought about a number of efforts to counter bullying within schools across the United
States and globally. Although a great deal has been learned since the first research in this area, there
are still a number of unanswered questions about bullying victimization experiences. In the current
research, we examined whether the correlates of bullying victimization differ by gender. Second,
although a great deal of existing research highlights the consequences of bullying on the health and
well-being of victims, we sought to examine, using panel data, whether these consequences differ
among boys and girls and by type of victimization experienced. Our findings, overall, suggest a
number of important similarities and differences in the victimization experiences of boys and girls.
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Table 4. Consequences of Bullying Victimization at Wave 2
(1) Self esteem (2) Delinquency (3) Drug use (4) Gang membership
Boys Girls Boys Girls Boys Girls Boys Girls
b (SE)
a
b (SE)
a
b (SE)
a
b (SE)
a
b (SE)
a
b (SE)
a
b (SE)
a
b (SE)
a
Outcomes at Wave 1
Self esteem .621 (.059)* .641 (.030)*
Delinquency .806 (.061)* .790 (.078)*
Drug use .398 (.050)* .326 (.061)*
Gang membership 2.335 (.483)* 3.007 (.478)*
Individual characteristics
White .046 (.067) .176 (.047)* .020 (.549) 1.128 (.149)* .072 (.099) .005 (.033) .168 (.368) 1.211 (.542)*
Black .001 (.073) .189 (.062)* .093 (.398) .207 (.363) .117 (.094) .028 (.099) .871 (.329)* .148 (.582)
Age .022 (.037) .025 (.030) .477 (.427) .350 (.125)* .109 (.069) .071 (.021)* .136 (.195) .272 (.194)
Bullying victimization
Intermittent direct
b
.069 (.064) .012 (.057) 1.699 (.683)* 1.281 (.363)* .277 (.128)* .058 (.086) .531 (.239)* .403 (.498)
Repeated direct .077 (.163) .015 (.109) 2.082 (1.131) 1.438 (1.289) .464 (.238) .023 (.242) .672 (.417) .058 (.850)
Intermittent indirect
c
.013 (.056) .026 (.056) 1.108 (.494)* .196 (.200) .180 (.088) .077 (.047) .006 (.253) .047 (.330)
Repeated indirect .018 (.031) .100 (.030)* .088 (.335) .570 (.224)* .125 (.044)* .049 (.046)* .096 (.165) .653 (.279)*
Constant 1.795 (.546)* 1.703 (.384)* 4.931 (5.384) 3.551 (1.520)* 1.300 (.882) .838 (.265)* 4.566 (2.408) 6.973 (2.114)*
NOTE: Coefficients in boldface represent significant gender differences at p < .10.
a
Standard errors (SE) are adjusted for clustering within 15 schools.
b
Reference category is no direct bullying victimization.
c
Reference category is no indirect bullying victimization.
* p < .05.
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In line with the previous research, our findings suggest that indirect forms of bullying
victimization are more prevalent as compared to direct bullying within our sample of
middle-school aged students; nearly one third of the students reported repeated experiences of
indirect bullying during the study. Not surprisingly, boys were more likely to experience direct or
physical forms of bullying and girls were more likely to report being teased or joked about. We see
no gender differences, however, in those correlates that were related to direct forms of bullying.
Race and age were not related to the likelihood of direct forms of bullying victimization for either boys
or girls, yet involvement in delinquency increased the risk of physical victimization equally for boys and
girls (but see Wilcox, Tillyer, & Fisher,2009). This is not entirely surprising, given the persistentvictim–
offender overlap found in research on delinquent behavior (e.g., Lauritsen, Sampson, & Laub, 1991;
Sampson & Lauritsen, 1990) as well as research within the bullying literature, which indicates that stu-
dent involvement in bullying falls on a continuum wherein students can be involved as a bully,a victim, a
bully–victim, and/or a bystander (Espelage & Swearer, 2003). Our results suggest that, for direct bully-
ing—including physical violence and threats of violence—prevention and intervention efforts can be
gender-neutral in their approach. In particular, efforts to reduce students’ involvement in delinquent and
criminal activity should also reduce their risk of being bullied at or en route to school.
In contrast, there are a number of gender differences in the correlates of indirect bullying
victimization, suggesting the need for gender-specific efforts to reduce this type of victimization.
Specifically, age, race, and school poverty were all important correlates of boys’ likelihood of
experiencing indirect bullying but were unrelated to girls’ experiences. Although there was a rela-
tively strong protective effect of age among boys in terms of indirect bullying, girls in our sample did
not benefit in the same way. Previous research has also found that the use of indirect aggressive stra-
tegies actually increases with age for girls but not for boys (Bjorkqvist, Lagerspetz, & Kaukiainen,
1992). As indirect aggression requires social and verbal skills, perhaps girls—because they develop
verbally more quickly—develop indirect strategies earlier than do boys. Thus, part of the maturation
and development process for girls may lead to both increased use of indirect bullying strategies as
well as increased victimization. Age-specific programming, or at least sustained efforts into the high
school years, may be necessary to combat indirect forms of bullying, particularly among girls.
Second, although involvement in delinquency was significantly related to indirect bullying victimiza-
tion for both boys and girls, it had a comparatively larger effect for girls. Thus, it appears for girls,
indirect bullying victimization is associated less with individual or school characteristics and more
with their involvement in certain activities. As delinquency still is less socially acceptable for girls,
perhaps girls who are engaged in such activities experience more teasing and harassment due to their
involvement in behavior that is seen as gender inappropriate. Alternatively, it could be that girls
involved in delinquency are associating with other delinquents in unsupervised situations, thus increas-
ing their own risk of victimization. Again, prevention and intervention efforts targeting delinquent
involvement may also be helpful in reducing indirect forms of bullying victimization among students.
Our results also demonstrate that bullying victimization has a number of detrimental conse-
quences for students. However, these consequences are conditioned by the frequency and type of
bullying experienced and by the gender of the victim. Specifically, intermittent direct bullying
appeared to be related to our outcome variables at the second wave of data collection, yet in most
cases, it was repeated indirect bullying that was associated with these emotional and behavioral
responses. This suggests that even occasional physical violence may contribute negatively to student
well-being and behavior, but in most cases, only repeated teasing or harassment is related to these
outcomes. One exception, however, is that for boys, it is the intermittent, rather than the repeated,
indirect bullying that was associated with delinquency. This may reflect a threshold effect of bully-
ing on delinquency for boys. Those boys who experience repeated forms of bullying may also be
prevented from spending time with students who are engaged in delinquent activities, thus limiting
their own involvement in delinquency.
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In contrast, repeated indirect bullying is associated with gang membership among girls at the
second wave of data collection. Girls who repeatedly are teased or have sexual jokes told about them
may seek protection from gangs. Whether girls in our sample joined gangs in the hope of preventing
some of the repeated harassment they were experiencing, as a primary reason individuals join gangs
is for protection and to address their fear of victimization (Melde, Taylor, & Esbensen 2009), or they
experienced teasing because they were affiliated with gangs and gang members is unclear.
Overall, however, we find that the gender differences were not statistically significant; in other
words, bullying does not appear to have gender-specific consequences in terms of gang membership.
Bullying victimization does, however, have gender-specific consequences in terms of drug use.
We find that repeated indirect bullying actually decreased drug use among boys, perhaps because
those boys who are teased repeatedly may be excluded from peer groups in which drug use may
occur, yet it increases use among girls. As was the case with delinquency, girls who use drugs may
put themselves at risk of increased teasing or having rumors told about them because the use of drugs
is less socially acceptable among girls. Alternatively, the stress of repeated bullying may lead girls to
use drugs as a way to escape. Finally, while bullying victimization was related in some way to delin-
quency, gang membership, and drug use for both boys and girls, only girls reported decreased self-
esteem at the second wave of data collection. Consistent with previous research (e.g., Gruber &
Fineran, 2008), this suggests that although bullying victimization may be related to behavioral man-
ifestations (i.e., delinquency) among both boys and girls, it may have more negative psychological
consequences on girls. That bullying may have a greater psychological impact on girls is important
information for school officials and counselors who work with students as they address bullying
within their schools.
Our findings are tempered by some important limitations. First, boys are more likely to perpetrate
both direct and indirect bullying and there is also some evidence that being victimized by a boy may
have greater consequences for victims than the experience of bullying by a girl (Felix & McMahon,
2006). Unfortunately, we have no information on the characteristics (i.e., gender and race) of the
bullying perpetrators and subsequently are unable to determine the extent to which power differen-
tials, such as in strength, size, or status, may influence our findings. There are also limitations in the
types of bullying victimization that we were able to examine with our data. For example, although
we were able to capture the extent to which students had sexual jokes and gestures made toward
them, this indicator did not capture physical sexual harassment including unwanted touching or
groping. This may be an important area to explore in the future because for both boys and girls, the
behaviors involving sexual harassment as we measured them were the second most frequent type of
bullying experienced. While previous research suggests that even observing bullying can result in
similarly negative consequences for students, we did not have such an indicator. On one hand, as
we are specifically interested in personal victimization, this should not undermine the conclusions
we can draw from our data. At the same time, though, children who observe bullying and peer vic-
timization are focused not on learning, as they should be, but rather on concerns regarding their own
safety, which may then affect their perceptions of their schools as well as their behaviors. Finally,
recent research by Hinduja and Patchin (2008) finds that ‘cyber-bullying’ experiences are related to
school problems, problem behaviors, and experiences of other forms of bullying as well. They high-
light the hurtful nature of such experiences with descriptions from the victims themselves, but sur-
prisingly do not find gender differences in the prevalence of cyber-bullying victimization. While
unfortunately we do not have measures of the sorts of online bullying they describe for our sample,
given our findings, future research might continue to examine the role of gender in cyber-bullying
and its consequences.
Despite these limitations, the quite clear gender differences in the correlates and consequences of
bullying victimization we find suggest important implications for future prevention efforts. Current
school safety policies have largely been constructed without attention to different forms of bullying
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that may occur and without acknowledgment that student characteristics such as gender have
profound implications on the likelihood and consequences of such experiences. Specifically, most
programs appear to primarily target the more serious types of bullying victimization—physical
violence. Yet, our findings suggest that the indirect forms are clearly linked with a number of con-
sequences among students and the impact of these experiences differs by gender. Rather than focus
only on preventing physical violence, schools should send strong messages to students and teachers
alike that all forms of bullying and harassment are inappropriate. If ignored, such low-level violence
may continue to jeopardize students’ health and well-being, particularly among girls, and may even
contribute to involvement in delinquent behavior and retaliatory violence. Moreover, existing
programs may be geared toward the behavior and experiences of boys which may, in some cases,
actually contribute to increases in bullying among girls (e.g., Eslea & Smith, 1998). Our results sug-
gest that future efforts to reduce and prevent bullying behaviors within schools must extend beyond
the stereotypic notion that boys are those most affected by bullying. As indirect bullying is often less
overt than physical forms, it is less likely that teachers and school personnel will notice such beha-
viors. At the same time, prevention efforts rely on students to report their victimization experiences
to school officials. If such experiences are not included as within the scope of anti-bullying work, it
may be harder for those students—who are likely to be predominantly female—to come forward
and ask for assistance. Thus, schools should actively seek to foster an environment conducive to
reporting all forms of bullying and victimization.
Notes
1. We are sensitive to the potential importance of the third criterion, however, we are not able to address this
power differential issue in our research, in part because it is somewhat difficult to convey to adolescents. The
first two criteria of Olweus’ definition are the focus of our examination.
2. Although we focus primarily on bullying victimization, similar gender differences have been found for per-
petration; boys appear to be more likely to use direct forms of violence against peers and girls are more likely
to use indirect forms of violence, particularly relational aggression (e.g., Crick & Grotpeter, 1995).
3. Some studies find that rates of violent victimization in school do not differ by race or ethnicity (e.g., Nansel
et al., 2001; Seals & Young, 2003; Snyder & Sickmund, 2006), yet others suggest that students of color are
less likely to report being victims of bullying than White students (e.g., Hanish & Guerra, 2000; Juvonen,
Graham, & Schuster, 2003; Spriggs, Iannotti, Nansel, & Haynie, 2007). One problem inherent with many of
these studies, particularly the earlier ones, is that students of color are vastly underrepresented in the samples
used. Furthermore, except in a handful of studies, ethnicity has not been a focus; indeed, the comparison is
usually made between White and Black students.
4. The U.S. Secret service has advanced an extreme consequence of being bullied, indicating that the profile for
many of the perpetrators of school shootings includes having been bullied. However, we urge caution in
implying such consequences of being a victim of bullying. If being bullied is responsible for school shoot-
ings, then we would have a lot more shootings; virtually all victims of bullying do not become school
shooters.
5. The students participating in the evaluation resemble all students in their schools; that is, the sample
demographics are similar to the school-level demographics.
6. Although program participation raises the potential for bias, a process evaluation determined that the
program was implemented with insufficient fidelity to have any effect. This implementation failure led to
discontinuation of the outcome analysis after the Wave 3 data collection. Outcome analyses found no dif-
ferences between the treatment and comparison groups. Contact authors for more detailed information about
the process and outcome evaluations.
7. As is the case in most panel studies that report attrition analyses (e.g., Esbensen, Miller, Taylor, He, & Freng,
1999; Thornberry, Krohn, Lizotte, & Chard-Wierschem, 1993), we experienced differential attrition. That is,
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the 218 students excluded from the analysis sample tended to be at higher risk of delinquency and other
adolescent problem behaviors than those students included in the final sample.
8. Some scholars have recently argued against subsuming sexual harassment and sexual violence under bul-
lying (e.g., Brown, Chesney-Lind, & Stein, 2007) whereas others have suggested such experiences be
termed ‘sexual bullying’ (Shute, Owens, & Slee, 2008). This is because, in some cases, even ‘egregious
behaviors’ are labeled as bullying when they would otherwise be considered sexual harassment and, there-
fore, be illegal and punishable within the criminal court. Unfortunately, the schools involved would not
allow us to ask students about sexual experiences including sexual harassment and victimization. For this
reason, we are unable to examine the full range of gender-based violence. Other scholars have provided a
much more detailed examination of sexual harassment and other forms of gender-based violence, including
both individual and environmental correlates of such experiences (e.g., Fineran & Bolen, 2006; Miller,
2008; Shute et al., 2008).
9. While some surveys use a single item (e.g., ‘Are you a member of a gang?’’) to measure gang affiliation
(e.g., Thornberry, Krohn, Lizotte, Smith, & Tobin, 2003), others have used additional criteria such as invol-
vement in illegal activities and possession of some organizational characteristics to classify gang members
(e.g., Esbensen & Huizinga, 1993). There is growing consensus, however, that the self-nomination tech-
nique is quite robust (see, e.g., Esbensen, Winfree, He, & Taylor, 2001). Accordingly, in the present survey,
gang membership was measured through a single item self-report measure.
10. This nonindependence does not affect the coefficients but does produce invalid standard errors. The cluster
function uses a so-called sandwich estimator in the calculation of the standard errors, producing ‘robust’
standard errors that do not make assumptions about the distribution or the within-cluster dependence of the
residuals (Rabe-Heketh & Skrondal, 2005).
11. When examining the frequencies for the individual response items, we see that assaults or threats of
assaults at school are more likely to be reported by both boys and girls than assaults or threats en route
to or from school. Less than 5% of boys and less than 2% of girls had repeated experiences of either of
the direct forms of bullying. Of the indirect bullying items, for boys, repeated experiences of being made
fun of were most common (11%), followed by sexual jokes or gestures (10%). Girls more commonly
reported repeated rumors/lies told about them (15%); the next most frequent form of indirect bullying for
girls was sexual jokes or gestures as well (14%).
12. Analyses were also performed using change scores from Wave 1 to Wave 2 for the consequences. Results
indicated that the effects of bullying victimization were similar to those presented. We elected to present
models controlling for Wave 1 measures of consequences to control for possible omitted variable bias and
for parsimony.
Authors’ Note
An earlier version of this paper was presented at the 2009 Western Society of Criminology annual
meeting in San Diego, CA.
Acknowledgment
The authors wish to thank Jody Miller, Lee Ann Slocum, and the editor for their helpful comments.
Declaration of Conflicting Interests
The authors declared no conflicts of interest with respect to the authorship and/or publication of
this article.
Funding
The authors disclosed receipt of the following financial support for the research and/or authorship of
this article: This research was funded by the National Institute of Justice, Office of Justice Programs,
346 Youth Violence and Juvenile Justice 8(4)
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U.S. Department of Justice, Award # 2003-JN-FX-0003. Points of view in this document are those of
the authors and do not necessarily represent the official position of the U.S. Department of Justice.
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Bios
Kristin Carbone-Lopez is an assistant professor in the Department of Criminology and Criminal Justice, Uni-
versity of Missouri, St. Louis. Her research focuses on gender and the overlap between crime and victimization.
Finn-Aage Esbensen is the E. Desmond Lee Professor of Youth Crime and Violence and Chair of the Depart-
ment of Criminology and Criminal Justice, University of Missouri, St. Louis.
Bradley T. Brick is an assistant professor in the Department of Sociology and Criminal Justice, Old Dominion
University. His research focuses on the areas of communities and crime, social control, and delinquency.
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... School characteristics included negative school climate, violent school context, school disorder, urban school, school size, and school security devices. Negative school climate captured various indices that tapped into perceptions of the school environment as hostile, unfriendly, or unwelcoming; such as the school having unclear or unfair rules; or the school having negative teacher, staff, or student interactions (Bae, 2016;Carbone-Lopez et al., 2010;Rinehart & Espelage, 2016). Violent school context included measures of violence and victimization at the school level, as well as student perceptions about how common or how much of a problem violence was at school. ...
... Specifically, with respect to domains of school climate, violent school context, and school disorder, there were studies that assessed school perceptions of these factors among individuals (e.g., Astor et al., 2006;Carbone-Lopez et al., 2010;Goldstein et al., 2008;Juvonen et al., 2016;Moon & Alarid, 2015), and others that aggregated individual perceptions to the school level (e.g., Attar-Schwartz, 2009;Zaykowski & Gunter, 2012). Some studies also included both school-and individual-level measures to aid in the interpretation of school-level contextual effects (e.g., Gottfredson & DiPietro, 2011). ...
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School violence is a significant social concern. To better understand its sources, a comprehensive meta-analysis of the school violence and victimization literature was undertaken. Across 761 studies, the relative effects of 30 different individual, school, and community level correlates were assessed (8,790 effect size estimates). Violence and victimization were conceptualized broadly to include various forms of aggression and crime at school. The results revealed that the strongest correlates of school violence perpetration were antisocial behavior, deviant peers, antisocial attitudes, victimization, and peer rejection; and that the strongest correlates of school victimization were prior/other victimization, social competence, risk avoidance, antisocial behavior, and peer rejection. Extracurricular activities and school security devices had among the weakest associations in the meta-analysis, and several traditional criminological predictors did not perform well in the school context. We conclude with recommendations for theory, future research, and policy.
... When examining outcomes, it is important to consider the type of experience and the gender of the victim. Using longitudinal data, Carbone-Lopez et al. (2010) found that female students who experience repeated indirect victimization (e.g., teasing) are at greater risk for emotional and behavioral responses than male students who encounter intermittent direct victimization (e.g., physical violence). Further differences among gender for the types of victimization and their associated PTSD symptoms are noted in the literature. ...
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This conceptual paper makes the case that peer victimization should be considered a potentially traumatic event due to the similarities between peer victimization and trauma in terms of definition, outcomes, theoretical frameworks, and measurement. Furthermore, there is a trend to include peer victimization on surveys measuring adverse childhood experiences and other childhood trauma. We conclude with a call for changes to the intervention and prevention efforts in the area of peer victimization. Both whole-school initiatives and programs targeting victimized students should address peer victimization in the same manner as other traumatic events in childhood.
... This association was not found in boys. This might be explained by differences in the type of peer victimisation by sex, for instance physical versus social [33]. Few studies have examined the association of HL with subsequent peer victimisation and we did not identify any published studies assessing whether this varies by child sex [14,[34][35][36]. ...
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Background Childhood hearing loss (HL) predicts poor mental health and is associated with a higher risk of communication difficulties. The relationship of childhood HL with specific types of poor mental health (such as depressive symptoms or self-harm) and peer victimisation remains unclear. Methods We analysed data from the Millennium Cohort Study (MCS), a prospective observational cohort study of children living in the UK at age 9 months and born between 2000 to 2002. Data were available on the children and their families at ages 9 months, then at 3, 5, 7, 11, and 14 years. Participants were 10,858 singleton children with self-reported data on peer victimisation, depressive symptoms, and self-harm at age 14 years. Multivariable logistic regression models were fitted to estimate odds ratios (OR) for HL with peer victimisation, depressive symptoms, and self-harm. HL presence was examined in terms of any HL between ages 9 months and 14 years, as well as by HL trajectory type (defined by onset and persistence). Analyses were adjusted for potential sources of confounding, survey design, and attrition at age 14 years. Interactions between sex and HL were examined in each model and multiple imputation procedures used to address missing data. Results Children with any HL had increased odds of depressive symptoms (OR: 1.32, 95% CI: 1.09–1.60), self-harm (1.41, 1.12–1.78) and, in girls only, peer victimisation (girls: 1.81, 1.29–2.55; boys: 1.05, 0.73–1.51), compared to those without HL. HL with later age at onset and persistence to age 14 years was the only trajectory associated with all outcomes. Conclusions Childhood HL may predict peer victimisation (in girls), depressive symptoms, and self-harm. Further research is needed to identify HL trajectories and methods to facilitate good mental health in children with HL.
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Background: Research on perceived school safety has been largely limited to studies conducted in Western countries and there has been a lack of large-scale cross-national studies on the topic. Methods: The present study examined the occurrence of adolescents who felt unsafe at school and the associated factors of perceived school safety in 13 Asian and European countries. The data were based on 21,688 adolescents aged 13-15 (11,028 girls, 10,660 boys) who completed self-administered surveys between 2011 and 2017. Logistic regression analyses were used to estimate odds ratios and 95% confidence intervals. Findings: The number of adolescents who felt unsafe at school varied widely across countries, with a mean occurrence of 31.4% for the total sample: 31.3% for girls, and 31.1% for boys. The findings revealed strong independent associations between feeling unsafe and individual and school-related factors, such as being bullied, emotional and behavioral problems and feeling that teachers did not care. The study also found large variations in perceived school safety between schools in many countries. Conclusion: The findings emphasize the need to create safe educational environments for all students, based on positive relationships with teachers and peers. School-based interventions to prevent bullying and promote mental health should be a natural part of school safety promotion.
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Background and Objective: The relationship of borderline personality traits with childhood teasing and traumatic experiences is a major risk factor in the development of borderline personality disorder (BPD) symptoms; nonetheless, this relationship is not fully understood. The present study aimed to provide further evidence on the role of childhood teasing, traumatic experiences, and other pathological personality traits, such as negative affectivity, antagonism, psychoticism, disinhibition, detachment, depression, anxiety, and stress symptom, in the development of borderline personality disorder, especially in Iranian non-clinical populations.
... Female socialization experiences emphasize self-sacrifice to meet the needs of others, and females are more hypercritical and critical of themselves, which may lead to lower levels of self-compassion (DeVore, 2013;Sun et al., 2016). When females face the negative interpersonal relationship of bullying victimization, they may increase their susceptibility to negative consequences (Carbone-Lopez et al., 2010), and even blame and criticize themselves, and cannot further suppress depression through self-compassion. Compared to females, males have slightly higher levels of self-compassion and males attach importance to self-assertion and independence, and males may be more willing to take their own needs seriously and sympathize with themselves in times of crisis (Yarnell et al., 2019). ...
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Background Left-behind children (LBC) in China have aroused widespread concern in society and the academic field because they have a high risk of psychological problems. For left-behind children, depression is the most serious problem. Bullying victimization has been evidenced as one of the most common causes of children’s depression. However, less is known about its longitudinal association and the process for how bullying victimization influences depression among left-behind children. Thus, the presentation aims to explore the mechanisms underlying by considering the roles of left-behind children’s negative thoughts and self-compassion. Methods The 3-wave longitudinal data were collected from a sample of 605 aged 8–11 from central China. We used the Olweus bully and victimization questionnaire, the children’s automatic thoughts scale, the depression scale, and the self-compassion scale. Results Bullying victimization positively predicted the depression level of left-behind children. Negative thoughts and self-compassion mediate the relationship between bullying victimization and depression. In the mechanism of bullying victimization on depression exists gender differences among left-behind children. Conclusion The present study suggested the association between bullying victimization and left-behind children’s depression and revealed the internal mechanism of negative thoughts and self-compassion. These findings provide a new perspective for left-behind children’s mental health education and intervention.
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Over the past two decades, bullying has received a lot of negative attention, with educators, parents, and youths expressing concerns regarding bullying at schools. However, bullying also occurs outside of schools, and the internet provides a platform that allows bullying to extend beyond the traditional school day. Scholars identify this form of bullying as cyberbullying. Research regarding the relationship between gender and cyberbullying remains unclear. Therefore, using an interdisciplinary approach, this chapter examines gender differences in cyberbullying. Merging theoretical insights from criminology, sociology, and gender studies, this chapter explores how male and female youths utilize the internet to engage in cyberbullying. This chapter also considers the implications of gender differences in cyberbullying for future research and policy development.
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This study explores the relationship among multiple forms of peer victimization (e.g., direct physical/verbal, relational, and sexual harassment) and psychosocial adjustment among urban students and uses cluster analysis to identify subgroups of victims. Students in sixth, seventh, and eighth grade completed self-report surveys about their psychosocial adjustment, peer victimization experiences, and the gender of the other person involved. Results reveal that both physical/verbal victimization and sexual harassment were related to internalizing behavior, and sexual harassment was related to externalizing behavior. Cluster analysis revealed preliminary subgroups of victims. In addition, being victimized by a boy was more strongly related to behavior problems for both boys and girls than the experience of being victimized by a girl. Results suggest that the gender of perpetrators and victims should be considered, and there is a need to include sexual harassment in the study of peer victimization when developmentally appropriate.
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This study investigated the prevalence of bullying and victimization among students in grades 7 and 8. It also explored the relationship of bullying and victimization to gender, grade level, ethnicity, self-esteem, and depression. Three survey instruments were used to obtain data from a convenience sample of 454 public school students. Twenty-four percent reported bullying involvement. Chi-square tests indicated significantly more male than female bullying involvement, seventh graders reported more involvement than did eighth graders, and there were no statistically significant differences in involvement based on ethnicity. Both bullies and victims manifested higher levels of depression than did students who were neither bullies nor victims. There were no significant differences between groups in terms of self-esteem.
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Björkqvist, Lagerspetz, and Kaukiainen [(1992): Aggressive Behavior 18: 117–127] suggested that there are significant differences in the types of aggressive behaviour–direct physical, direct verbal, and indirect‐engaged in and experienced by boys and girls of different ages. This study reports on similar age and sex differences in the types of bullying behaviour found in British schools, based on a survey of 7,000 primary and secondary school pupils. It further relates these types of bullying to where victims were bullied, who bullied them, and whether an adult was told about bullying. Our analyses focused on whether age and sex differences characteristically found for these latter items could be explained by differences in types of bullying, or whether other factors were responsible. We also compare Olweus' measure of indirect bullying with our own. © 1994 Wiley‐Liss, Inc.
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Bullying victimization is part of the adolescent experience in most societies, yet little is known about its consequences. In this article we utilize a multisite, longitudinal data set to examine the effects of being bullied. We also explore definitional and measurement issues that confound this line of research. While some researchers have relied on a single/generic item to measure bullying, others have focused on behaviorally specific items. In addition, most prior research on bullying has relied on cross-sectional data, thereby restricting researchers’ ability to examine the consequences of prior victimization. Using three waves of data, we create a typology of victimization (nonvictims, intermittent victims, and repeat victims) that allows us to establish correct temporal ordering to examining the effects of victimization on subsequent attitudes. Importantly, we assess the consequences of bullying victimization using both a single-item indicator and a composite measure consisting of behaviorally specific questions.
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Community crime and violence intrudes into schools that are, after all, parts of the communities they serve.
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We investigated the influence of low self-control and Attention-Deficit Hyperactivity Disorder (ADHD) on bullying and bully victimization in a sample of 1,315 middle school students using a school survey. Students who reported taking medication for ADHD were at increased risk for bullying as well as victimization by bullies. The correlation between ADHD status and bullying could be explained by low self-control, a construct theorized by Gottfredson and Hirschi to be the most important determinant of criminality. In contrast, the correlation between ADHD status and bullying victimization was independent of self-control. Subsequent analyses found that self-control influenced bullying victimization through interactions with student gender and measures of physical size and strength. These findings identify low self-control and ADHD as potential risk factors for bullying and victimization and have implications for research on self-control in young adolescents.