A Cognitive-Ecological Approach to Serving
Students With Emotional and Behavioral Disorders:
Application to Aggressive Behavior
Nancy G. Guerra
University of New Hampshire
Paul Boxer
University of New Orleans
Tia E. Kim
University of California at Riverside
ABSTRACT: In this article we present a cognitive-ecological model for understanding and preventing
emotional and behavioral difficulties and propose directions for school-based intervention programs,
particularly with aggressive children. In the cognitive-ecological framework, intervention efforts
should target certain cognitive skills (e.g., skills that encourage attention to multiple cues in a setting)
and knowledge structures (e.g., normative beliefs about appropriate responses to conflict) across
multiple contexts that change over time (e.g., classroom, peer, school, family). We also emphasize
the importance of coordination among contextual influences so that children learn consistent, crosscontext standards that encourage prosocial and socially competent behavior. Practitioners working
with students who exhibit emotional and behavioral difficulties should strive to integrate efforts at
modifying cognition as well as context in the service of promoting behavioral change that maintains
over time and across situations.
Recent advances in understanding the
learning, maintenance, prevention, and
treatment of problematic social behaviors in
childhood and adolescence have emphasized
the central role of the child’s developing
cognitions (Beck, 1999; Boxer & Dubow, 2002;
Compton et al., 2004; Crick & Dodge, 1994;
Durlak, Rubin, & Kahng, 2001; Eron, 1994;
Guerra & Huesmann, 2004; Huesmann, 1998;
Lochman & Lenhart, 1995). The developing
individual is seen as an active participant in
a learning process linking individual (e.g.,
irritability, impulsivity) and environmental
(e.g., community violence, poverty) risk factors
to social behavior through cognitive structures,
such as beliefs, rules, and schemas, and skills,
such as attention, attribution, and problem
solving. This cognitive-ecological view posits
that problem behaviors emerge through
interactions between individual predisposition
and contextual socialization and are
maintained over time and across situations by
cognitive “styles” that are shaped by direct and
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BehaviorDisorders_30(3).indd 85
observational learning experiences. Cognitive
styles are learned across multiple contexts
and, in turn, influence responding across
these contexts. The term “ecological” refers
to the nested contexts of child development,
providing a stage for social interactions,
opportunities for social engagement, and a
normative or regulatory structure that includes
costs and benefits of distinct courses of action
(Guerra & Huesmann).
Consider a boy who grows up in an
environment laced with harsh and hostile
encounters with parents, teachers, and peers.
Over time, it is likely that these negative
experiences will influence, at least to some
degree, his self-perception (“nobody likes me”),
perceptions of others (“they have it in for me”),
and beliefs about aggression (“it’s OK to hit and
be mean—everybody does it”). Under these
conditions, it is also likely that he will develop
characteristic biases in social information
processing that are based on the presumption
that others act with hostile intent, leading to
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increased perceptions of vulnerability and
anger, and a greater likelihood of aggressive
retaliation. For example, Dodge and colleagues
(Dodge, Pettit, & Bates, 1997; Dodge, Pettit,
Bates, & Valente, 1995) have shown that
children who experience harsh parental
discipline or are physically abused during
their early childhood years are more likely to
attribute hostile intent to peers in ambiguous
situations and behave more aggressively than
their nonexposed peers.
If cognitive patterns linked to emotional
reactions, such as anger, and behaviors, such
as aggression, are learned over time, then it
is also the case that they can be “unlearned.”
In essence, this is a fundamental premise of
cognitive-behavioral interventions; that is,
modifying dysfunctional cognition will, in
turn, lead to positive effects on emotional and
behavioral adjustment. However, because
the primary emphasis is on the individual’s
cognitive deficits and distortions and how
these can be modified, less attention has
focused on the contribution of the child’s total
developmental ecology to the emergence and
maintenance of targeted cognitions (Boxer &
Butkus, in press; Durlak et al., 2001).
Both clinical and psycho-educational
interventions typically are designed to change
how children think in response to problematic
social situations, with less attention focused
on modifying contextual influences on these
emerging cognitions. The assumption is that
once children correct errors in thinking or
reduce deficits in social information-processing
skills, they will be better equipped to navigate
their social and emotional worlds, resulting in
corresponding gains in adjustment. Although
cognitive-behavioral interventions also address
situational factors that have established or are
maintaining specific symptoms or behaviors
(e.g., functional analysis; Haynes & O’Brien,
1990), they focus primarily on immediate
situational
contingencies
rather
than
overarching developmental contexts. In some
sense, a focus on the individual as the target
of intervention ignores the continuous and
dynamic influence of the social environment
on the child’s emerging cognitions. Indeed,
one of the most robust findings in both the
prediction and intervention literature looking
at youth problem behaviors is the complex and
continuous interplay between the developing
child and the nested social contexts in which
development unfolds (Bronfenbrenner, 1979;
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BehaviorDisorders_30(3).indd 86
Guerra, Huesmann, Tolan, VanAcker, & Eron,
1995; Henggeler, Schoenwald, Bourduin,
Rowland, & Cunningham, 1998).
The purpose of this paper is to describe
how a cognitive-ecological model of children’s
social behavior builds on cognitive-behavioral
approaches to suggest effective avenues for
intervention. As described, the cognitiveecological model emphasizes the role of
cognitions that develop over time as individuals
navigate multiple social environments.1 We
propose that the effectiveness of cognitivebehavioral interventions for children with
emotional and behavior disorders should
be enhanced by simultaneously addressing
maladaptive
cognitions
and
relevant
situational and contextual influences on these
emerging cognitions. Because most of our
work has focused on school-based approaches
to the prevention and treatment of children’s
aggressive behavior, we illustrate the cognitiveecological approach as applied to the learning
and prevention of aggression in schools.
We begin by discussing specific patterns
of cognition and information processing
related to social behavior. Following this, we
examine specific teacher, peer, and school
influences on both cognition and aggression
that are potentially malleable via prevention
and intervention efforts. We highlight the need
to think about developmentally appropriate,
universal strategies for preventing the
emergence of distortions or deficits in cognitive
processing as well as strategies for intervening
with at-risk students. Finally, we discuss
how individual and contextual influences
on aggression and social behavior can be
integrated into school-based, multicomponent
prevention and intervention programs that
address complex needs of children over time
and across contexts.
The Cognitive Underpinnings
of Children’s Social Behavior
In the cognitive-ecological framework,
behavior is seen as a product of an array of
causal influences including individual factors
(e.g., temperament, arousal level, brain
structures), environmental socializers (e.g.,
family practices), and situational instigators
(e.g., stress). These predisposing factors are
believed to influence behavior, in part, via
their influence on cognitive processes and
structures that develop over time. For example,
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both high levels of impulsivity and high levels
of environmental violence can lead children to
short circuit their search for cues in threatening
situations, leading to a hostile attributional
bias that is more likely to trigger aggressive
responding (Dodge, Bates, & Pettit, 1990).
The cognitive-ecological framework builds
on a number of integrative social-cognitive
models of behavior (e.g., Anderson & Bushman,
2002; Crick & Dodge, 1994: Huesmann,
1998). What these models have in common
is an emphasis on both sequential processing
of social information (although this processing
can also occur in simultaneous parallel paths)
and an emphasis on latent mental structures
that guide information processing by reducing
the cognitive workload. A cognitive system
thus includes memory structures that link
cognitive concepts and emotions, knowledge
structures that represent interconnected
concepts, and an executive program that
manages the entire system linking inputs
to outputs (Huesmann). Over time, both
processing styles and mental structures
crystallize, resulting in characteristic patterns
of cognition and associated behaviors. Further,
as children develop more habitual styles of
responding in familiar situations, cognitive
processing becomes more automatic. In
this fashion, social-cognitive mechanisms
are seen as instrumental in the stability and
maintenance of behavior over time and across
situations. Which aspects of cognition and
their development represent the best bets for
intervention? We now turn to a brief review
of cognitive processes and structures that
have been studied in relation to children’s
social behavior.
In social situations, children are presented
with an array of internal and external cues;
in the interest of cognitive efficiency, they
learn over time to address certain cues and
ignore others. The salience of different cues
hinges on personal and situational factors.
An aggressive child is more likely to attend
to aggression-promoting cues (e.g., being
bumped-into by a peer) and less likely to
properly address prosocial cues (e.g., the
peer subsequently apologizing). Contextual
stimuli also can exert a priming effect, where
cues linked to these stimuli are processed
more readily. For instance, if kindness and
caring are repeatedly emphasized in the
classroom, children may be more sensitive
to facial cues that suggest someone’s feelings
are hurt.
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BehaviorDisorders_30(3).indd 87
The link between processing of social
cues and behavior also hinges on how cues
are interpreted or causally attributed. A major
emphasis of cognitive-behavioral therapy is
on understanding how meanings, attributions,
and explanations guide behavior, and how
related distortions can misguide behavior.
For example, social categories such as
gender or ethnicity can be used as guides for
interpretation or misinterpretation. A child
who believes that girls are nice and boys are
mean may attribute a “stare” from a girl as
an attempt at engagement while attributing the
same stare from a boy as a show of disrespect
or provocation. Perhaps the most robust finding
linking attributions to children’s behavior in
both clinical and population samples is that
aggressive children are more likely to attribute
hostile intent to others under ambiguous
circumstances (Dodge et al., 1990; Guerra
& Slaby, 1990; Orobio de Castro, Veerman,
Koops, Bosch, & Monshouwer, 2002).
In addition to encoding and interpretation
of cues, children must select from a range of
available responses, evaluate these responses,
and select a response for enactment. Although
responses such as aggression and withdrawal
seem to be part of an innate behavioral
repertoire, through socialization experiences
children develop more elaborate and
situation-specific guidelines for generating
responses and evaluating the outcome of
these responses. Over time, a child’s response
repertoire becomes more sophisticated
and more organized according to rules of
social interaction across contexts. Responses
are guided by cognitions including beliefs
about their appropriateness, beliefs about
consequences, beliefs about self-ability or
efficacy to enact them, and consistency with
self-schema. For instance, it is likely that a
child who believes that saying “please” is very
important will automatically respond in this
manner when making a request. Alternately, a
child who believes that “nice guys finish last”
will probably generate more aggressive than
passive responses in social situations.
In our own work we have been interested
in the role of normative beliefs for behavior,
defined as one’s perception about the
appropriateness of a particular behavior in
specific settings. In the case of aggressive
behavior, we have shown that these beliefs
emerge from observation of one’s own
behavior, observation of others’ behavior both
in vivo and through media representations,
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and indirect and direct instruction across
different contexts (Guerra et al., 1995). These
beliefs begin to stabilize around age seven or
eight, consistent with children’s engagement
in games with rules. As children get older,
normative beliefs become increasingly stable
and influence subsequent behavior in relevant
areas (Huesmann & Guerra, 1997).
Knowledge structures such as normative
beliefs can influence social information
processing by increasing the salience of
particular cues or specific responses. Further,
simple structures often are linked together
in a larger organizational framework that
suggests possible courses of action or “scripts”
for responding. Scripts are mental constructs
that direct behavior by organizing a person’s
understanding of a given situation, including a
likely sequence of action, preferred response,
and expected consequences. Scripts serve to
simplify the cognitive workload and increase
the automaticity of responding. As development
unfolds across familiar situations, children’s
characteristic responses become increasingly
guided by associated scripts. For instance,
prosocial children presumably have more
dominant prosocial scripts, and aggressive
children are more likely to access regularly
more aggressive scripts.
The cognitive-ecological model emphasizes the role of contextual influences on the
learning, encoding, and utilization of scripts
for social interaction and behavior. Contexts
provide rich opportunities to observe patterns
of social interaction, frequency of different
types of behavior, likely consequences of
different courses of action, as well as to
experiment with different behaviors in different
situations. For example, a child who grows up
in a violent home is likely to encode patterns
of interaction under conditions of social
conflict that include yelling, screaming, and
other types of aggressive behaviors. Cues for
conflict thus might trigger similar aggressive
interaction patterns.
Contextual influences impact cognition and
behavior through several mechanisms. These
include observational learning, reinforcement,
and normative standards. Observational
learning involves both imitation and active
information
processing—children
must
frequently make sense of diverse observations
that do not provide a consistent guide for
action. Further, what is observed in different
contexts also may vary. Similarly, contexts
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BehaviorDisorders_30(3).indd 88
vary in the extent to which they provide
reinforcements for specific behaviors. Among
some youth, aggression may be highly regarded
in the neighborhood and peer contexts,
whereas this behavior often is discouraged
and punished in family and school contexts.
Contexts also provide information about
normative standards of acceptable behavior.
For instance, youth gangs provide youth with
well-articulated norms and scripts and govern
almost every aspect of social behavior and
relationships in that context. Through such
overwhelming modeling and reinforcement,
youth in gangs are likely to generalize those
norms and scripts to other contexts as well—
for example, by believing generally that any
insult or provocation must be addressed with a
violent response.
Teacher, Peer, and School
Influences on Cognition
and Aggression
Given the influence of multiple contexts
on development, cognition, and behavior, how
can we best design and implement prevention
and intervention programs that acknowledge,
incorporate, and modify these ecological
influences? From the cognitive-ecological
perspective, schools represent excellent
settings for prevention and intervention. In
particular, schools have been identified as key
venues for the delivery of services related to
the mitigation or prevention of aggression and
other problem behaviors, in part because of the
opportunities they provide for reaching large
numbers of children and adolescents, thus
permitting universal or large-scale selected
preventive interventions (Farrell, Meyer, Kung,
& Sullivan, 2001).
Within the cognitive-ecological framework, schools also represent a setting for
development that includes multiple sources of
influence on student cognition and behaviors.
In this framework, how teachers treat students
and respond to classroom behavior, how
students interact in the classroom as well as
the lunchroom and playground, and how
the school in general deals with students can
promote or discourage positive or negative
behaviors. Schools thus directly impact
student cognitive, social, emotional, and
behavioral development by influencing the
transactions of students within the school
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system. Further, schools also can influence
transactions between systems, for instance, by
encouraging family involvement in student life
or school work, or by providing opportunities
for student involvement in community service
learning activities.
From a cognitive-ecological perspective,
contextual influences within schools operate
at multiple levels. Teachers, peers, and
administrators come to the school setting
with a distinct set of social-cognitive skills
and beliefs that, in turn, influence how they
treat others. A striking example of how teacher
beliefs influence both their own behavior
and student outcomes comes from a series of
experiments conducted several decades ago
by Rosenthal and colleagues (e.g., Rosenthal
& Jacobson, 1968). In these experiments, the
researchers demonstrated that teachers’ beliefs
about student abilities had a meaningful
impact on the students’ actual academic
performance. They noted that teachers
responded differently to children whom they
perceived as more capable (regardless of
their actual ability levels) compared to other
children, calling on them more frequently
and providing more encouragement in the
classroom. In turn, these students actually
improved on achievement indicators. These
results suggest that teachers’ beliefs and
attitudes towards student achievement affected
their actual achievement-relevant behaviors
with students and subsequently students’
actual achievement.
Translating this to social behavior, teacher
expectations also should influence how
students are treated through a similar process
that might actually reinforce and even shape
these behaviors. Indeed, teachers’ perceptions
of and attitudes toward their students often
have been shown to relate to students’
behaviors in the classroom (Hughes, Cavell,
& Jackson, 1999; Hughes, Cavell, & Willson,
2001), underscoring their role as socializing
agents and the importance of their attitudes
toward student behavior (Boulton, 1997;
Craig, Henderson, & Murphy, 2000). Teacher
cognitions also may shape social preferences
and peer culture in the classroom. For instance,
Chang (2003) observed that when teachers
held more negative attitudes toward student
aggression, students in their classes were more
rejecting of aggressive classmates. This effect
was attenuated, however, when coupled with
higher levels of teachers’ general warmth
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BehaviorDisorders_30(3).indd 89
toward students. In this fashion, teacher
cognition can influence student behavior by
influencing how peers respond to this behavior
in the classroom and school.
Schools also provide a venue for regular
and ongoing exposure to the peer group at
the classroom and school level. In part, this
exposure puts a normative “stamp” on certain
behaviors as a function of their frequency and
consequences. Otherwise put, if a majority
of students at a school engage regularly in a
particular problem behavior for which they
are infrequently reprimanded, it is likely
that this behavior will come to be seen as
normative and acceptable. Children learn
about appropriate behaviors by observing
the behavior of similar others in routine
activities. Aggressive behavior provides a good
illustration of these “peer contagion” effects, by
which aggressive children promote aggressive
and antisocial behavior in one another (Boxer,
Guerra, Huesmann, & Morales, in press;
Dishion, McCord, & Poulin, 1999; Espelage,
Holt, & Henkel, 2003). More generally,
children exposed frequently to aggression as
witnesses or victims also are more likely to
behave aggressively (Boxer, Edwards-Leeper,
Goldstein, Musher-Eizenman, & Dubow,
2003; Guerra, Huesmann, & Spindler, 2003;
Schwartz, 2000; Singer, Anglin, Song, &
Lunghofer, 1995). When analyzed at the level
of the classroom (i.e., specifying classrooms as
the units of analysis), it has been shown that
children’s levels of aggression tend to co-vary—
that is, entire classes may be characterized
as more or less aggressive (Stormshak et al.,
1999). Interestingly, however, a sanctioning
effect also has been observed at the level of
the peer group. Henry and colleagues (2000)
found that when children in a classroom made
behavioral norms against aggression salient
(i.e., by rejecting aggressive peers), classroom
levels of aggression reduced over time.
Although teachers and students are key
components of the overall ecology of a school,
school-level characteristics also are important
to consider. For example, rates of student
aggression appear to be lower when teachers
perceive that their school administration
maintains consistent and effective policies
toward student aggression at the school level
(Boxer, Musher-Eizenman, Dubow, Heretick, &
Danner, 2003). Similarly, bullying prevention
programs seem to be most effective when
they are designed as whole school efforts that
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send a clear message indicating bullying will
not be accepted at school (Olweus, 1993).
Further, aggressive behavior at school is likely
to be greater at unstructured times and in
unsupervised areas—for example, hallways
during class period transitions when student
perceptions of danger are higher (Astor, Meyer,
& Behre, 1999; Astor, Meyer, & Pitner, 2001;
Behre, Astor, & Meyer, 2001). However, it is
also the case that school policies can give
mixed messages about acceptable behaviors
and probable consequences. For example,
although the “zero tolerance” policy was
popularized in the 1990s as an effective
response to increasing rates of youth violence,
it also has received criticism due to inflexible
implementation and the potential to punish
students drastically for very minor offenses (cf.
Casella, 2003).
A cognitive-ecological framework emphasizes the role of teachers, peers, and school
administrators in the emergence and maintenance of students’ cognitive skills, beliefs,
and behaviors. As we have pointed out, each
of these socialization agents also brings a set
of cognitive skills and beliefs to the table that
shapes their actions accordingly. For example,
a teacher who believes that a specific child
is aggressive and unlikely to change may
respond quite differently to that child—being
more sensitive to aggression-related cues—
resulting in increased attention when the child
is aggressive and decreased attention when the
child behaves in a prosocial manner. As the
child’s aggression increases, he/she may come
to see this behavior as normative, resulting
in subsequent increases in aggression (see
Huesmann & Guerra, 1997).
A Cognitive-Ecological View
on Population-Based and
Targeted Prevention
Developmentally oriented practitioners
and researchers in the area of children’s
behavioral and mental health often have
advocated the use of preventive, rather than
remedial approaches to promoting children’s
psychosocial adjustment—particularly in
school settings (e.g., Cowen et al., 1996;
Dubow, Roecker, & D’Imperio, 1997). This
orientation stems from the recognition that
emotional and behavioral disorders are
developmental phenomena, emerging from
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BehaviorDisorders_30(3).indd 90
the conflation of individual and environmental
risk factors at multiple levels. Preventionoriented activities typically fall into two
categories (cf. Institute of Medicine, 1994).
Population-based prevention activities, also
known as universal or primary prevention,
provide services to an entire population to
reduce the likelihood that some problem will
emerge. A zero tolerance policy adopted by
school administrators in an attempt to deter
aggression in the entire student population
would be considered a population-based
strategy. Targeted (also selected or secondary)
prevention activities generally include
“at-risk” or “high-risk” individuals and are
designed to prevent the emergence of a fullscale problem following the initial appearance
of signs or symptoms of the problem. A
diversion program for first-time youthful status
offenders intended to dissuade them from
escalating into serious antisocial offending is
an example of the targeted approach (Tolan &
Guerra, 1994).2
Because it is a developmental model, the
cognitive-ecological framework may best be
applied to behavioral and emotional difficulties
through population-based and targeted
prevention services. As discussed earlier, with
respect to aggression, the cognitive-ecological
model specifies clear sources of both early (e.g.,
temperamental vulnerability, physical abuse)
and later (e.g., aggressive cognitive styles) risk
as well as factors that can promote or maintain
problems over time (e.g., violent communities,
schools, families, and media; antisocial peer
affiliations). Further, the cognitive-ecological
model identifies risk factors that may be present
for an entire population, such as a hostile
school climate or violent media, or present
only for some portion of a population, such
as domestic violence. Most importantly, the
cognitive-ecological model also implies clearly
a point in development after which population
and targeted strategies may begin to show
less effectiveness: around middle childhood
(approximate age 7–10 years old) when
children’s social cognitions are likely to begin
guiding their social behavior and to become
more resistant to change (Huesmann, 1998;
Huesmann & Guerra, 1997). The cognitiveecological framework thus underscores the
need to deliver preventive services to children
during and prior to the elementary school years,
when their social cognitions are expected to
be most malleable.
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This is not to suggest, however, that
cognitive-ecological interventions would be
ineffective for children past middle childhood.
Certainly, studies of cognitive-behavioral and
social-cognitive interventions support the
notion that even into adolescence, programs
employing those treatment modalities can
yield positive effects (e.g., Guerra & Slaby,
1990; Sussman, Rohrbach, & Mihalic,
2004; Yung & Hammond, 1995). Further,
empirical research supports the utility of
implementing
developmentally
tailored
cognitive interventions across the childhood
to adolescence age span (Boxer, Goldstein,
Musher-Eizenman, Dubow, & Heretick, in
press). Still, interventions derived from the
cognitive-ecological framework are likely to be
most effective when delivered to youth before
the youth have established persistent patterns
of aversive behavior and related social and
academic problems (Metropolitan Area Child
Study Research Group, 2002).
Cognitive-Ecological Strategies
for Population-Based and
Targeted Prevention in Schools
It has long been recognized that prevention
and intervention programs targeting aggression
and antisocial behavior may be most effective
when conducted as multilevel interventions
that also target the influence of contexts on
behavior and development. For example, the
Metropolitan Area Child Study (MACS; MACS
Research Group, 2002), Project FAST Track
(Conduct Problems Prevention Research Group,
1999), and Project LIFT (Reid, Eddy, Fetrow, &
Stoolmiller, 1999) included classroom-based,
peer group, and family interventions. One
goal of the multilevel approach, of course, is
to promote consistency across contexts: for
example, what a child learns at school via
classroom programming should be reinforced
at home and among peers. Still, this goal may
be viewed as operating within the individualdeficit framework. That is, new skills (to
replace or augment those that are presumed
to be deficient or deviant) that children learn
for managing conflict or negative arousal can
more effectively generalize in the presence of
cross-context support for implementing those
skills. The cognitive-ecological framework
requires much more than skills transfer. In
the cognitive-ecological view, ecologies must
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BehaviorDisorders_30(3).indd 91
change in tandem with individual skills to
support the emergence and crystallization of
new cognitions.
Consider the aggressive child enrolled
in a multicomponent program that provides
both classroom and family interventions. The
child may learn new problem-solving skills
in the classroom, and the child’s parents may
learn new strategies for managing that child’s
behavior in a multiple family therapy group
program. To some extent, then, the child’s
immediate contexts might change: teachers
provide instruction and reinforcement for new
behaviors at school while parents do likewise for
new behaviors at home. However, what about
other classrooms in the school building, and
other teachers? What about the neighborhoods
through which the child must travel on the way
to and from school, or playground interactions
during recess? On the home front, what about
the parents’ interactions with one another, or
with other adults in the home? What about
the child’s own neighborhood, and his/her
interactions with peers in that context?
What about the television shows the child is
permitted to watch?
With regard to population-based prevention approaches to aggression in the cognitiveecological framework, Boxer and Dubow
(2002) noted ways to modify school ecologies
in accordance with a cognitive-ecological
view. For example, schools can emphasize the
promotion of safety and nurturance rather than
the reduction of aggression and disruption
by instituting new prosocial extracurricular
activities and fostering positive and meaningful
teacher-student
relationships
(Morrison,
Furlong, & Morrison, 1994). Schools also
can integrate social and emotional learning
concepts into regular classroom materials
(Elias et al., 1997). In recent years, a number of
efforts have been underway to improve school
climate as a means for enhancing student
engagement, learning, and development.
Several different approaches and models have
been implemented, but they all share a common
set of principles. These principles focus on
building close-knit learning communities that
emphasize caring and compassion, creating a
sense of community, providing a welcoming
environment, increasing and sustaining
student-adult connections, and setting clear
and well-publicized rules and standards for
acceptable behaviors at school (Charney,
1998; Noddings, 1992).
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As mentioned previously, schools also
can influence transactions between systems.
Of particular relevance to population-based
approaches are policies and strategies for
parent engagement. A large literature suggests
that parent involvement in schools can
enhance student outcomes (e.g., Ban, 1993).
Parent involvement can provide consistency in
the learning and developmental environment
for children by establishing mutual goals that
are supported by both parents and teachers,
increasing parents’ ability to monitor their
child’s learning and behavior, and by creating
activities that link home and school. These
collaborative strategies should yield norms
and rules for behaviors that are consistent at
both home and at school, providing a clear
message that is reinforced across contexts.
Schools therefore can strive to engage their
students’ families by encouraging teacherparent communication through formal and
informal meetings, informing parents about
policies and programs through newsletters
mailed directly to homes, and enhancing
student accountability through the inclusion
of social and behavioral evaluations in student
report cards.
It is also important to note that schools can
serve as the locus of prevention efforts within
neighborhoods and larger communities.
Schools might take the lead on efforts to
reduce violence in the broader ecology by
encouraging or requiring students to engage
in prosocial community service activities or
hosting after-school activities for students as
well as adults. Schools also can partner with
university researchers to expand their services
and their positive impact (Hunter, Elias, &
Norris, 2001).
In terms of targeted prevention, a fully
elaborated cognitive-ecological approach
requires a new orientation to the therapeutic
enterprise. In this view, for lasting changes, it
would not be sufficient to provide individual
cognitive-behavioral
treatment
focused
on modifying problematic cognitions and
behaviors, even with adjunctive family
therapy, teacher training, or group social
skills training. Returning to the example of
aggression, the practitioner in such a case
would need to consider all possible ecological
sources of influence on the child’s aggressionsupporting cognitive style. Responses from
teachers, parents, and peers to the child’s
behavior would of course be important, but it
would also be important to consider the extent
284 / May 2005
BehaviorDisorders_30(3).indd 92
to which the child is exposed to aggression
across those and other contexts and make
recommendations for treatment accordingly.
For example, the practitioner would need
to assess the types and levels of aggression
in the child’s home environment and offer
suggestions for any necessary remediation:
Does the child consume violent media? Do
the parents or other adult caretakers engage
in frequent verbal conflict or any physical
aggression? Does the child view violence or
other antisocial behavior in the neighborhood?
If the answer to any of these questions is yes, the
practitioner must offer potential modifications,
such as reducing the child’s access to violent
media, referring for couples counseling, or
finding appropriate after-school activities to
limit the child’s exposure to aggression in the
community.
Future Directions and Caveats
Given the large body of research
supporting a cognitive-ecological view (cf.
Boxer & Dubow, 2002; Guerra & Huesmann,
2004), it seems imperative that researchers
and practitioners begin to design, implement,
and evaluate prevention activities derived
from this model. Although we have focused
on how the cognitive-ecological framework
can support efforts to prevent student
aggression, this framework can be applied to
crafting interventions for other emotional and
behavioral problems as well. In some respects,
cognitive-ecological approaches to dealing
with problems besides aggression can be based
directly on expansions of traditional cognitivebehavioral interventions. Cognitive-behavioral
interventions have received considerable
support in the childhood intervention literature
for dealing with a host of other emotional and
behavioral problems including anxiety and
depressive disorders (Compton et al., 2004;
Gaynor et al., 2003), stress management
and coping (Hains, 1994), and secondary
prevention of mental health problems (Durlak
& Wells, 1998). When compared to other
therapeutic modalities and psycho-educational
programs, cognitive-behavioral approaches
consistently produce the most significant gains
(Barrett & Ollendick, 2004; Compton et al.;
Kazdin & Weisz, 2003).
The key to making a cognitive-behavioral
intervention one that is cognitive-ecological
lies in the extent to which practitioners are
Behavioral Disorders, 30 (3), 277–288
7/31/05 8:03:17 PM
able to address sources of ecological risk in
the specific disorder or problem behavior. For
example, ecological risk factors for depression
include periodic major stressful life events
and ongoing daily stresses (Compas, Howell,
Phares, Williams, & Giunta, 1989). Psychoeducational interventions can of course be
used to instruct children on ways to cope
and prepare for both types of stress (Dubow,
Schmidt, McBride, Edwards, & Merk, 1993).
However, practitioners also could work with
families and teachers to reduce the prevalence
and impact of everyday hassles, for example,
by improving organization in children’s home
and classroom environments, reducing family
and peer conflict, helping families access
social services for reducing economic stress
and helping teachers access resources for
students. It should be noted that problems in the
broader community, such as crime, violence,
and poverty, are associated with a range of
potential negative emotional and behavioral
outcomes, and therefore interventions targeting
modifications to communities can benefit a
variety of child problems.
It must be said that shifting from a cognitivebehavioral to a cognitive-ecological approach
to dealing with emotional and behavioral
difficulties in students is not likely to be an
easy or rapid transition. Besides the typical
barriers to implementation, such as teacher
and parent resistance to changing their own
behaviors to ameliorate children’s difficulties,
the cost of providing mental health programs
and services, and of course, the stability of
children’s behavioral difficulties (especially
aggression; Huesmann & Guerra, 1997),
cognitive-ecological intervention requires the
practitioner to place even greater demands on
individuals representing sources of ecological
influence, not to mention on whole ecologies.
However, one way to facilitate the transition to
cognitive-ecological intervention is for schoolbased practitioners to educate teachers and
families about this broader perspective and
thus rally their support for new populationbased or targeted programs.
Summary
In this article, we have presented a
cognitive-ecological model for understanding
and preventing an array of emotional and
behavioral problems, and have suggested
directions for school based universal and
selected
programs,
particularly
those
Behavioral Disorders, 30 (3), 277–288
BehaviorDisorders_30(3).indd 93
targeting aggressive behavior. Consistent
with the cognitive underpinnings of behavior
discussed, we believe that efforts should
target certain cognitive skills and knowledge
structures across multiple contexts that change
over time. Of particular importance are socialcognitive skills that encourage attention to
multiple cues in a setting, interpretation of
cues based on factual information rather
than stereotypes or biases, and generation of
responses and consequences that emphasize
consideration of both self and others. It also
is critical that contextual influences coalesce
in their normative orientations so that children
learn consistent standards that encourage
prosocial and socially competent behavior.
These standards can be communicated through
schoolwide interventions such as the Olweus
(1993) bullying prevention program; they
must also be reinforced at the classroom and
peer level through consistent reinforcement
of rules. An emphasis on the cognitive
foundations of behavior in context provides a
venue for intervention that is consistent with
the educational mission of schools and their
important role in promoting child well-being.
NOTES
1. It is important to note that although this
model emphasizes the context-cognitionbehavior link, this does not mean that
emotional reactions are not considered.
In many instances, emotions may be the
strongest predictor of behavior, for instance,
perceptions of distress blamed on others can
lead to an upward spiral of extreme rage that
leads to reactive, hostile, and under-controlled
aggression. Similarly, distress blamed on
self can lead to a downward spiral of shame
and withdrawal (Beck, 1999). Alternately,
children who are prone to strong emotional
reactions might be too overwhelmed during a
social encounter to search for relevant cues,
generate solutions, etc. (e.g., Lemerise &
Arsenio, 2000). As this illustrates, we do not
deny the innate primacy of many emotional
reactions, but contend that most events
trigger a chain of emotional and cognitive
reactions, such that emotions are moderated
by cognitions and cognitions are moderated
by emotional reactions.
2. A third type of prevention—indicated or
tertiary prevention—is similar in concept
May 2005 / 285
7/31/05 8:03:20 PM
and execution to remediation or intervention
for full-scale psychosocial problems (e.g.,
the use of stimulant medications for attentiondeficit/hyperactivity disorder). To refer to
it as “prevention” is essentially a semantic
convention, and thus, we do not discuss
it here.
REFERENCES
Anderson, C. A., & Bushman, B. J. (2002). Human
aggression. Annual Review of Psychology, 53,
27–51.
Astor, R. A., Meyer, H. A., & Behre, W. J. (1999).
Unowned places and times: Maps and interviews
about violence in high schools. American
Education Research Journal, 36, 3–42.
Astor, R. A., Meyer, H. A., & Pitner, R. O. (2001).
Elementary and middle school students’
perceptions
of
violence-prone
school
subcontexts. Elementary School Journal, 101,
511–528.
Ban, J. R. (1993). Parents assuring student success
(PASS): Achievement made easy by learning
together. Bloomington, IN: National Educational
Service.
Barrett, P. M., & Ollendick, T. H. (2004). Handbook
of interventions that work with children and
adolescents: Prevention and treatment. New
York: Wiley.
Beck, A. T. (1999). Prisoners of hate. New York:
Harper Collins.
Behre, W. J., Astor, R. A., & Meyer, H. A. (2001).
Elementary and middle school teachers’
reasoning about intervening in school violence:
An examination of violence-prone school
subcontexts. Journal of Moral Education, 30,
151–183.
Boulton, M. J. (1997). Teachers’ views on bullying:
Definitions, attitudes, and ability to cope.
British Journal of Educational Psychology, 67,
223–233.
Boxer, P., & Butkus, M. (in press). Individual
intervention for aggression in early adolescence:
An application of the cognitive-ecological
model. Clinical Case Studies.
Boxer, P., & Dubow, E. F. (2002). A social-cognitive
information-processing model for school-based
aggression reduction and prevention programs.
Applied and Preventive Psychology, 10,
177–192.
Boxer, P., Edwards-Leeper, L., Goldstein, S. E.,
Musher-Eizenman, D., & Dubow, E. F. (2003).
Exposure to “low-level” aggression in school:
Associations with aggressive behavior, future
expectations, and perceived safety. Violence &
Victims, 18, 691–704.
Boxer, P., Goldstein, S. E., Musher-Eizenman,
D., Dubow, E. F., & Heretick, D. (in press).
Developmental issues in the prevention of
286 / May 2005
BehaviorDisorders_30(3).indd 94
school aggression from the social-cognitive
perspective. Journal of Primary Prevention.
Boxer, P., Guerra, N. G., Huesmann, L. R., & Morales,
J. (in press). Proximal peer-level effects of
a small-group selected prevention on aggression in elementary school children:
An investigation of the peer contagion
hypothesis. Journal of Abnormal Child
Psychology.
Boxer, P., Musher-Eizenman, D. R., Dubow, E. F.,
Heretick, D. M. L., & Danner, S. A. (2003).
Validity of teacher perceptions of student
aggression: A cognitive-ecological perspective. Unpublished manuscript, University
of Michigan.
Bronfenbrenner, U. (1979). The ecology of human
development: Experiments by nature and design.
Cambridge, MA: Harvard University.
Casella, R. (2003). Zero tolerance policy in schools:
Rationale, consequences, and alternatives.
Teacher’s College Record, 105, 872–892.
Chang, L. (2003). Variable effects of children’s
aggression, social withdrawal, and prosocial
leadership as functions of teacher beliefs and
behaviors. Child Development, 74, 535–548.
Charney, R. S. (1998). Teaching children to care:
Management in the responsive classroom.
Greenfield, MA: Northeast Foundation for
Children.
Compas, B. E., Howell, D. C., Phares, V., Williams,
R. A., & Giunta, C. T. (1989). Risk factors
for emotional-behavioral problems in young
adolescents: A prospective analysis of adolescent
and parent stress. Journal of Consulting and
Clinical Psychology, 57, 732–740.
Compton, S. N., March, J. S., Brent, D., Albano, A.
M., Weersing, V. R., & Curry, J. (2004). Cognitivebehavioral psychotherapy for anxiety and
depressive disorders in children and adolescents:
An evidence-based medicine review. Journal of
the American Academy of Child and Adolescent
Psychiatry, 43, 930–959.
Conduct Problems Prevention Research Group
(1999). Initial impact of the Fast Track Prevention
Trial for conduct problems: I. The high-risk
sample. Journal of Consulting and Clinical
Psychology, 67, 631–647.
Cowen, E. L., Hightower, A. D., Pedro-Carroll, J. L.,
Work, W. C., Wyman, P. A., & Haffey, W. G.
(1996). School-based prevention for children
at risk: The Primary Mental Health Project.
Washington, DC: American Psychological
Association.
Craig, W. M., Henderson, K., & Murphy, J. G.
(2000). Prospective teachers’ attitudes toward
bullying and victimization. School Psychology
International, 21, 5–21.
Crick, N. R., & Dodge, K. A. (1994). A review and
reformulation of social information processing
mechanisms
in
children’s
adjustment.
Psychological Bulletin, 115, 74–101.
Behavioral Disorders, 30 (3), 277–288
7/31/05 8:03:23 PM
Dishion, T. J., McCord, J., & Poulin, F. (1999). When
interventions harm: Peer groups and problem
behavior. American Psychologist, 54, 755–764.
Dodge, K. A., Bates, J. E., & Pettit, G. S. (1990).
Mechanisms in the cycle of violence. Science,
250, 1678–1683.
Dodge, K. A., Pettit, G. S., & Bates, J. E. (1997). How
the experience of early physical abuse leads
children to become chronically aggressive. In
D. Cicchetti & S. L. Toth (Eds.), Developmental
perspectives on trauma: Theory, research, and
intervention (Vol. 8, pp. 262–288). Rochester,
NY: University of Rochester.
Dodge, K. A., Pettit, G. S., Bates, J. E., & Valente, E.
(1995). Social information-processing patterns
partially mediate the effect of early physical
abuse on later conduct problems. Journal of
Abnormal Psychology, 104, 632–643.
Dubow, E. F., Roecker, C. E., & D’Imperio, R. (1997).
Mental health. In R. T. Ammerman & M. Hersen
(Eds.), Handbook of prevention and treatment
with children and adolescents: Intervention in
the real world context (pp. 259–286). New York:
Wiley.
Dubow, E. F., Schmidt, D., McBride, J., Edwards,
S., & Merk, F. L. (1993). Teaching children
to cope with stressful experiences: Initial
implementation and evaluation of a primary
prevention program. Journal of Clinical Child
Psychology, 22, 428–440.
Durlak, J. A., Rubin, L. A., & Kahng, R. D. (2001).
Cognitive behavioral therapy for children
and adolescents with externalizing problems.
Journal of Cognitive Psychotherapy, 15,
183–194.
Durlak, J. A., & Wells, A. M. (1998). Evaluation of
indicated preventive intervention (secondary
prevention) mental health programs for
children and adolescents. American Journal of
Community Psychology, 26, 775–802.
Elias, M. J., Zins, J. E., Weissberg, R. P., Frey, K. S.,
Greenberg, M. T., Haynes, N. M., et al. (1997).
Promoting social and emotional learning:
Guidelines for educators. Alexandria, VA:
Association for Supervision and Curriculum
Development.
Eron, L. D. (1994). Theories of aggression: From
drives to cognitions. In L. R. Huesmann (Ed.),
Aggressive behavior: Current perspectives (pp.
3–11). New York: Plenum.
Espelage, D. L., Holt, M. K., & Henkel, R. R. (2003).
Examination of peer-group contextual effects
on aggression during early adolescence. Child
Development, 74, 205–220.
Farrell, A. D., Meyer, A. L., Kung, E. M., & Sullivan,
T. N. (2001). Development and evaluation of
school-based prevention programs. Journal of
Clinical Child Psychology, 30, 207–220.
Gaynor, S. T., Weersing, V. R., Kolko, D. J., Birmaher,
B., Heo, J., & Brent, D. A. (2003). The prevalence
and impact of large sudden improvements
Behavioral Disorders, 30 (3), 277–288
BehaviorDisorders_30(3).indd 95
during adolescent therapy for depression: A
comparison across cognitive-behavioral, family,
and supportive therapy. Journal of Consulting
and Clinical Psychology, 71, 386–393.
Guerra, N. G., & Huesmann, L. R. (2004). A
cognitive-ecological model of aggression.
Revue Internationale de Psychologie Sociale, 2,
177–204.
Guerra, N. G., Huesmann, L. R., & Spindler, A. (2003).
Community violence exposure, social cognition,
and aggression among urban elementary-school
children. Child Development, 74, 1507–1522.
Guerra, N. G., Huesmann, L. R., Tolan, P. H.,
VanAcker, R., & Eron, L. D. (1995). Stressful
events and individual beliefs as correlates of
economic disadvantage and aggression among
urban children. Journal of Consulting and
Clinical Psychology, 63, 518–528.
Guerra, N. G., & Slaby, R. L. (1990). Cognitive
mediators of aggression in adolescent offenders:
II. Intervention. Developmental Psychology, 26,
269–277.
Hains, A. A. (1994). The effectiveness of a schoolbased, cognitive-behavioral stress management
program with adolescents reporting high and
low levels of emotional arousal. The School
Counselor, 42, 114–125.
Haynes, S. N., & O’Brien, W. H. (1990). Functional
analysis in behavior therapy. Clinical Psychology Review, 10, 649–668.
Henggeler, S. W., Schoenwald, S. K., Bourduin,
C. M., Rowland, M. D., & Cunningham, P. B.
(1998). Multisystemic treatment of antisocial
behavior in children and adolescents. New York:
Guilford.
Henry, D., Guerra, N. G., Huesmann, L. R., Tolan, P.,
Van Acker, R., & Eron, L. D. (2000).Normative
influences on aggression in urban elementary
school classrooms. American Journal of
Community Psychology, 28, 59–81.
Huesmann, L. R., (1998). An information processing
model for the development of aggression.
Aggressive Behavior, 14, 13–24.
Huesmann, L. R., & Guerra, N. G. (1997). Childrens’
normative beliefs about aggression and
aggressive behavior. Journal of Personality and
Social Psychology, 72, 408–419.
Hughes, J. N., Cavell, T. A., & Jackson, T. (1999).
Influence of the teacher-student relationship
on childhood conduct problems: A prospective
study. Journal of Clinical Child Psychology, 28,
173–184.
Hughes, J. N., Cavell, T. A., & Willson, V. (2001).
Further support for the developmental
significance of the quality of the teacher-student
relationship. Journal of School Psychology, 39,
289–301.
Hunter, L., Elias, M. J., & Norris, J. (2001). Schoolbased violence prevention: Challenges and
lessons learned from an action research project.
Journal of School Psychology, 39, 161–175.
May 2005 / 287
7/31/05 8:03:27 PM
Institute of Medicine (1994). Reducing risks for mental
disorders: Frontiers for preventive intervention
research. Washington, DC: National Academy.
Kazdin, A. E., & Weisz, J. R. (2003). Evidence-based
psychotherapies for children and adolescents.
New York: Guilford.
Lemerise, E. A., & Arsenio, W. F. (2000). An integrated
model of emotion process and cognition in social
information processing. Child Development, 71,
107–118.
Lochman, J. E., & Lenhart, L. (1995). Cognitive
behavioral therapy of aggressive children: Effect
of schemas. In H. P. van Bilsen, P. C. Kendall, &
J. H. Slavenburg (Eds.), Behavioral approaches
for children and adolescents: Challenges for the
next century (pp. 144–166). New York: Plenum.
Metropolitan Area Child Study Research Group.
(2002). A cognitive-ecological approach to
preventing aggression in urban settings: Initial
outcomes for high-risk children. Journal of
Consulting and Clinical Psychology, 70, 179–
194.
Morrison, G. M., Furlong, M. J., & Morrison, R.
L. (1994). School violence to school safety:
Reframing the issue for school psychologists.
School Psychology Review, 23, 236–256.
Noddings, N. (1992). The challenge to care in
schools: An alternative approach to education.
New York: Teachers College.
Olweus, D. (1993). Bullying at school: What we
know and what we can do. Malden, MA:
Blackwell Publishers.
Orobio de Castro, B., Veerman, J. W., Koops, W.,
Bosch, J. D., & Monshouwer, H. J. (2002).
Hostile attribution of intent and aggressive
behavior: A meta-analysis. Child Devevlopment,
73, 916–934.
288 / May 2005
BehaviorDisorders_30(3).indd 96
Reid, J. B., Eddy, J. M., Fetrow, R. A., & Stoolmiller, M.
(1999). Description and immediate impacts of a
preventive intervention for conduct problems.
American Journal of Community Psychology,
27, 483–517.
Rosenthal, R., & Jacobson, L. (1968). Pygmalion in
the classroom: Teacher expectation and pupils’
intellectual development. New York: Holt,
Reinhart, & Winston.
Schwartz, D. (2000). Subtypes of victims and
aggressors in children’s peer groups. Journal of
Abnormal Child Psychology, 28, 181–192.
Singer, M. I., Anglin, T. M., Song, L., & Lunghofer, L.
(1995). Adolescents’ exposure to violence and
associated symptoms of psychological trauma.
Journal of the American Medical Association,
273, 477–483.
Stormshak, E. A., Bierman, K. L., Bruschi, C.,
Dodge, K. A., Coie, J. D., & Conduct Problems
Prevention Research Group. (1999). The
relation between behavior problems and peer
preference in different classroom contexts.
Child Development, 70, 169–182.
Sussman, S., Rohrbach, L., & Mihalic, S. (2004).
Blueprints for violence prevention, Book Twelve:
Project Towards No Drug Abuse. Boulder,
CO: Center for the Study and Prevention of
Violence.
Tolan, P. H., & Guerra, N. G. (1994). Prevention of
delinquency: Current status and issues. Applied
and Preventive Psychology, 3, 251–273.
Yung, B., & Hammond, R. (1995). PACT: Positive
Adolescents Choices Training: A model for
violence prevention groups with AfricanAmerican youth. Champaign, IL: Research
Press.
Behavioral Disorders, 30 (3), 277–288
7/31/05 8:03:31 PM