Multiple Contexts of Adolescent Bullying
1
ABSTRACT
This paper uses an ecological perspective to explore the risk factors associated with bullying behaviors
among a representative sample of adolescents aged 11 to 14 (n = 9816 , X = 12.88, s = .9814 ). Data
derived from the Health Behavior in School Children: WHO Cross-National Survey were used to
model the relationship between bullying and media effects, peer and family support systems, selfefficacy, and school environment. Overall, the results of this study suggest that bullying increases
among children who watch television frequently, lack teacher support, have themselves been bullied,
attend schools with unfavorable environments, have emotional support from their peers, and have
teachers and parents who do not place high expectations on their school performance. In addition, we
found an inverse relationship between being Asian or African American, feeling left out of school
activities and bullying. Our results lend support to the contention that bullying arises out of deficits in
social climate, but that social support systems mediate bullying behavior irrespective of the student’s
racial/ethnic characteristics, parental income levels or media influences. Because the number of friends
and the ability to talk to these friends increases the likelihood of bullying, we suggest that bullying is
not simply an individual response to a particular environment but is a peer-group behavior. We
conclude that limiting television viewing hours, improving student’s abilities to access family support
systems and improving school atmospheres are potentially useful interventions to limit bullying
behavior.
Multiple Contexts of Adolescent Bullying
2
INTRODUCTION
Contemporary society is increasingly concerned with the right to be free from victimization
because of one’s sexuality, religion, race or physical characteristics/ limitation(s) (Smith, 2004).
Bullying, which may occur in up to 30 percent of school-age children in the U.S. (Nansel et al., 2001;
Zimmerman, 2005), is an aggressive behavior that targets individuals based on these characteristics.
The many distinct forms of harassment that occur in the context of bullying, ranging from verbal
threats to bodily injury and sexual assault, are viewed as detrimental to the physical, emotional and
psychological well-being of victims as well as perpetrators. Bullying has repeatedly been shown to be
related to more aggressive forms of violence and to be associated with negative outcomes in adulthood
(Olweus, 1991; Perry et al., 1988; Tritt & Duncan, 1997). Bullying is viewed as a serious public health
problem worthy of research and intervention (Zimmerman, 2005).
The recent attention given to understanding bullying behaviors has lead to numerous definitions
of bullying. For example, bullying has been defined as “a systematic abuse of power” (Smith and
Sharp, 1994, p. 2, emphasis added) and as repetitive, unpleasant behavior that takes place over time
(Smith & Brain, 2000). These definitions are broad and have been applied to both adults and children
in varied settings. The definition of bullying has recently expanded to include indirect aggression,
relational aggression, and social aggression, including withdrawal of friendship, spreading rumors and
excluding individuals from social groups (Smith, 2004; Crick, 1999; Underwood, 2002; Espelage &
Swearer, 2004). In general, bullying is a form of child/adolescent aggression characterized by three
primary and distinguishing features (Limber, 2004; Olweus et al., 1999): 1) behavior with the intent of
doing harm to another individual, 2) behavior repeated over time, and 3) behavior that occurs in an
interpersonal context involving an imbalance of power.
Multiple Contexts of Adolescent Bullying
3
The Multiple Contexts of Youth Development
Prior work on bullying behaviors in children and adolescents involves a broad array of
individual and contextual factors. An ecological framework that focuses on the interplay of these
individual characteristics in multi-level contexts of development is particularly useful for
understanding the complex dimensions of bullying and for developing sensitive and effective
interventions (Limber, 2006; deLara, 2006; Garbarino & deLara, 2002; Bronfenbrenner & Morris,
1998).
The primary focus of the ecological perspective to human development (Bronfenbrenner &
Morris, 1998) is on the dynamic interaction between the bully and the victim in the immediate and
more distal contexts which include this behavior. The bullying relationship in question is defined by the
interaction of the bully and the victim, including the characteristics of each, from the most immediate
and primary to the more distal but significant influences (see Figure 1). At the core of the bullying
relationship are the individual characteristics of the bully and the victim which, in turn, play out in the
various contexts, leading to relationship attributes such as dependency and/or conflict. Emphasis is
placed on understanding the bully’s individual characteristics in relation to the multiple social systems
of which he or she is an inseparable part.
[Figure 1 here]
The most immediate context of development is the microsystem which includes the direct
settings in which individuals develop (see Figure 1). A microsystemic influence focuses on the
individual’s most immediate environment, such as support for the child’s behavior in the classroom or
the larger school setting. These influences include, for example, parental involvement or interference in
the bully/victim interaction and the character of bully/victim relationships in school settings. The
mesosystem involves the interaction of two or more microsystems in influencing behavior. The joint
Multiple Contexts of Adolescent Bullying
4
contributions of two or more microsystems, such as family and school, can have a powerful impact on
the positive development of children and youth, particularly in supporting academic achievement.
Likewise, parent-teacher collaboration could prevent or mitigate physical and/or psychological damage
from bullying and thus may have a significant impact on the welfare of both individuals. From the
perspective of the bully or victim, the exosystem is a more distal context which does not directly
include the participants but which may nonetheless significantly impact them. In the case of school
bullying, exosystem factors include, among other things, the cumulative effect of school policies that
shape institutional contexts and exert an influence on specific behaviors of teachers and/or students.
For example, exosystem contextual factors could include specific staff training to reduce or prevent
bullying.
The macrosystem consists of those factors affecting the welfare of the individuals in a most
distant and least direct manner (see Figure 1). These factors include broader societal attitudes towards
violence and carrying a weapon, whether or not hazing is an accepted part of school sports teams, or
whether physically violent bullying is treated as a “boys will be boys” or “girls will be girls” behavior.
Another macrosystem variable pertains to the role of the media, which reflects cultural or subcultural
values and attitudes.
The chronosystem represents the effect of time on the behavior and on the context in which that
behavior takes place. For example, a new child at school may initially engage in bullying and/or victim
behaviors. Over time these behaviors may or may not become less prevalent. As another example,
societal attitudes towards bullying may change over time. Given that a key element of bullying
behavior is repetition of that behavior over time, the chronosystem, and the continuity of the character
of the underlying systems (see above), provide a degree of stability or habitualness to bullying
behavior. Of course, an important feature of ecologically informed interventions is that the underlying
Multiple Contexts of Adolescent Bullying
5
components of the chronosystem may be influenced or changed over time, comprising or enhancing the
welfare of individuals and their relationships.
INDIVIDUAL CHARACTERISTICS AND CONTEXTS OF BULLYING BEHAVIOR: A
REVIEW OF RESEARCH
Consistent with an ecological perspective, the review of research that follows addresses the key
individual characteristics of bullies and victims as well as the significant contexts of bullying, including
the school, the family, the peer group and the community as expressed through the media. While
attention is given primarily to research on children in the United States, there are instances where
international research is helpful, particularly in understanding and gaining perspective on bullying
among and between ethnic groups (Elsea & Mukhtar, 2000) and where international perspectives offer
insight into theoretical and methodological perspectives to bullying (Veenstra et al., 2005).
Individual characteristics of bullies. Two decades of research has painted a fairly clear picture
of the individual-level correlates of adolescent bullying. Individuals who have been bullied in the past
are more likely to bully others, have negative attitudes towards school, and engage in unhealthy
behaviors such as tobacco and alcohol use (Nansel et al., 2001). Physical bullying is more prevalent
among males whereas females are typically involved with verbal or psychological bullying (Olweus,
1991). Borg (1998) presents evidence of a parabolic relationship between bullying and age,
emphasizing that the nature of bullying changes in form from more overt/physical behaviors, common
among young children, to more covert behaviors as children get older. The relationship between
ethnicity and bullying has not been widely studied (Seals & Young, 2003), therefore findings
pertaining to the prevalence of bullying among ethnic minority students are inconclusive. For example,
some researchers have found no significant differences in bullying behaviors among different
Multiple Contexts of Adolescent Bullying
6
racial/ethnic groups (Seals & Young, 2003). On the other hand, Elsea & Mukhtar (2000), who studied
bullying in British schools, found that linguistic, religious and cultural differences among diverse
ethnic groups are factors that precipitate bullying. Given the small number of studies on the topic, the
inconsistent findings, different cultural contexts of international studies, and the failure to control for
other factors previously found to be related to bullying in multivariate analyses, bullying among ethnic
minority children is a topic that merits further attention (Elsea & Mukhtar, 2000).
Previous studies report a positive association between self-esteem and the ability to cope with
stressors (Natvig et al., 2001; Bandura, 1997). In this vein, research on bullying behavior has addressed
the relationship between bullying and self-esteem and depression (Smith & Young, 2003; KaltialaHeino et al., 1999). However, findings on these individual characteristics in relationship to bullying
behavior are not clear (Smith, 2004). Some studies have shown that the enhancement of self-esteem
and self-efficacy can be important protective factors for bullying (Rigby & Cox, 1996; O’Moore &
Kirkham, 2001), others have suggested the exact opposite, including them instead among the many risk
factors for bullying (Pearce & Thompson, 1998), and some have found no relationship at all between
self-esteem, self-efficacy and bullying (Seals & Young, 2003). These equivocal outcomes are probably
due to varying and inconsistent operational definitions of depression, self-efficacy, self-confidence, and
self-esteem. Consequently, the relationship between these psychological moods and bullying is a
research topic that merits further investigation.
School context and school climate. Relatively little is known about contextual/environmental
factors that may predispose youths to bully others (Limber, 2006; Zimmerman et al. 2005). While the
majority of bullying occurs on school grounds, little is known about the effect of school factors on
bullying behavior in primary school children (Wolke et al., 2001). Researchers who have studied
school-related factors tend to focus on the effect of school size, class size, (Batsche & Knoff, 1994;
Multiple Contexts of Adolescent Bullying
7
Olweus, 1997; Whitney & Smith, 1993; Wolke et al., 2001) and competition at school (Olweus, 1997)
on subsequent bullying (Natvig et al., 2001). Few studies have focused on the pupils’ perception of
different aspects of the school environment as potential risk factors for bullying behavior. One
exception is a study by Natvig et al. (2001) who found that school-related stress and school alienation
are potential risk factors for bullying behavior among Norwegian adolescents. The current research
extends their results by incorporating notions of students’ perceptions of the school environment.
Accordingly, we consider the relationship between school stress, as measured by excessive
parent/teacher expectations, and stress relief, such as the ability to talk to parents and friends about
difficult situations, and bullying in US schools.
Family context and family climate. Although most bullying behaviors occur in school, there is
nonetheless increasing attention to the role of family socialization and sibling relationships in bullying
and victimization. With the prominence of catastrophic high school tragedies (e.g. Columbine High
School, Virginia Tech), society has awakened to the role of parents in preventing bullying behaviors
(Lickel et al., 2003). Researchers studying families report that the parents of bullies typically lack
involvement and warmth (Olweus, 1993). Furthermore, there is evidence that bullies tend to have
relatively authoritarian parents who use—and therefore model—power assertive techniques of
discipline and physical punishment (Bowers et al., 1994; Rodkin & Hodges, 2003). In contrast to the
lack of involvement and warmth in families of bullies, there is evidence that the families of victims are
sometimes characterized by overly protective mothers who may discourage the development of
independence and self confidence in their children as well as fathers who are distant and overly critical
or permissive (Olweus, 1993; Duncan, 2004). Not surprisingly, parental maltreatment of children in the
family, including physical, emotional and sexual abuse, has been associated with both bullying and
victimization behavior in adolescents (Sheilds & Cicchetti, 2001). In addition to parental influence,
Multiple Contexts of Adolescent Bullying
8
there is evidence that bullying-victimization behaviors in school are related to being a bully or a victim
in sibling relationships (Wolke & Samara, 2004).
Peer group contextual effects. With the exception of bully-victim relationships, most peer
relationships are based on voluntary interactions that reflect mutuality, reciprocity and positive
companionship (Hartup & Stevens, 1997; Brown, 2003). Bully-victim relationships, however, are
antagonistic and based on the exact opposite characteristics. Research on bully-victim peer associations
suggests that both bullies and their victims are rejected by their peers, although bullies are the more
aggressive partner in the relationship. In the bully-victim alliance, bullies seek out vulnerable peers to
be their victims while victims appear to make themselves available targets (Brown, 2003). Bully-victim
consequences are further influenced by other peer group characteristics including ethnicity of the peer
group and broader sets of peers at the crowd level (Brown, 2003). For example, research at a
multiethnic middle school pointed to the relatively smaller number of victims and larger number of
bullies among African American peers (Graham & Juvonen, 2002). Furthermore, with the
development of larger peer crowds in adolescence, individuals can be stigmatized as a group and, in
turn, victimized or bullied by peers with more status and who are more aggressive (Merton, 1996).
Although there are distinctive characteristics influencing victim/bully outcomes, Espelage et al. (2003),
in a study of middle school early adolescent 6-8th graders, present evidence that peer group membership
and contextual effects influence and shape adolescent aggression in both bullying and fighting
behaviors.
The community as context for bullying: The role of media exposure. The role of exposure to
media violence has long been a source of concern as a potential catalyst for aggressive behavior in
children and adolescents. There is considerable evidence, and a longstanding research focus, on the
Multiple Contexts of Adolescent Bullying
9
relationship between children’s television watching and child/adolescent violence and aggression. In
particular research on violence in films, television programs, music and video games indicates
consistently and unmistakably that media violence increases the possibility of aggression and violence,
in both immediate/short term and long term contexts (Johnson, et al., 2002; Anderson, et al., 2003;
Robertson, et al., 2004). These findings are based on research with large and diverse samples, diverse
methods and diverse media venues. While the relationship between media and violence/aggression is
clearest in the case of television and film viewing, an increasing number of video game studies are
pointing to similar results (Johnson et al., 2002; Anderson et al., 2003).
The amount of influence television watching and computer game playing have on individual
development is conditional on specific factors, such as the age of the child and the level of family
supervision. However, the role of media exposure, including television watching and video game
playing, is not well understood in relation to bullying. Given the substantial research on violence and
children’s television watching, the absence of research on adolescent media experiences and bullying is
a significant omission. In fact, only two studies have specifically examined the relationship between
either television watching or computer game playing and bullying behavior: a cross-sectional sample
of youths in Switzerland and a longitudinal study of four year olds whose bullying behavior was
assessed and reported by their mothers. The former study explains media usage in terms of bullying
behavior (Kuntsche, 2004). The later study, by Zimmerman and colleagues (2005), found significant
relationships between parental emotional support, cognitive stimulation, amount of television watching
at four years of age and later bullying behavior reported at ages six through eleven. Cognitive
stimulation was assessed using information on outings, reading, playing and parental role in teaching a
child while emotional support was based on questions related to whether the child ate meals with both
parents, parents talked to the child while working and spanking. According to the authors, “maximizing
Multiple Contexts of Adolescent Bullying
10
cognitive stimulation and limiting television watching in the early years of development might reduce
children's subsequent risk of becoming bullies” (Zimmerman, 2005; p. 388).
While some attention has been paid to the effect of television watching on bullying, no study to
date has addressed the influence of playing computer games on this type of child/adolescent
aggression. Given a recent study that the average American child aged 2-17 plays seven hours of video
games per week (Gentile & Walsh, 2002), the absence of research again represents a significant
omission. This research topic is especially salient in light of the recent attention given to a new game
by Rockstar Games (publishers of the Grand Theft Auto games) called “Bully,” released in October
2006, where players adopt the persona of a 15 year-old juvenile delinquent who terrorizes his victims
with a range of physically and psychologically abusive behaviors.
METHODOLOGICAL LIMITATIONS OF EXTANT RESEARCH ON BULLYING
Beyond the lack of attention to such potentially significant dimensions of bullying behavior as
the impact of video gaming, several methodological limitations can be identified in the research on
bullying. A primary consideration is confounding incidence with frequency by combining categories
of the response variable pertaining to the extent of bullying behaviors (Zimmerman, 2005). This is
problematic because bullying is a sustained behavior occurring over time; dichotomizing the
measurement of bullying removes the ability to assess frequency and thus introduces measurement
error. We argue that equating “sometime” bullies with those who enact sustained bullying behavior
tends to convolute results and contradicts most operational definitions of bullying as sustained,
repeated behavior that occurs over time.
A second limitation is related to the operationalization of independent variables in studies of
bullying behavior. Above we discussed how varying definitions of self-esteem and self-efficacy have
Multiple Contexts of Adolescent Bullying
11
resulted in different conclusions. Another example is Zimmerman et al.’s (2005) measure of parental
emotional support, which included items related to eating meals, talking to the child while working and
spanking. Eating meals and spanking may be inadequate measures of this concept, however. Spanking
a child is a measure of physical maltreatment and not an indicator of emotional support. Any possible
relationship to emotional support is indirect therefore rendering it a measure of unknown validity. In
addition, Zimmerman relied on mothers’ reports of bullying behaviors in their children. This
introduction of measurement error was compounded by the fact that the definition of “bullying” as it
appears in the social science literature was not revealed to the mothers.
A third limitation pertains to the opportunity for intervening variables to influence the
relationship between media and bullying in extant studies. In the oft-cited Zimmerman study on the
relationship between bullying and television watching, there are too many potentially confounding
influences to adequately support a direct relationship between the two. For example, in addition to
gender, race, age and parents’ income and educational levels, which were controlled, other factors must
be accounted for in order to assess the ceteris paribus effect of television watching on bullying.
Previous research suggests that level of parental involvement, weapon carrying, self-esteem and
helplessness, and teacher and student support are all factors that are related to each other, affect
bullying and at a minimum should be included in the analysis. Therefore, we believe that evaluating
concurrent television watching and video game playing while holding these other factors constant is a
better means of assessing the direct relationship between media influences and bullying.
A fourth and final limitation pertains to focusing on the characteristics influencing bullying
behavior in isolation, in univariate analyses, based on the relationship of single independent variables,
taken one at a time, in relation to bullying behaviors. Such an approach has critical limitations given
the complex and broad array of factors associated with bullying behavior, including gender, SES,
Multiple Contexts of Adolescent Bullying
12
parenting behaviors, and individual characteristics such as academic performance. Previous research
clearly points to the need for multivariate, multi- contextual analyses such as the current investigation
(Veenstra et al., 2005; Haynie et al., 2001).
The present research addresses past methodological limitations and, therefore, provides more
reliable findings on early adolescent bullying, in the following ways. First, since parametric and
categorical models are not optimal for ordinal level data, this research models the frequency of bullying
behavior using ordinal logistic regression to assess how the predictor variables affect frequency. In this
way, the contributions of these predictor variables to bullying behavior can be assessed while
preserving the variation in the data and remaining “faithful” to the original question as it was asked to
survey respondents. Second, proportional odds models have been used extensively to model ordinal
outcomes. A crucial assumption of this technique is that the effect of the independent variables on each
odds ratio is the same (i.e. for this research an example is that the effect of any mediating factor on the
odds of never bullying versus “bullying” once or twice is the same as the effect on the odds of
“bullying” once a week versus being a chronic and frequent bully), which is clearly restrictive (Long,
1997). In fact, the proportional odds assumption did not hold empirically with these data. This tends to
cast doubt on previous research that models this same data to study the correlates of bullying using the
proportional odds model (i.e. Nansel, et al., 2001) without making appropriate statistical adjustments.
Additionally, we used the students' own perceptions of cognitive stimulation and emotional support
which may be more directly related to bullying. And, while the Zimmerman et al. (2005) paper is
innovative and informative, we believe that the measures we used in the current study represent an
improvement over the measures of cognitive stimulation and emotional support used in their study
because we measured students’ perceptions of cognitive stimulation in their immediate environments
(e.g. school and home). Finally, by measuring the concurrent effects of media influences on the
Multiple Contexts of Adolescent Bullying
13
propensity of adolescents to bully others, the potential for intervening variables to affect the
relationship between exposure and outcome is reduced.
RESEARCH QUESTIONS AND HYPOTHESES
We seek to understand adolescent bullying behavior and how the confluence of individual
characteristics and multiple contexts are related to bullying. Ecological theory is designed particularly
to model the relationships among individual characteristics and multiple contexts (Bronfenbrenner &
Morris, 1998; Espelage, et al., 2003; Swearer & Espelage, 2004), and serves as the underlying
conceptual foundation for this study. Prior research provides guidance regarding the specific individual
characteristics and contexts that act either as risk factors or mitigating factors for bullying.
Specific research questions arising from the ecological framework include:
1)
What individual characteristics and psychological states are most associated with
bullying behavior?
2)
At the microsystem level, what types of teacher behaviors, peer group interactions and
family relationships are most associated with bullying behavior?
3)
At the mesosystem level, to what extent does the influence of two or more
microsystem contexts (e.g. families and schools) reduce or enhance the likelihood of
bullying?
4)
At the exosystem level, do contexts that only indirectly include the bully (e.g. school
climate) influence bullying?
5)
At the macrosystem level, is there a relationship between concurrent media influences
(e.g. television watching and computer game playing) and bullying?
Multiple Contexts of Adolescent Bullying
14
Prior research on bullying behavior suggests a parabolic relationship between bullying and age.
We therefore hypothesized that the relationship between age and bullying among 11-14 year
olds would reflect this pattern, with the overall amount of bullying increasing over time. Given the
research support for differential gender prevalence for bullying, we hypothesized that males would be
more likely to bully than females. In light of both the sparse and inconclusive findings on the
relationship between bullying and race or ethnicity, we had no specific expectation for the direction of
our findings. Previous research on the psychological correlates of bullying, such as feeling selfconfident or helpless, is unclear as well. Therefore, we did not have specific directional expectations
for our findings in this regard either.
Prior research suggests that bullies tend to lack social support systems both at home and at
school. It was anticipated that individuals who have positive emotional support from parents and/or
peers will be less likely to bully. Given that previous research shows that the parents of bullies are
uninvolved in their children's lives (Olweus, 1993), we expected that parental involvement in school
and bullying would be inversely related. Peer-group relationships and friendships can influence and
shape both positive relationship patterns and, as well, adolescent aggression in bullying and fighting
behaviors (Espelage et al., 2003). From a purely quantitative perspective, the directional relationship
between number of friendships and bullying remains unclear, and would appear to depend on the type
and quality of peer influence. On the one hand, an individual with more friends may be more sociable
and therefore less likely to bully. However, peer relationships may sanction undesirable behaviors
(Nansel et al., 2001), and hence bullying may increase as peer support for those behaviors increases.
We expected that self-identified bullies who have extensive peer connections are likely to be affiliated
with peer groups that sanction or endorse fighting or bullying behaviors. Moreover, we hypothesized
Multiple Contexts of Adolescent Bullying
15
that apathetic teachers, for example those who show little interest in students as people or treat them
unfairly, create a classroom climate that would be conducive to bullying.
Prior work has found that the propensity to bully others may be related to an individual's
inability to cope with school-related stressors (Natvig et al., 2001). Consequently, we anticipated that
individual's who perceive that their parents and teachers have unreasonable expectations of their school
performance would be more likely to bully. Moreover, we expected that children whose parents support
their school activities, for example by encouraging them to do well at school or by manifesting a
willingness to resolve any problems that they may have at school, would be less likely to engage in
bullying.
We hypothesized that the general school atmosphere, as measured by students’ perceptions that
their school is welcoming, pleasant and a place where they “belong,” would be negatively related to
bullying. The broad framework for peer relationships, for example, student perceptions of whether they
enjoy being together, whether they feel accepted, or whether the atmosphere is one of students
expressing concern and help, would be related to bullying. We anticipated, then, that students who feel
positively supported in such a context are less likely to engage in bullying. Finally, given the larger
cultural context that reifies violence in television and video games, we presupposed that excessive
media usage is related to an increased prevalence in bullying. Since there is evidence that bullying may
be a more frequent problem in urban schools, we hypothesized as well that individuals in urban settings
may be more prone to bullying behaviors than individuals in smaller communities.
DATA AND METHODS
Participants
Data were drawn from the 1997 – 1998 World Health Organization’s Health Behavior in
School-Aged Children Survey (HBSCS). The HBSCS is a nationally representative school-based study
Multiple Contexts of Adolescent Bullying
16
intended to (1) monitor health-risk behaviors and attitudes in youth over time to provide background
data and to identify targets for health promotion initiatives, and (2) provide researchers with relevant
information in order to understand and explain the development of health attitudes and behaviors
through early adolescence. Although these data were collected in 1997-1998, they have nonetheless
been recently utilized in important research on bullying (e.g. Nansel et al., 2001). In addition, the
HBSCS has several advantages. First, it is a representative sample of 15,686 students in grades 6
through 10 in public and private schools in the United States. We focused on the 9,816 students aged
11 – 14. Our sample of 9,816 11-14 year olds included 5,142 non-Hispanic whites (52.3%), 1,575 nonHispanic blacks (16%), 2470 Hispanic/Latinos (25.2%), 488 non-Hispanic Asians (5%) and 141 nonHispanic Native Americans (1.5%). Our final regression analysis included 7,946 cases such that 81%
of the cases were retained. Since the survey is nationally representative, our conclusions are
generalizable to the population of American children aged 11 – 14. In addition, the large sample size
has positive implications for power assessments in statistical analyses. This is a marked improvement
over other studies that are based on less representative surveys and/or samples using small sample
sizes.
Statistical analyses were carried out using STATA, Version 9.0 (StataCorp, College Station,
TX). Partial proportional ordinal logistic regression equations1 were used to model the effects of these
1 When proportionality is unrealistic, the partial proportional ordinal logistic model appropriately allows for the
possibility that some of the estimated coefficients are the same for all values of j while others are not. As Lall et
al. (2002) contend, “strikingly” different results can be obtained when using alternative ordinal models. An
additional benefit is that this model is much more parsimonious than other models frequently employed when the
proportional odds assumption is deemed invalid. Accordingly, the following was fit to the data
 Pr(Y  y j | X 1 ... X p
log 
 Pr(Y > y j | X 1 ... X p


)
 = α j + [β1 X 1 + γ j1T1 ] + [β 2 X 2 + γ j2 T2 ] + [β q X q + γ jq Tq ] + ...[β p X p ] , j = 1,2,... , M  1
) 
where X 1 ,X 2 ,. .. ,X p are the set of covariates, q of which are known to have proportional odds and p – q do not.
In the parameterization of the partial proportional odds model used in this paper, each X has a constant
component associated with it (see Table 4). In addition, each X can have M – 2 gamma coefficients (entitled
Multiple Contexts of Adolescent Bullying
17
variables on the propensity to bully while accounting for 2-stage cluster sampling survey design effects
and covariates related to both the frequency of bullying and other independent variables described
above.
Outcome Measure
The outcome variable was designed to measure the self-reported frequency of bullying
behaviors among respondents in the sample. As distinguished from aggression, bullying is understood
in the context of a power differential relationship between a dominant child and a weaker child
characterized as ongoing and repeated. The following definition (Olweus, 1993) was introduced to our
final sample of 7,946 students aged 11 – 14. The definition clearly emphasized the repeated and
ongoing nature of the bullying relationship and distinguished bullying from aggressiveness perpetrated
on a victim who cannot readily defend him- or herself:
“We say a student is being BULLIED when another student, or a group of students, say or do
nasty and unpleasant things to him or her. It is also bullying when a student is teased repeatedly
in a way he or she doesn’t like. But it is NOT BULLYING when two students of about the same
strength quarrel of fight. How often have you taken part in bullying other students in school this
term? (italics added)”
Although bullying is conceptually different from aggression, there is a strong relationship
between aggressiveness, as operationalized by number of fights the child has fought, and bullying
2
among these school-aged children (χ16
= 765.12, p = 0.00).
Responses were coded 1 if the student had not engaged in bullying behavior (no bullying), 2 if
the behavior occurred “infrequently” (i.e., once or twice), 3 if the behavior occurred “sometimes” (i.e.,
more than once or twice but not weekly), 4 if the bullying was chronic but not frequent (i.e., occurred
on a weekly basis), and 5 if the bullying was both chronic and frequent (i.e., several times per week). In
“Increment at cut-off points” in Table 4) where M = 5 (the number of categories in Y) (See Lall, 2002 for further
explanation). The gamma coefficients represent deviations from the proportionality assumption, in other words if
the gammas for a variable are all 0 then the variable meets the proportional odds assumption (Williams, 2005).
Multiple Contexts of Adolescent Bullying
18
the context of the literature that defines bullying in terms of systematic and repeated behavior (Limber,
2004; Olweus et al., 1999), we define bullying behavior to be chronic and frequent (i.e., bullies can be
placed into the last category given above). However, we report results for non-bullying (category 1)
versus bullying behavior (category 5) with the understanding that if the proportional odds assumption
was not violated for that variable then the odds are the same for each contrast (i.e. category 1 versus 5
is the same as category 1 versus 2, 3 or 4). In reporting our results, the term “bullying” refers to
chronic and frequent aggressive behavior fitting into category 5. Table 1 reports the frequency
distribution of each category.
Main Predictors and Covariates
Explanatory variables used in this study have been associated with bullying or other aggressive
behavior in previous literature and inclusion was based solely on existing theoretical and empirical
studies. The variables may be grouped into categories representing the microsystem, mesosystem,
exosystem and macrosystem (Table 2). Composite measures of our subscales were derived via
exploratory factor analytic techniques and items that did not load above 0.30 were excluded from
further analysis with one exception (Table 3) (See also Table 2). Despite the fact that “Easy to talk to
mother” did not load above .30, it was included in the analysis for theoretical reasons.
[Table 2 here]
[Table 3 here]
Individual-Level Variables
Individual characteristics. We included as individual characteristics self-reports of age, gender,
and ethnicity. Dummy variables were included to estimate the differential effect of being female
(female = 1) versus being male (male = 0). In addition, dummy variables coded the effect of being
Multiple Contexts of Adolescent Bullying
19
African American (African American = 1), Asian (Asian = 1), American Indian (American Indian = 1),
or Pacific Islander (Pacific Islander = 1) versus being White (White = 0). Age is a continuous variable
ranging from 11 to 14.
Self-confidence, helplessness and feelings of being left out. The individual characteristics of
feeling 1) left out; 2) helpless; and 3) self-confident were included as well. Students were asked: “How
often do you feel:” (a) “left out of things,” (b) “helpless,” or (c) “confident in yourself.” Response
choices included 1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = always.
Additional individual-level variables were parental education, parental income, the presence of
both parents in the household, whether the individual was him- or herself a victim of bullying in the
past and whether the individual had previously carried a weapon to school.
Microsystem Variables
Emotional support from parents and friends. Separate scales of parent (Cronbach’s alpha = .54)
and friend (Cronbach’s alpha = .60) emotional support were created due to the poor reliability of the
combined measures. Students were asked to report the level of ease/difficulty they have talking with
their parents or friends. Responses included 1 = very easy, 2 = easy, 3 = difficult, 4 = very difficult, 5 =
impossible. Possible values for each scale ranged from 2 to 10, with 2 meaning strong social support
and 10 meaning a complete lack of social support.
The role of friends. It is assumed that the number of friends that students have proxies the
amount of social support they have and therefore “number of friends” was added to the model.
Teacher apathy. Teacher apathy includes measures designed to assess the level to which
students feel (1) prohibited to express their views in the classroom, (2) the teacher shows little interest
in them, (3) they are treated unfairly, and (4) the teacher is unwilling to provide extra help when it is
Multiple Contexts of Adolescent Bullying
20
needed. Possible responses included 1 = strongly agree, 2 = agree, 3 = neither agree nor disagree, 4 =
disagree, and 5 = strongly disagree. Total scores ranged from 4 through 20 (Cronbach’s alpha = .78).
Higher scores indicate increasing levels of teacher apathy.
Mesosystem Variables
Parental support at school. A parental support scale was constructed based on the degree to
which the respondent agreed that their parent(s) were (a) ready to help with problems at school, (b)
willing to come to school to talk to teachers, and (c) encouraged them to do well in school. Responses
ranged from 1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = always. Total scores ranged from 3
to 15 (Cronbach’s alpha = .82); higher values indicate increasing levels of parental support.
School-related stressors. Our analysis considered two measures designed to assess the level of
stress students feel from unreasonable expectations of their school performance. In two separate
questions, respondents were asked whether they agreed that their teachers and parents expect too much
from them in school. Responses ranged from 1 = strongly agree, 2 = agree, 3 = neither agree nor
disagree, 4 = disagree, and 5 = strongly disagree. These separate scores were summed to create an
index whose values ranged from 2 through 10 (Cronbach’s alpha = .73); higher values indicate
increasingly reasonable expectations.
Exosystem Variables
School atmosphere. We created scale items to represent aspects of school climate. Respondents
were asked to indicate the extent to which they agree that (a) the rules in school are fair, (b) the school
they attend is a nice place, and (c) they belong in school. Possible responses ranged from 1 = strongly
agree, 2 = agree, 3 = neither agree nor disagree, 4 = disagree, and 5 = strongly disagree. Possible
values range from 3 through 15 (Cronbach’s alpha = .76). Larger values are indicative of a negative
Multiple Contexts of Adolescent Bullying
21
school climate and thus students who score highly on this measure are more likely to be associated with
bullying.
Broader peer group relationships. We included a scale designed to measure the extent to which
respondents believe that (a) students enjoy being together; (b) other students are kind and helpful; and
(c) they are accepted by other students. Possible responses included 1 = never, 2 = rarely, 3 =
sometimes, 4 = often, and 5 = always. Scale values ranged from 3 through 15 (Cronbach’s alpha = .73).
Higher values indicate increasing levels of peer support and acceptance.
Macrosystem Variables
Media effects. Media effects are proxied by two variables: hours of television and hours spent
playing computer games. Respondents were asked to report the number of hours spent per week
playing computer games. Possible responses ranged from “not at all” through “10 or more.” They were
also asked the number of hours spent per day watching television. Responses ranged from “not at all”
through “more than 4 hours.”
Urbanicity. Because bullying has been shown to be more of a problem in urban schools
(Fleming et al., 2002), we controlled for urban residence by including, in our model, a dummy variable
equal to unity if the respondent lived in a big city.
RESULTS
The beta coefficients (log-odd ratios) and associated p-values resulting from the estimated
partial proportional ordinal logistic regression model are presented in Table 4. For purposes of brevity,
we only show the results for the “Bully” (i.e. category “5” of our dependent variable, n = 385) versus
the “Not a bully” (n = 4529) contrast when the proportional odds assumption was violated. The omitted
comparisons include 1 (not a bully) vs. 2, 1 vs. 3 and 1 vs. 4. A dash (-) in the table means that the
Multiple Contexts of Adolescent Bullying
22
assumption is satisfied and the beta coefficient can be interpreted as applying to all levels of the
dependent variable. The first two columns present the results from the proportional odds model. This
model assumes that each independent variable has the same influence on the odds of moving from
category 1 (no bullying) to category 2 (once or twice) as that factor does on the odds of moving from
category 2 to category 3 (sometimes), etc. The second two columns present the adjustment to these
odds ratios when the assumption of proportional odds is violated. The test statistics corresponding to
the beta coefficients shown in the second two columns of table 4 indicate that significant deviations
from the proportional odds model exist. The overall effect of each independent variable on the odds of
being a chronic and frequent bully is determined from the combination of beta coefficients in column 1
and adjustments in column 3.
Table 5 presents the results of the logistic regression in terms of odds-ratios; i.e. it transforms
the beta coefficients and proportional odds adjustments presented in Table 4 into a more
understandable form. An odds ratio (OR) represents the effect of an independent variable on the
likelihood (or odds) of being a bully (n = 468) relative to the likelihood (or odds) of not being a bully
(n = 4529) In addition, when substantive changes are of interest, we report standard deviation changes
and/or changes in predicted probabilities.
[Table 4 here]
[Table 5 here]
Individual Characteristics of Bullies
The first entry in Table 5 shows that the odds of being a bully are 0.80 times as high for females
as for males, i.e. females are 20% less likely to be bullies although this result is not significant at
conventional levels (Z = -1.89, p = .059). The odds of bullying increase significantly with age. Being a
year older increases the odds of bullying by 6%, holding other variables constant (Z = 2.24, p = .025).
Multiple Contexts of Adolescent Bullying
23
The odds of bullying are increased by 24% when age is allowed to vary over its range (i.e., from its
minimum value of 11 to its maximum value of 14). African American (Z = 4.21, p = .000) and Asian (Z
= -3.46, p = .001) adolescents are significantly less likely to engage in bullying behaviors than White
adolescents. The odds of bullying among African Americans and Asians are 25% and 30% less than
they are for Whites, respectively. None of the other race/ethnicity variables were statistically
significant. Our results further indicate that as parental income increases so does bullying (Z = 3.27, p
= 0.001). The variables measuring mother and father education and living with both parents, however,
were statistically insignificant.
With respect to the psychological correlates of bullying, we found a significant and negative
relationship between feeling “left out” and the frequency of bullying behaviors among school aged
children (Z = -4.53, p = 0.00). Additionally, although not statistically significant, we found that the
more students feel “helpless,” the more likely they will bully (Z = 1.69, p = .092). Lacking selfconfidence was not statistically significant and hence we are unable to conclude that it is a risk factor
for bullying.
Individuals who were previously bullied at school are significantly more likely, in turn, to be
bullies. The odds of bullying are 34% greater among individuals who reported being bullied at school
during the current school term (Z = 12.82, p = 0.000). Finally, the odds of bullying are 46% higher
among students who reported carrying a weapon to school (Z = 8.50, p = 0.00).
Microsystem Factors
Emotional support from parents and friends. Our measure of parental emotional support was
statistically significant and positively related to bullying (Z = 4.88, p = 0.000). Students who have
greater difficulty discussing their problems with parents are more likely to engage in bullying
behaviors. For example, the odds of bullying are 7% higher among individuals who lack emotional
Multiple Contexts of Adolescent Bullying
24
support from their parents. Additionally, our measure of friend emotional isolation strongly predicted
bullying. Students who are less isolated from their friends are more likely to engage in bullying
(Z = -6.56, p = 0.000).
Peer group contextual effects. The role of one’s peers in facilitating bullying behaviors extends
as well to the number of friends one has: each additional friend increases the odds of bullying by 12%
(Z = 5.43, p = 0.000).
Teacher apathy. Teachers who are supportive, take an active interest in students, and treat them
fairly, create an environment where bullying is less likely. For example, a two standard deviation
decrease in our measure of teacher apathy decreases the odds of bullying by almost 24% (Z = 4.39, p =
0.000).
Mesosystem Factors
Parental support at school. Our measure of parental support at school was statistically
insignificant; therefore we cannot conclude that inadequate parental involvement in school is a risk
factor for bullying.
School-related stressors. Overly permissive parental and teacher relationships with students are
likely to foster an environment where bullying results. More specifically, the odds of bullying increase
by almost 5% among students whose parents and teachers hold low expectations of their school
performance (Z = 1.97, p = 0.048), contrary to our prediction.
Exosystem Factors
School atmosphere. Our measure of school climate was statistically significant as well. Each
standard deviation increase in our measure of school atmosphere increases the odds of being a bully by
44% (Z = 3.38, p = 0.001). Recall from above that our measure of school atmosphere consisted of
respondents’ perception that the rules in school are fair, the school they attend is a nice place, and that
Multiple Contexts of Adolescent Bullying
25
they belong in school. Our results therefore indicate that transitioning from a students’ perception of a
pleasant school atmosphere characterized as fair, welcoming and pleasant to one characterized as
unpleasant, unfair and unwelcoming increases the predicted probability of being a bully by 6%, holding
other variables constant. Our measure of broader peer group relationships, however, was not
statistically significant.
Macrosystem Factors
The community as context for bullying: The role of media exposure. While our results indicate
that urbanicity is not related to bullying, our measure of television watching has a very large and
statistically significant effect on the probability of being a bully (Z = 7.84, p = 0.000). Each standard
deviation increase in hours of television watched per day increases the odds of being a bully by 21%,
holding other variables constant. The coefficient on our variable corresponding to hours of computer
game playing per week was statistically insignificant. For comparison purposes, each standard
deviation increase in hours of computer game playing per week increased the odds of bullying by only
1.5%.
In Figure 2, we let the number of television hours per week vary and plotted the effect of
television watching on the probability of bullying while the other variables were held constant at their
means. At zero hours per day of television viewing the probability of being a bully is approximately
1.5%; as television viewing hours increase the probability of bullying nearly doubles to 2.8% for an
adolescent who watches four hours of television per day (just under the sample average of 4.1 hours).
Moving to the sample maximum of six hours per day, the probability of bullying nearly doubles again,
to exceed 5%.
[Figure 2 here]
The Set of Patterned Interrelationships Among Subsystems: Interaction Effects
Multiple Contexts of Adolescent Bullying
26
In keeping with an ecological approach, we were interested in the multiple contextual effects of
our variables and their interactions. To investigate these effects, we defined combinations of
4
characteristics corresponding to ideal types in the population based on 2 = 16 combinations of
characteristics. These characteristics included the self-identified bully’s gender and racial group as well
as his or her status as living with both parents or in a big city. In Table 6, we symbolize each of the
possible combinations with IRijkl where i = 1 if the individual is male, j = 1 if the individual lives with
both parents, k = 1 if the individual is black and l = 1 if the individual lives in a big city. Next, we
allowed the amount of television watching to vary over its range. We then predicted the probability of
bullying for several combinations of variables. The effect of parental, teacher and emotional support,
self-confidence, and school atmosphere on the probability of bullying at maximum and minimum
values of television watching for each combination of the above characteristics are presented in Table
6.
[Table 6 here]
Table 6 shows that despite constancy across combinations of variables, the effect of television
watching on bullying varies within levels of the predictor variables. Disregarding for the moment
perceptions of school environment, level of self-confidence, hours of television watched per day, and
the level of parental, teacher and emotional support, males consistently exhibit a higher probability of
bullying than do females. Similarly, when examining the interaction between race and gender, it
becomes clear that White males are more likely to be bullies than are Black males or females of any
race, again disregarding other factors.
Clearly, television watching affects the likelihood of being a bully: the predicted probability of
bullying is higher among individuals who watch several hours of television per day (i.e., television
watching is high) and this holds across all categories and irrespective of socio-demographic
Multiple Contexts of Adolescent Bullying
27
characteristics. Conversely, children who claim to watch television infrequently (i.e., television
watching is low) are less likely to self-report being a bully conditional on being school-integrated (i.e.,
school atmosphere is high) and possessing high levels of parental and teacher emotional support (i.e.,
parental and teacher emotional support is high). In addition, children who watch several hours of
television per day but who have higher levels of teacher support are less likely to bully others
irrespective of race, gender, place of residence and parental presence in the home. For students who
watch television frequently, school atmosphere is the most important mediator of bullying behavior.
When negative school atmosphere is at its max within high levels of television, the probability of
bullying is higher than it is across any other category. In fact, the probability of bullying is highest for
White males living with both parents in an urban area who frequently watch television and attend
schools with adverse climates (IR1101 = .124).
Overall, the effect of television watching on the odds of being a bully is the largest for males
living in urban areas who live with both parents (IR11.1 ) , who attend schools with adverse
environments, and report having very little teacher support. For example, if a child who watches
television frequently does not have support from his teachers, the probability he will bully increases
from 5.1% to 8.0% for Blacks and from 5.3% to 8.2% for Whites who live in big cities with both
parents present. Poor school environments similarly increase the probability of bullying from 3.3% to
12.0% for Blacks and 3.4% to 12.4% for Whites. Black females who feel supported by their teachers
and who attend schools with positive environments have the lowest probability of bullying. For
example, the predicted probability that a Black female living in single parent home in a rural area will
bully is 0.9%. Interestingly, having low levels of self-confidence increases the likelihood of bullying
when television is at its maximum but decreases the probability of bullying when television is at its
minimum.
Multiple Contexts of Adolescent Bullying
28
DISCUSSION
Our interpretation of the results followed naturally from an ecological perspective to
understanding the nature of bullying behavior. This perspective moves from the microsystem to the
mesosystem, exosystem and then to the macrosystem, emphasizing the set of patterned interactions that
occur between them. At each contextual level, we found statistically significant effects, suggesting that
our conceptual understanding of bullying behavior is advanced by using an ecological model as the
theoretical lens in which we come to terms with this type of childhood aggression. In what follows, we
summarize our main findings, note similarities and differences between the current research and
previous studies, and offer our interpretation of the results.
Based on the pattern of responses, our unadjusted estimate is that approximately 4.9% of
adolescents aged 11-14 are chronic and frequent bullies. Our adjusted estimate suggests that, on
average, 3% of students aged 11-14 are chronic and frequent bullies. These are considerably low
estimates in relation to Nansel et al.’s (2001) finding of a 19.3% prevalence; however, this is likely the
result of methodological differences in the operationalization of “bullying.” Rather than including
acute or infrequent acts, the present estimate relied on defining bullying as a frequent behavior that
occurs several times per week. While measuring bullying as a dichotomous, or yes/no, variable
produces a prevalence estimate of 42.6%, excluding only those who never or rarely bullied from the
estimate yields a prevalence of 16.8%. Thus, our analyses suggest that researchers failing to account for
frequency in their operationalization of bullying are likely to report a 3-8 fold overestimation
(Zimmerman, 2005).
Apart from methodological differences, our study differs from the Nansel et al. (2001) study in
additional ways. We included measures of parental and friend emotional support, number of friends the
bully has, media usage and measures of perceived teacher support. In addition, we focused on a smaller
Multiple Contexts of Adolescent Bullying
29
subset of adolescents, namely those between the ages of 11 and 14. Finally, using the same data set, we
found a violation in the proportional odds model technique that provided the basis for their estimation.
Therefore, we turned to statistical methods designed to account for this violation in the data.
At the level of risk factors associated with the individual, our findings are consistent with other
studies reporting that bullying is more common among boys than girls (Natvig et al., 2001; Olweus,
1997). Anderson et al., (2001) reported that perpetrators of violence were more than twice as likely to
report being bullied and on this basis concluded that bullying may be related to other types of school
violence. We provide further evidence that victims of bullying are more likely to bully others (Haynie
et al., 2001). Anecdotal evidence suggesting that race and/or ethnicity are not risk factors for bullying
behaviors are contradicted by our results. The coefficients pertaining to two race variables in our model
were significant and therefore we conclude that race can be added to the growing list of risk factors for
bullying. In particular, Whites have a higher probability of being (chronic and frequent) bullies than do
either Asians or African Americans.
Prior research has been unclear as to the effect of low levels of self-esteem on the proclivity to
engage in bullying. For example, in their study of Irish school children, O'Moore and Hillery (1989)
found that bullies tend to have lower levels of self-esteem (see also, Duncan, 1999, Rigby & Slee,
1991, Tritt & Duncan, 1997). Others have suggested that greater amounts of self esteem increase
bullying (Natvig et al., 2001, Olweus 1997, Slee & Rigby, 1993). We did not have a specific measure
of self-esteem, using instead a measure of self-confidence. Therefore, we cannot settle this ongoing
debate either way. On the other hand, we found that, controlling for other factors, feeling helpless
increases bullying behaviors. In this respect, our results are consistent with prior research finding that
bullies feel more helpless than non-bullies (Duncan, 1999). It is possible that students who feel helpless
Multiple Contexts of Adolescent Bullying
30
engage in bullying as a means of empowering themselves. Feeling helpless may also arise from having
inadequate social support systems.
In accord with Zimmerman et al.’s (2005) findings in children, our results suggest that bullying
may arise out of deficits in social support among adolescents. We found that involvement in bullying
is related both to interactions with parents, teachers and friends and to the type of support provided by
each. Students with parental emotional support are less likely to be bullies. It seems intuitively
plausible that students who feel strong emotional support from their parents will turn to discussion as a
means of tempering any aggressive tendencies that might otherwise result in bullying. It is also likely
that adolescents turn to their parents to discuss problems, issues and concerns, thereby increasing the
salience of having parental emotional support.
Our results indicate that emotional alienation from friends decreases bullying. At first glance,
this appears to be a counterintuitive finding. Previous research has suggested, however, that bullies
tend to associate with other students who engage in bullying behavior, such that peer groups of bullies
induce individual group members to engage in even more bullying (Espelage et al., 2003).
Unfortunately, we were unable to assess the characteristics of the bully’s friends. However, this view
that bullying is supported by association with other bullies is corroborated by two additional findings.
First, we found that the probability of bullying increases with number of friends. Second, our results
show that students who feel included in school activities (i.e., do not feel left out) are more likely to
bully (this could also be because students who are more involved in school activities have more
opportunity to bully). Clearly, bullying does not exist in a vacuum but is influenced by the broader
environment, in which friendships play an important role.
Perceived social support from teachers was associated with lower probabilities of bullying. Our
results suggest that the frequency of bullying depends on the extent to which teachers 1) take an active
Multiple Contexts of Adolescent Bullying
31
role in promoting student welfare, 2) are interested in helping students in need, 3) allow for the
possibility of alternative forms of self-expression, 4) promote cooperation, and 5) create an equitable
school environment. Furthermore, these results illustrate the critical relationship of the school context
to the likelihood of bullying behavior, directly through supportive teacher behavior and indirectly in
structuring the classroom setting.
The results of the current study also provide support for previous findings that students’
perceptions of different aspects of the school environment are risk factors for bullying (Natvig et al.,
2001). While Natvig et al. (2001) focused on the nature of school work as a measure of school stress,
we considered an alternative aspect of the school atmosphere: the degree to which students experience
a pleasant, welcoming and fair school environment. Quite possibly, it may be that different aspects of
the school environment, as perceived by the student, are observed as effects rather than causes of
bullying (Natvig et al., 2001). The strength of our measure is that we included the students’ own
perceptions, namely whether they believe their parents and/or teachers expect too much from them at
school. School-related stress in the form of unreasonable expectations placed on students by their
parents and teachers was found to decrease bullying behaviors, contrary to our prediction. This finding
is actually consistent with research implying that children who engage in bullying are more likely to
come from homes in which parents are extremely permissive (Olweus, 1993).
Given that preferred leisure activities of adolescents include playing computer games
(Cesarone, 1994) and watching television, it is surprising that only a handful of researchers have
studied their relationship to bullying. In any event, the ceritus paribus effect of television watching on
bullying frequency is of particular interest. Our analysis revealed evidence to support Zimmerman et
al.’s (2005) finding of a significant relationship between television watching and bullying. We
extended their results to show the separate and independent effects of television watching on
Multiple Contexts of Adolescent Bullying
32
subsequent bullying. We found that while the odds of bullying increase by 28.7% per standard
deviation change in hours spent watching television, the odds of bullying increase by only 1.5% per
standard deviation change in computer game playing. An explanation for this finding was offered by
Zimmerman et al. (2005) who noted that a high percentage of television programs contain explicit or
implicit violence which could serve as a model for children to engage in aggressive behaviors,
including bullying. The causal mechanism is believed to be that media violence causes aggressive
behaviors and/or cognitions, increased arousal, and an aggressive affective state that is internalized
during psychosocial development (Bushman & Anderson, 2002). While in our study we were unable to
differentiate between violent and non-violent television viewing and computer gaming, others have
reported that approximately 60% of television programs and 60%-90% of computer games contain
violent themes (National Television Violence Study, 1998). This is especially true for school-aged
children who are exposed to a much broader range of television programs than adults. Thus, our
measures of viewing and gaming hours are likely to provide reasonable measures of exposure to media
violence.
A student with low self confidence and who watches a lot of television is more likely to take
behavioral cues from television, which can be violent, leading to a greater chance of being a bully. A
student with low self confidence who does not watch television is more likely to take behavioral cues
from other, less violent sources (e.g. parents, teachers, etc.) and therefore less likely to bully.
Conversely, students who watch very little television and/or have higher levels of self confidence are
less likely to take behavioral cues from television and therefore less likely to bully. Overall, the
probabilities discussed here demonstrate the importance of interaction effects between the four sociodemographic characteristics when seeking to develop an understanding of bullying behavior, television
viewing hours and the mediating influence of social support systems. More importantly, many of the
Multiple Contexts of Adolescent Bullying
33
differences in predicted probabilities we presented illustrate the results found within the partial
proportional logistic regression. Specifically, children who lack a strong social base due to low levels
of teacher support or who attend schools that are unwelcoming and unfavorable have a higher
probability of engaging in bullying, but the bullying behavior is mediated by other influences, such as
the number of hours of television watching per day.
Our last macrosystem variable, urbanicity, was an attempt to measure the broader contextual
environment in which the school is located. More specifically, since there are many schools in any
particular geographic locale, all of which are presumed to suffer from the same kinds of social
problems that aggravate bullying (Ortega & Lera, 2000), we included a variable to measure the
differential effect of urbanization on bullying. Our variable was not significant so we were unable to
conclude that place of residence significantly affects the propensity to bully.
LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH
By conceptualizing bullying as multidimensional and by considering many variables at multiple
levels of analysis, the current study presents a clear advance on past research. Nevertheless, it is
important to acknowledge several limitations that exist in our study. First, as noted above, the nature of
the data poses some limitations. The data set is 10 years old and was not originally collected for the
purpose of studying the concomitants of bullying behavior. However, the age of the data set only
reinforces the need to collect more representative data on bullying behaviors of students in this age
range. Also, due to the cross sectional nature of the HBSCS data, we are unable to establish any causal
relationships and hence the time ordering between exposure and outcome is difficult to establish.
Therefore, our analysis rests primarily on theoretical considerations that violence is a learned response
to negative environmental stimuli such as media influences. Some researchers prefer instead to
emphasize a different directional relationship by noting that individuals with violent or aggressive
Multiple Contexts of Adolescent Bullying
34
tendencies are inclined to play video games and watch television (Kuntsche, 2004). Second, given the
rapid pace at which the content of both television and computer games changes, our results should be
interpreted with caution. As such, the lack of effect for game playing in this study might not apply to
the more violent games of today. Third, in the present study, the data on bullying are based on selfreport, which may have implications for our results. Self-reported bullying behavior is bound to be an
under-representation of its actual frequency given that social desirability effects are likely to exist in
the reporting of negative behavior. Different methodologies used to report bullying across studies have
resulted in conflicting findings. Observation of students’ behavior may be a more accurate way of
ascertaining bullying because a bully may be unconscious or unaware that he is engaging in this type of
behavior. Some researchers have argued, however, that teachers’ reports of bullying behavior may not
accurately reflect the extent of bullying that takes place in settings away from the classroom, such as on
the playground, where bullying occurs most frequently (Pellegrini & Bartini, 2000). Future research
should attempt to replicate our findings with data that measures bullying by peer report since selfreport probably underestimates the true amount of bullying in the population. Fourth, our findings
could be strengthened via the use of additional data that is more targeted and specific. For example,
understanding the precise mechanisms in which peer groups influence bullying would be more
informative than our current measure “number of friends.“ Also, self-confidence, helplessness and
feeling “left out” are in reality more complex and should be measured as multidimensional rather than
as single item constructs. In this regard, we were constrained by the data. Consequently, our knowledge
would greatly benefit from future studies that focus more specifically on the causal mechanisms of selfesteem and confidence, feelings of helplessness and peer group functioning such as popularity, group
status in the broader social network as well as levels and approval of aggressive behavior in the group.
CONCLUSION
Multiple Contexts of Adolescent Bullying
35
Bullying is a complex behavior with multiple causes and risk factors, ranging from individual
characteristics to school settings to broader social contexts. In our view, the ecological perspective
provides both a vehicle for better understanding the complex features of bullying and also for crafting
sensitive and effective interventions at multiple contextual levels. For example, teaching students to
“use their words” to resolve conflicts is unlikely to be successful if the school is perceived negatively
by students (who may then tend to ignore the school’s recommendation on conflict resolution) and/or if
the school condones or ignores bullying in other contexts such as during athletic programs.
Additionally, interventions at both the individual and school level may be insufficient if parents use
bullying and aggressive behavior at home or encourage children to solve problems physically. Finally,
broader societal attitudes towards violence—as exemplified by the violent content of television
shows—increase the likelihood of chronic and frequent bullying. Thus, interventions to reduce
bullying are most likely to succeed if they address contributors to bullying behavior at every level from
the individual to school and family to society.
Multiple Contexts of Adolescent Bullying
36
ACKNOWLEDGEMENTS
We would like to thank the United States Department of Justice -- Office for Juvenile Justice
and Delinquency Prevention and the Michigan Department of Human Services Grant #: 071B2001414
for funding this research.
Multiple Contexts of Adolescent Bullying
37
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