Analyze an Article About the Impact of Trauma in Education

Review the journal articles attached. Reflect on the impact of trauma in educational settings and identify at least one way in which educators can work to prevent or address this. Consider one way in which support personnel, such as a school counselor, school nurse, or administrator, might assist in preventing or addressing trauma

2 pages and use the attached journal articles and another one to support your reflection.

Exposure to Violence and Nonviolent Life Stressors and Their Relations to
Trauma-Related Distress and Problem Behaviors Among Urban

Early Adolescents

Erin L. Thompson, Jasmine N. Coleman, Kelly E. O’Connor, Albert D. Farrell, and Terri N. Sullivan
Virginia Commonwealth University

Objective: The impact of exposure to violence must be considered within the context of a larger
constellation of nonviolent life stressors faced by youth in underresourced communities. This study
examined nonviolent life stressors, two types of violence exposure, and their associations with trauma-
related distress and problem behaviors. Method: Participants were a predominantly African American
(80%) sample of early adolescents (Mage � 12.9 years) living in communities with high rates of crime

Structural equation models examined the extent to which nonviolent life stressors and violence exposure
(witnessing violence and physical victimization) were associated with adolescents’ frequencies of
trauma-related distress (reexperiencing traumatic events, avoidance, and hyperarousal) and problem
behaviors (physical aggression, delinquent behavior, and substance use). Results: Nonviolent life
stressors, witnessing violence, and physical victimization were each significantly associated with all three
symptoms of trauma-related distress and with each of the three problem behaviors. In each case, stronger
relations with trauma-related distress and problem behaviors were found for nonviolent life stressors than
for physical victimization. After controlling for nonviolent life stressors, both types of violence exposure
remained significantly associated with problem behaviors but differed in their patterns of association with
trauma-related distress. No gender differences were found among these relations. Conclusion: These
findings highlight the need to control for nonviolent life stressors when examining the impact of violence
exposure on adjustment. Furthermore, mental health providers may be missing important information
related to adolescents’ symptomatology if they fail to inquire about trauma-related distress when
adolescents deny exposure to violent and life-threatening events.

Keywords: violence, nonviolent life stressors, trauma-related distress, problem behavior, adolescence

Exposure to violence is a significant public health concern that
disproportionally affects adolescents living in urban, low-income
communities (Ozer & Weinstein, 2004; Stein, Jaycox, Kataoka,
Rhodes, & Vestal, 2003). It includes physical victimization, de-
fined as experiencing acts of force, such as being slapped,
punched, hit, or shot, and witnessing violence, which involves
seeing the physical victimization of someone else. A nationally

representative survey of youth living in the United States indicated
that 27% of adolescents aged 10 to 13 and almost half (42%) of
adolescents aged 14 to 17 had witnessed community violence in
the past year (Finkelhor, Ormrod, & Turner, 2009). These rates are
concerning, given the association between violence exposure and
various forms of maladjustment, such as trauma-related distress,
aggression, delinquency, and substance use (Fowler, Tompsett,
Braciszewski, Jacques-Tiura, & Baltes, 2009; Pinchevsky, Fagan,
& Wright, 2014). Adolescents in low-income, urban communities
are at an increased risk not only for exposure to violence but also
for a host of nonviolent stressful experiences that have been linked
to maladjustment (Natsuaki et al., 2007; Ozer & Weinstein, 2004).
However, few studies have examined the unique impact of expo-
sure to violence on adverse outcomes after accounting for nonvi-
olent life stressors (for exceptions, see Allison et al., 1999; Brooks-
Gunn, Johnson, & Leventhal, 2010; Evans, 2004; Farrell et al.,
2007). The purpose of this study was to examine violence exposure
and nonviolent life stressors and their associations with adoles-
cents’ trauma-related distress and problem behaviors.

Nonviolent Life Stressors

Ecological theory asserts that healthy development occurs most
frequently when children’s environments are both consistent and
predictable (Bronfenbrenner & Evans, 2000). In contrast, chaotic

This article was published Online First November 7, 2019.
X Erin L. Thompson, Jasmine N. Coleman, Kelly E. O’Connor, Albert

D. Farrell, and Terri N. Sullivan, Department of Psychology, Virginia
Commonwealth Universit

This study was funded by the National Institute of Child Health and
Human Development Grant 1R01HD089994, the National Center for In-
jury Prevention and Control, Centers for Disease Control and Prevention,
CDC Cooperative Agreement 5U01CE001956, and the National Institute
of Justice, Grant 2014-CK-BX-0009. The findings and conclusions in this
report are those of the authors, and do not necessarily represent the official
position of the National Institute of Child Health and Human Development,
the Centers for Disease Control and Prevention, or the National Institute of
Justice.

Correspondence concerning this article should be addressed to Albert D.
Farrell, Department of Psychology, Virginia Commonwealth University,
P.O. Box 842018, Richmond, VA 23284-2018. E-mail: afarrell@vcu.edu

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Psychology of Violence
© 2019 American Psychological Association 2020, Vol. 10, No. 5,

509

–519
ISSN: 2152-0828 http://dx.doi.org/10.1037/vio0000264

509

https://orcid.org/0000-0003-4389-1125

mailto:afarrell@vcu.edu

http://dx.doi.org/10.1037/vio0000264

environments, characterized by high levels of crowding, noise, and
residential instability (Brooks-Gunn et al., 2010), are inversely
related to positive well-being (Wachs & Evans, 2010). According
to the risk and resilience model of developmental psychopathology
(Compas & Andreotti, 2013), nonviolent, and often chronic, life
experiences can produce significant physical, cognitive, and envi-
ronmental changes that increase the risk for engaging in maladap-
tive behaviors (Compas & Andreotti, 2013). These types of envi-
ronmental characteristics may be particularly salient among racial
and ethnic minority youth living in urban settings, as they face
nonviolent risk factors, such as racism, social stratification, and
inequitable distribution of wealth (Evans, 2004). Indeed, research
has established links between nonviolent life stressors and inter-
nalizing and externalizing behaviors of ethnic and racial minority
youth (Liu, Bolland, Dick, Mustanski, & Kertes, 2016; Liu, Mus-
tanski, Dick, Bolland, & Kertes, 2017; Natsuaki et al., 2007). In
addition, a previous study revealed that concentrated neighborhood
disadvantage accounted for over a third of the difference in expo-
sure to violence between African American and White youth
(Zimmerman & Messner, 2013).

Despite their potential impact, few previous studies evaluating
the impact of violence exposure on adjustment have taken into
account the influence of other concurrent, nonviolent stressors
experienced by adolescents. This is a serious limitation, given
evidence suggesting that emotional and behavioral difficulties are
more highly associated with nonviolent life stressors than with
exposure to violence (Liu et al., 2016; Ozer & Weinstein, 2004).
Ozer and Weinstein (2004), for example, found that trauma-related
distress was more highly correlated with nonviolent life stressors
(e.g., “no place to play in the neighborhood”) than with violence
exposure (r � .52 vs. .29) among an ethnically diverse sample of
seventh graders. They also found that both constructs uniquely
predicted increases in trauma-related distress after controlling for
one another. Similarly, Liu and colleagues (2016) found that
among African American 13- to 19-year-old adolescents, nonvio-
lent life stressors and violence exposure were each uniquely asso-
ciated with aggressive and rule-breaking behavior in a model that
also controlled for racial discrimination (�s � .23 and .16 for
nonviolent life stressors and exposure to violence, respectively).
Aggressive and rule-breaking behavior was also more highly cor-
related with nonviolent life stressors than with exposure to vio-
lence (r � .39 vs. .30, respectively). These findings provide
empirical support for investigating associations between violence
exposure and adjustment within the context of other nonviolent life
stressors experienced by youth, particularly among adolescents of
color.

Physical Victimization Versus Witnessing Violence

There is growing evidence that physical victimization and wit-
nessing violence are related but distinct constructs (Vermeiren,
Schwab-Stone, Deboutte, Leckman, & Ruchkin, 2003). In a meta-
analysis of 110 studies, Fowler and colleagues (2009) found stron-
ger associations between physical victimization, as compared with
witnessing violence, and a range of externalizing problems. In
contrast, Cyr and colleagues (2017) found that physical victimiza-
tion (i.e., assault) was not a significant predictor of posttraumatic
stress disorder (PTSD) symptoms after controlling for witnessing
violence. Previous studies have also shown that whereas physical

victimization tends to co-occur with witnessing violence, not all
youth who witness violence are directly victimized (Ayer et al.,
2019; Ford, Grasso, Hawke, & Chapman, 2013). Taken together,
these findings underscore the importance of differentiating be-
tween witnessing violence and physical victimization to clarify
their unique and combined associations with adolescent develop-
ment.

Gender Differences

There is also a need to determine how male and female adoles-
cents differ in their exposure to violent and nonviolent life stres-
sors and how such stressors may influence adolescent adjustment
differently. Compared with girls, boys tend to be more frequently
exposed to violence (Fowler et al., 2009) and are at greater risk for
engaging in problem behaviors (Card, Stucky, Sawalani, & Little,
2008). Girls, in contrast, have been shown to be at a greater risk for
developing trauma-related distress (Alisic et al., 2014). However,
little research has examined gender differences in nonviolent
stressful life events or their differential association with internal-
izing and externalizing behaviors. One exception was Liu and
colleagues (2016), who found no moderating effects for gender on
relations between nonviolent life stressors and externalizing prob-
lems (i.e., aggressive and rule-breaking behavior) or internalizing
symptoms (i.e., anxiety and depression). Additional work is war-
ranted to clarify the moderating role of gender in studies evaluat-
ing the unique associations between violence exposure, nonviolent
life stressors, and multiple indicators of adjustment.

Current Study

The current study examined nonviolent life stressors and two
types of violence exposure (i.e., witnessing violence and physical
victimization) and their relations to trauma-related distress (i.e.,
reexperiencing traumatic events, avoidance, and hyperarousal) and
problem behaviors (i.e., physical aggression, delinquent behavior,
and substance use) among a predominantly African American
sample of early adolescents living in urban, underresourced com-
munities. We focused on concurrent relations to determine the
extent to which recent experiences including nonviolent life stres-
sors, witnessing violence, and physical victimization were associ-
ated with trauma-related distress and problem behaviors during
early adolescence. We hypothesized as follows:

Hypothesis 1: Nonviolent life stressors and both types of
violence exposure would each be correlated with the three
symptoms of trauma-related distress and the three problem
behaviors;

Hypothesis 2: Compared with exposure to violence, nonvio-
lent life stressors would be more highly correlated with each
of the outcomes based on previous research;

Hypothesis 3: Nonviolent life stressors would account for a
unique proportion of variance in outcomes even after control-
ling for both types of violence;

Hypothesis 4: Exposure to violence would account for a
unique proportion of variance in the outcomes after control-
ling for nonviolent life stressors; and

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510 THOMPSON, COLEMAN, O’CONNOR, FARRELL, AND SULLIVAN

Hypothesis 5: No specific gender differences were hypothe-
sized regarding the relations between violent and nonviolent
events and the adjustment variables.

Method

Participants

We conducted a secondary analysis of data from a project that
collected 8 years of data between 2010 and 2018 from 2,653
students in three public schools in neighborhoods with high levels
of violence (Farrell, Sullivan, Sutherland, Corona, & Masho,
2018). The purpose of that project was to evaluate the Olweus
Bullying Prevention Program (Olweus & Limber, 2010). Between
74% and 100% of students at the participating schools were
eligible for the federal free or reduced lunch. During Year 1, the
project recruited a random sample of English-speaking sixth-,
seventh-, and eighth-grade students from the rosters at each school
(N � 669). In each subsequent school year, project staff recruited
a new sample of 295 to 340 new participants from each school that
included a new cohort of sixth-grade students and a sample of
seventh- and eighth-grade students to replace those who left the
schools or withdrew from the project. Active student assent and
parent consent were obtained from about 80% of those eligible.

The final sample had a mean age of 12.9 years (SD � 1.10);
51% were female. The sample was about evenly distributed across
the sixth, seventh, and eighth grades (ns � 876 to 891). In all, 17%
identified their ethnicity as Hispanic or Latino/a, 11% did not
endorse any racial categories, of whom 91% described themselves
as Hispanic or Latino/a. Of the rest, the majority (80%) endorsed
African American or Black as either the sole category (72%) or as
one of several categories (8%). The remainder of participants
described themselves as White (5%), Asian (1%), American Indian
or Alaska Native (1%), or Native Hawaiian or Other Pacific
Islander (1%). Approximately 41% lived with a single mother,
26% with both biological parents, 23% with a parent and step-
parent, 7% with a relative without a parent, and 3% with their
father without a mother or stepmother. In all, 70% participated
while their school was implementing the intervention.

Procedure

The evaluation study used a multiple baseline experimental
design wherein the order in which intervention activities were
initiated in each school was randomized by having an administra-
tor from each school draw a face-down card from a standard deck
of playing cards. Intervention activities began in Year 2 at the
school whose administrator drew the highest valued card, in Year
3 at the school whose administrator drew the next highest valued
card, and in Year 6 at the school whose administrator drew the
lowest valued card. The focus of the intervention was on improv-
ing school climate through (a) school-level components, including
the formation of a bullying prevention coordinating committee to
assist in staff training and developing of school rules related to
student behavior and (b) classroom-level, weekly classes taught by
teachers, including antibullying rules, the bullying circle, leader-
ship, and stress management.

Research staff described the study to students and gave them
consent forms to take home to their parents. Parental consent and

student assent letters described the study as a project to learn more
about school, family, and community-based programs to create
safer and healthier schools and communities. Families were also
told that lessons would be taught in some sixth, seventh, and eighth
grade classrooms and that students would fill out a 45-min survey
twice a year. Participants were given $5 gift cards if they returned
the consent form, even if parents did not give consent for partic-
ipation. Surveys were completed on computer-assisted interviews.

Research assistants administered surveys to small groups of
students in the school during the school year and in participants’
homes or public spaces during the summer. Participants received a
$10 gift card at each wave when they completed any part of the
survey. For more information, see the article by Farrell, Sullivan,
et al. (2018). The project collected data four times per year (i.e.,
every 3 months), using a planned missing data design, wherein
participants were randomly assigned to complete two out of four
waves during each year they participated. The planned missing
data design was used to reduce costs, carryover effects, participant
burden, fatigue, and attrition (Graham, Taylor, & Cumsille, 2001).
Because the current study focused on relations between concurrent
experiences and behavior, we created a cross-sectional data set that
included one randomly selected wave for each of the 2,653 par-
ticipating students. The university’s institutional review board
approved all procedures.

Measures

Nonviolent life stressors. We used the Urban Adolescents
Negative Life Experiences Scale to measure the frequency of
experiencing nonviolent life stressors. Items were drawn from
three sources: The Interpersonal Problem Solving Inventory for
Urban Adolescents (Farrell, Ampy, & Meyer, 1998), the Urban
Adolescents Life Experiences Scale (Allison et al., 1999), and a
qualitative study in which a predominantly African American
sample of adolescents from low-income communities identified
stressful problem situations (Farrell et al., 2007). Priority was
given to selecting items that overlapped across sources. Items that
reflected witnessing violence or experiencing victimization were
excluded to avoid overlap with the exposure to violence measures.
The final set of 20 items included family stressors (e.g., “Family
members were getting on your nerves” and “Someone in your
family got in serious trouble”), transitions (e.g., “Your parent lost
a job” and “Someone in your family that you were close to doesn’t
live with you anymore”), resource limitations (“You didn’t get
enough to eat” and “You didn’t have transportation to get some-
where you wanted to go”), and neighborhood stressors (“You had
trouble sleeping at night because it was noisy in your neighbor-
hood or your room was too hot or too cold”). Participants rated
how frequently each stressor occurred in the past 3 months on a
5-point scale (1 � never, 2 � once or twice, 3 � once or twice a
month, 4 � once or twice a week, 5 � almost every day). We
created a composite indicator to represent nonviolent life stressors
by averaging ratings across items. This was based on Bollen and
Bauldry (2011), who argued that a composite indicator may be
more appropriate than a latent variable for items that do not meet
the assumption of conceptual unity required by latent variables.
They noted that it is more appropriate to consider items such as
exposure to stressful life events as causes of a construct (exposure
to stressful events), the specific pattern of which may vary across

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511LIFE STRESSORS AND ADJUSTMENT

individuals rather than as interchangeable indicators that reflect an
underlying latent variable. Cronbach’s � for the composite was .81
in the current study.

Violence exposure. We used the Survey of Children’s Expo-
sure to Community Violence (Richters & Saltzman, 1990) to
assess the frequency of exposure to violence. Although the original
version assessed both the frequency and context of the incidents
(e.g., relationship to perpetrator or where incident occurred), we
only assessed frequency. The resulting measure included 10 items
that assess victimization (e.g., “Been chased by gangs or older
kids?”) and 10 that assess witnessing violence (e.g., “Seen some-
one else being attacked or stabbed with a knife?”). Respondents
indicated how often they had been victimized or witnessed vio-
lence in the past 3 months on a 6-point scale (1 � never, 2 � 1–2
times, 3 � 3–5 times, 4 � 6–9 times, 5 � 10–19 times, 6 � 20 or
more times). The original measure has been used in many studies
including the National Institute of Mental Health Community
Violence Project (Martinez & Richters, 1993). Based on the same
rationale as for nonviolent life stressors, we created composite
variables for physical victimization and witnessing violence by
averaging ratings across items. Alphas based on the average fre-
quency across items were .71 and .86, respectively.

Trauma-related distress. We used the Checklist of Chil-
dren’s Distress Symptoms (Richters & Martinez, 1990) to assess
trauma-related distress. This 28-item measure was developed to
examine the impact of exposure to violence on children’s emo-
tional and psychological well-being in a community violence
project (i.e., Martinez & Richters, 1993). Items correspond to the
Diagnostic and Statistical Manual of Mental Disorders, Third
Edition (American Psychiatric Association, 1987) diagnostic cri-
teria for PTSD and the PTSD symptom clusters of reexperiencing
(“How often do you feel like something bad or frightening from
the past is happening all over again?”), avoidance (e.g., “How
often do you avoid or try not to go to places or do things that
remind you something bad that happened in the past?”), and
hyperarousal (e.g., “How often do you watch things around you
real closely in order to protect yourself from something bad
happening?”). Respondents rated each item on a 5-point scale (1

�

never, 2 � seldom, 3 � once in a while, 4 � a lot of the time, 5 �
most of the time). Previous research has found higher levels of
violence exposure to be associated with higher scores on the
Checklist of Children’s Distress Symptoms (Howard, Feigelman,
Li, Cross, & Rachuba, 2002).

We conducted a confirmatory factor analysis to evaluate the
three-factor solution within our sample. Consistent with previous
research (Overstreet & Braun, 2000), responses were recoded to be
more clinically meaningful, such that ratings of “never,” “seldom,”
and “once in a while” reflected the absence or low level of a
symptom (coded 0) and ratings of “a lot” or “most of the time”
reflected the presence of an above threshold symptom (coded 1).
We evaluated models using the �2 difference test, the root mean
square error of approximation (RMSEA), comparative fit index
(CFI), and Tucker–Lewis index (TLI). Although the Reexperienc-
ing and Avoidance factors were highly correlated (r � .92), the
three-factor model with factors representing reexperiencing, avoid-
ance, and hyperarousal fit the data adequately, �2(347) � 2855.57,
RMSEA � .05, CFI � .92, TLI � .92, and improved upon the fit
of the one factor model based on the RMSEA, CFI, and TLI for
both boys and girls (��2 � 112.15 and 222.18, ps � .001,

�RMSEA � .00 and �.01, �CFI � .01 and .02, �TLI � .02 and
.02, respectively).

Problem behaviors. We used the Problem Behavior Fre-
quency Scale–Adolescent Report (PBFS-AR; Farrell, Thompson,
Mehari, Sullivan, & Goncy, 2018) to assess the frequency of
problem behaviors (e.g., aggression, delinquent behavior, and sub-
stance use). Participants reported how frequently they engaged in
specific behaviors in the past 30 days using an operationally
defined 6-point frequency scale (1 � never, 2 � 1–2 times, 3 �
3–5 times, 4 � 6–9 times, 5 � 10–19 times, 6 � 20 or more
times). The PBFS-AR assesses three forms of aggression (in-
person physical, in-person relational, and cyber), two forms of
victimization (in-person and cyber), substance use, and delinquent
behavior. This scoring is based on the study by Farrell, Thompson,
et al. (2018), who found support for seven factors based on ordered
categorical confirmatory factor analyses of data from a large,
predominantly African American sample of middle school stu-
dents. This seven-factor model fit the data well and demonstrated
strong measurement invariance across groups that differed on
gender and grade. Previous studies have found support for the
validity of the PBFS-AR based on its pattern of correlations with
teacher ratings of adolescents’ behavior and self-report measures
of relevant constructs (Farrell, Sullivan, Goncy, & Le, 2016) and
with school office discipline referrals (Farrell, Thompson, et al.,
2018).

The present study created latent variables based on items from
the PBFS-AR physical aggression (five items; e.g., “Hit or slapped
someone”), delinquent behavior (six items; e.g., “Taken something
from a store without paying for it [shoplifted]”), and substance use
(nine items; e.g., “Use marijuana [pot, hash, reefer, K2]”) scales.
Our analyses treated the items as ordered categorical variables
using weighted least squares mean and variance adjusted estima-
tors. Although PBFS-AR items are rated on a 6-point scale, very
few participants (i.e., 1.2% or less) endorsed higher frequency
categories. Because such low frequencies create problems for the
weighted least squares mean and variance adjusted estimator, we
recoded all items into four categories by combining the three
highest categories. The three-factor model fit the data well,
�2(116) � 435.73, RMSEA � .03, CFI � .98, TLI � .98, and
improved upon the fit of the one factor model based on the
RMSEA, CFI, and TLI for both boys and girls, ��2 � 174.33 and
220.26, ps � .001, �RMSEA � �.03 and �.04, �CFI � .07 and
.07, �TLI � .08 and .08, respectively. We therefore used the
three-factor solution.

Analysis Plan

We conducted all analyses using Mplus Version 8.0 and used
full information maximum likelihood estimation to address miss-
ing data. We examined six models to determine both the total and
the unique relations between the three “exposure variables” (non-
violent life stressors, physical victimization, and witnessing vio-
lence), and the six “adjustment variables” (trauma-related distress
and problem behaviors). All models included the composite indi-
cators representing nonviolent life stressors, physical victimiza-
tion, witnessing violence, and violence exposure, the three latent
variables representing the trauma-related distress factors, the three
latent variables representing the problem behavior factors, and
covariates including dummy-coded variables representing inter-

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512 THOMPSON, COLEMAN, O’CONNOR, FARRELL, AND SULLIVAN

vention status (coded 0 if the intervention was not being imple-
mented during the year the student completed the measures),
Latino/a ethnicity, gender based on school records, and grade.

The six models were distinct, but statistically equivalent, in that
they included either path coefficients or covariances among all of
the manifest and latent variables. Comparisons of the R2 values
from these models enabled us to determine the variance in each
adjustment variable accounted for by each of the exposure vari-
ables alone, their unique association after controlling for other
exposure variables, and the total variance accounted for by the
various combinations of variables. Model 1 focused on relations
between the covariates and adjustment by regressing each of the
six adjustment variables on the covariates, but modeling all other
relations among the variables with covariances. In addition to the
covariates, the remaining models regressed the six adjustment
variables on nonviolent life stressors (Model 2), physical victim-
ization (Model 3), witnessing violence (Model 4), physical vic-
timization and witnessing violence (Model 5), and physical vic-
timization, witnessing violence, and nonviolent life stressors
(Model 6). We examined the consistency of effects across gender
within the context of multiple group models that used a Wald test
to compare parameter estimates for boys and girls. We evaluated
the adequacy of our sample size based on the standard error
estimates obtained in our final model and p � .05. This indicated
that we had a sufficiently large sample to detect coefficients with
absolute values as small as .09 for correlations, .09 for standard-
ized factor loadings, .07 for path coefficients, and .11 for differ-
ences between path coefficients.

Results

Descriptive Statistics

Correlations among the scales representing nonviolent life stres-
sors, violence exposure, and the latent variables representing
trauma-related distress and the problem behavior constructs are
reported in Table 1. As expected, witnessing violence and physical
victimization were highly correlated (r � .66), and both were
moderately to highly correlated with nonviolent life stressors (rs �
.50 and .44, respectively). The three trauma-related distress factors

were highly intercorrelated (rs � .78 to .92), as were the three
problem behaviors (rs � .61 to .80). There were also small-to-
moderate correlations between the trauma-related distress and
problem behavior factors (rs � .20 to .33). We found support for
Hypothesis 1, such that nonviolent life stressors were moderately
to highly correlated with adolescents’ trauma-related distress (rs �
.49 to .53) and with problem behaviors (rs � .37 to .48). Physical
victimization and witnessing violence were each moderately cor-
related with trauma-related distress (rs � .21 to .31) and moder-
ately to highly correlated with adolescents’ problem behaviors
(rs � .30 to .47). We found partial support for Hypothesis 2. That
is, the trauma-related distress factors were more highly correlated with
nonviolent life stressors than with either type of violence exposure
(rdiff � .20 to .28, ps � .001). The three problem behavior factors
were also more highly correlated with nonviolent life stressors than
with physical victimization (rdiff � .07 to .10, ps � .001), but there
was no difference in the strength of correlations with nonviolent life
stressors than those with witnessing violence (ps .56).

Table 1 also reports d coefficients representing mean differences
across gender. There were small differences in frequencies of
violence exposure and nonviolent life stressors, such that boys
reported significantly higher frequencies of both witnessing vio-
lence and physical victimization (ds � .11), but lower levels of
nonviolent life stressors (d � �.12). Boys reported moderately
lower levels of trauma-related distress compared with girls
(ds � �.42 to �.49). In contrast, there were no gender differences
in reported frequencies of the three problem behaviors.

Relations With Exposure to Violence and Nonviolent
Life Stressors

The six statistically equivalent models fit the data well,
�2(1257) � 3666.98, RMSEA � .03, CFI � .95, TLI � .95.
Within Model 1, the demographic covariates accounted for a
significant proportion of the variance in all latent variables except
delinquent behavior, R2s � .04 to .05 (Table 2). These primarily
reflected associations with gender and ethnicity. In addition, grade
was related to substance use but not related to the other adjustment
variables. Intervention status was not related to any of the adjust-
ment variables. The three models that entered each exposure

Table 1
Correlations and Mean Differences Among Nonviolent Life Stressors, Exposure to Violence, Adolescents’ Trauma-Related Distress,
and Problem Behaviors

Variables
Nonviolent

life stressors
Witnessing

violence
Physical

victimization Re-experiencing Avoidance Hyperarousal
Physical

aggression
Delinquent
behavior

Substance
use

Nonviolent life stressors —
Witnessing violence .50�� —
Physical victimization .44�� .66�� —
Reexperiencing .51�� .31�� .27�� —
Avoidance .53�� .28�� .28�� .92�� —
Hyperarousal .49�� .24�� .21�� .78�� .85�� —
Physical aggression .48�� .47�� .38�� .33�� .33�� .32�� —
Delinquent behavior .42�� .44�� .35�� .31�� .31�� .23�� .79�� —
Substance use .37�� .36�� .30�� .31�� .30�� .20�� .61�� .80�� —
d coefficients

Boys versus girls �.12�� .11� .11�� .45�� .49�� .42�� .10 .19 �.12

Note. N � 2,653.
� p � .01. �� p � .001.

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513LIFE STRESSORS AND ADJUSTMENT

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514 THOMPSON, COLEMAN, O’CONNOR, FARRELL, AND SULLIVAN

variable, without controlling for the other exposure variables,
found that all six adjustment variables were significantly related to
nonviolent life stressors (Model 2: �s � .35 to .52), physical
victimization (Model 3: �s � .24 to .41), and witnessing violence
(Model 4: �s � .26 to .48; Table 2 and Figure 1). Within Model
5, which included both violence exposure variables in the regres-
sion model, each type of violence exposure remained significantly

related to trauma-related distress and the problem behaviors, but
there were some differences in the strength of these associations.
In particular, witnessing violence was more highly associated with
all three problem behaviors (�diff � .18 to .22, ps � .001). In
contrast, the two types of violence exposure did not significantly
differ in their strength of association with the three trauma-related
distress factors (all ps .17).

Figure 1. Standardized regression coefficients with 95% confidence intervals for models regressing trauma-
related distress and problem behaviors on (a) nonviolent life stressors, (b) physical victimization and (c)
witnessing violence. Figure shows coefficients when variable was by itself, and the decrease as additional
variables are added to the equation.

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in
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ed
br

oa
dl

515LIFE STRESSORS AND ADJUSTMENT

We found support for Hypothesis 3, which stated that nonviolent
life stressors would account for a unique proportion of variance in
adjustment even after controlling for both types of violence expo-
sure. This was evaluated in Model 6, which regressed the six
adjustment variables on nonviolent life stressors and both types of
violence exposure. Within this model, nonviolent life stressors
remained significantly related to the three trauma-related distress
factors (�s � .44 to .48, ps � .001), with values only slightly
lower than those found in Model 2, which did not include the two
violence exposure variables in the regression equations (��s � .02
to .06). Nonviolent stressors also remained significantly related to
the three problem behavior factors (�s � .20 to .28, ps � .001),
though including the two violence exposure variables resulted in a
substantial reduction in these coefficients compared with Model 2
(��s � .15 to .19; see Model 2 vs. Model 6 in Figure 1a).

Model 6 provided mixed support for Hypothesis 4. The two
violence exposure variables accounted for a significant percentage
of the variance in two of the three trauma-related distress factors
(�R2s � .01, p � .001), and in all three of the problem behavior
factors (�R2s � .06 to .09, p � .001). In contrast, the two violence
exposure variables were no longer significantly related to hyper-
arousal after controlling for nonviolent life stressors. As we had
hypothesized, controlling for nonviolent life stressors reduced the
strength of the associations between violence exposure and adjust-
ment, though the pattern differed for trauma-related distress and
problem behaviors. This is reflected in Figures 1b and 1c, which
depict the reduction in the standardized regression coefficients for
the three trauma-related distress factors that resulted from includ-
ing nonviolent life stressors in the model (see Model 6 vs. Model
5 in Table 2 and Figures 1b and 1c). Attenuated effects were
particularly evident for associations with the three trauma-related
distress factors. In contrast, controlling for nonviolent life stressors
had a less dramatic impact on path coefficients representing asso-
ciations between the two types of violence exposure and the three
problem behavior factors.

We addressed Hypothesis 5 by conducting a Wald test to de-
termine if relations between the three exposure variables and six
adjustment variables differed by gender. The overall test was not
significant, Wald �2(18) � 18.70, p � .41, indicating that effects
did not significantly differ for female and male adolescents.

Discussion

Few previous studies that evaluated the impact of violence
exposure on adjustment have accounted for the influence of con-
current nonviolent life stressors experienced by adolescents. To
address this limitation, we investigated relations between early
adolescents’ nonviolent life stressors, two types of violence expo-
sure, trauma-related distress symptoms, and problem behaviors.
We found full support for Hypotheses 1 and 3. The three violence
and nonviolence exposure variables were each significantly corre-
lated with the six adjustment variables, and adolescents’ reported
frequencies of nonviolent life stressors were uniquely associated
with the adjustment variables, after controlling for violence expo-
sure and other demographic covariates. These findings are consis-
tent with ecological theories, such as the cultural ecological model
(García Coll et al., 1996) and the risk and resilience model of
developmental psychopathology (Compas & Andreotti, 2013),
which emphasize the importance of examining familial, social, and

structural risk factors in predicting adolescent adjustment within
urban, underresourced communities.

Consistent with Hypothesis 2, trauma-related distress was more
highly correlated with nonviolent life stressors than with either
type of exposure to violence. Physical aggression, delinquency,
and substance use were more highly correlated with nonviolent life
stressors than with physical victimization (but not compared with
witnessing violence). Research is clear that exposure to violence is
harmful during adolescence and should not be ignored (for a
review, see Fowler et al., 2009). However, our findings illustrated
the unique role of nonviolent life stressors on urban adolescents’
adjustment and that they exerted an influence above and beyond
that of violence exposure. Moreover, we found that, after control-
ling for nonviolent life stressors, the two types of violence expo-
sure accounted for little to no variance in trauma-related distress
and less than half of the variance originally explained by each
problem behavior. These findings support the notion that exposure
to violence may be indicative of a larger constellation of detri-
mental experiences faced by minority youth living within urban
contexts (Zimmerman & Posick, 2016). An alternative explanation
for our findings is that youth feel less able to control nonviolent
life stressors, compared with direct victimization. For example,
Farrell and colleagues’ (2007) qualitative work identified power-
lessness as one mechanism to explain relations between nonviolent
stressors and urban adolescents’ risk for emotional and behavioral
difficulties.

Our findings highlight the need to examine the impact of wit-
nessing violence and physical victimization on adjustment sepa-
rately. For Hypothesis 4, we found that, after controlling for
nonviolent life stressors, both types of violence exposure were still
significantly associated with reexperiencing symptoms and all
three forms of problem behaviors. However, contrary to our hy-
pothesis, after controlling for nonviolent life stressors, witnessing
violence was no longer associated with avoidance, and neither type
of violence exposure remained significantly associated with hy-
perarousal. Witnessing violence had a stronger association with the
three problem behaviors than did physical victimization. This
finding is particularly surprising, given previous work that has
found that effects on externalizing behaviors are stronger for
victimization than for witnessing violence (Fowler et al., 2009).
However, one study found that urban adolescents were less likely
to talk to their parents about violence they witnessed versus
experienced themselves, which in turn, put them at higher risk for
maladjustment (Kliewer & Lepore, 2015). This suggests that ad-
olescents may be less likely to effectively process their experi-
ences with witnessing violence, resulting in more behavioral dif-
ficulties. Additional work is needed to ascertain whether different
mechanisms exist between the two types of violence exposure and
adjustment.

We also examined possible gender differences across these
relations (Hypothesis 5). Although boys reported higher frequen-
cies in violence exposure and girls reported higher frequencies in
nonviolent life stressors, gender did not moderate the impact of
violence exposure or nonviolent life stressors on early adolescents’
frequencies of trauma-related distress, aggression, delinquent be-
havior, or substance use. This is consistent with one of the only
known studies to examine gender differences between nonviolent
life stressors and adolescent adjustment (Liu et al., 2016). Our
results most likely reflect our focus on a predominately African

T
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.

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d

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to

be
di

ss
em

in
at

ed
br

oa
dl

516 THOMPSON, COLEMAN, O’CONNOR, FARRELL, AND SULLIVAN

American sample of youth living in urban, socioeconomically
disadvantaged contexts with high rates of community violence.

Research Implications

Our findings support the notion that adolescents’ exposure to
nonviolent life stressors is uniquely related to their emotional and
behavioral functioning. Findings also highlight the need to control
for nonviolent life stressors when examining the unique impact of
violence exposure on adjustment. Accounting for the broader
social ecology of adolescents’ environment should be an integral
part of community violence research, especially among minority
youth living in urban, underresourced communities (Allison et al.,
1999; Evans, 2004). Additional work is needed, however, to fur-
ther parse out the differences between how nonviolent life stres-
sors at the individual level relate to constructs measured at the
neighborhood or community levels, such as poverty and employ-
ment rates. Investigating these differing effects has important
implications for the appropriate level of intervention (e.g., indi-
vidual, family, school, and community). Future work should also
examine potential moderators and mediators of our findings. For
example, it is unknown what mechanisms may explain why non-
violent life stressors are more closely associated with adolescents’
emotional and behavioral functioning, compared with their expe-
riences of physical victimization. In addition, future studies should
explore mitigating factors that protect individuals exposed to non-
violent life stressors from the risk of trauma-related distress and
problem behaviors. Potential moderators may include support from
a caring adult, beliefs about problem behaviors, and neighborhood
cohesion.

Limitations

Several limitations within the current study warrant discussion.
The study sampled predominantly African American, middle-
school students from areas relatively high in crime and poverty.
Our findings may not generalize to youth from other ethnic or
racial groups or those living in different socioecological contexts.
The remaining portion of the sample represented a fairly diverse
group with no more than 10% endorsing any other race. As such,
race could not be tested as a potential moderator. In addition, the
focus on early adolescents indicates that similar results may not be
found in studies sampling younger or older youth. Future studies
should examine potential differences across racial and ethnic
groups, as well as age groups, in the relations between violent and
nonviolent stressors and adolescent adjustment.

The present study used a broad measure of nonviolent life
stressors with a total score representing the frequencies of all
events. Individuals may experience events across various settings
including family or community domains. Adolescents may also
experience daily stressors (e.g., not spending enough time with
their parents) or more severe stressors (e.g., losing a loved one)
that may differ in their effects on adjustment. Studies have found
support for differential effects on substance use and delinquent
behavior, dependent upon the context in which the stress was
measured (e.g., family vs. school vs. individual stressors; Booker,
Gallaher, Unger, Ritt-Olson, & Johnson, 2004; Booth & Anthony,
2015). Future studies should consider examining the differential
relations between various types of nonviolent stressful events and
adolescent adjustment.

This study is also limited by its cross-sectional design. This
prevents us from drawing conclusions about the causal relations
between violent and nonviolent life stressors as they relate to
adolescents’ trauma-related distress and problem behaviors. For
example, there may be other constructs that cause the variables
used in the current study to be positively related. There is some
evidence to support both longitudinal and reciprocal relations
between violence exposure and aggressive behavior in adolescents
(Esposito, Bacchini, Eisenberg, & Affuso, 2017). It is not known,
however, whether there are reciprocal relations between nonvio-
lent life stressors and problem behaviors or trauma-related distress.

Clinical Implications

The current findings have important implications for screening
purposes. The strong association between nonviolent life stressors
and trauma-related distress, even after controlling for violence
exposure, is particularly salient, given the trauma criterion for
diagnosing PTSD. To meet criteria for PSTD, an individual must
be exposed to a specific traumatic event characterized by threat-
ened or actual death, harm, or sexual violence (American Psychi-
atric Association, 2013). Our findings suggest that mental health
providers may be missing important information related to adoles-
cents’ trauma symptomatology if they fail to inquire about trauma-
related distress when adolescents deny exposure to violent and
life-threatening events.

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Received March 26, 2019
Revision received August 24, 2019

Accepted September 26, 2019 �

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519LIFE STRESSORS AND ADJUSTMENT

http://dx.doi.org/10.1037/12057-001

http://dx.doi.org/10.2105/AJPH.2012.300931

http://dx.doi.org/10.2105/AJPH.2015.302920

Exposure to Violence and Nonviolent Life Stressors and Their Relations to Trauma-Related Distres …

Nonviolent Life Stressors

Physical Victimization Versus Witnessing Violence

Gender Differences

Current Study

Method

Participants

Procedure

Measures

Nonviolent life stressors

Violence exposure

Trauma-related distress

Problem behaviors

Analysis Plan

Results

Descriptive Statistics

Relations With Exposure to Violence and Nonviolent Life Stressors

Discussion

Research Implications

Limitations

Clinical Implications

References

Trauma and Triggers: Students’ Perspectives on
Enhancing the Classroom Experiences at an

Alternative Residential Treatment-Based School
Angelique Gabrielle Day, Beverly Baroni, Cheryl Somers, Jenna Shier, Meredith Zammit,

Shantel Crosby, Jina Yoon, Megan Pennefather, and Jun Sung Hong

Youths in residential treatment (RT) are often burdened with histories of trauma exposure
and experience a multitude of unique challenges for both daily functioning and develop-
mental trajectories. Youths spend a large portion of their day in school; these educational
experiences affect long-term well-being. This study uses qualitative focus group methodol-
ogy to better understand the school experiences of youths placed in an RT educational
environment. The sample consisted of 45 female residents placed in out-of-home care due
to a child welfare or delinquency petition. Several key themes emerged that illustrate youth per-
ceptions of the climate of RT, how strict discipline schools can affect mood, and what factors
promote or hinder school engagement and disengagement. These themes included issues related
to interactions with residential and school staff, teachers, classmates, and other staff; their own
inabilities to interpersonally cope; and mismatches between their educational needs and services
provided. The article concludes with a discussion of implications for policy and practice.

KEYWORDS: education well-being; foster care; juvenile delinquency; youth voice

Youths in residential treatment (RT) facili-
ties are often burdened with trauma
histories and experience academic, behav-

ioral, and emotional problems (Abram et al., 2004;
Ford, Chapman, Connor, & Cruise, 2012), which
limit opportunities for a healthy, successful future
(Wolpow, Johnson, Hertel, & Kincaid, 2009). The
number of children and adolescents admitted to
RT programs has increased significantly since 1980
(Doerfler, Toscano, Volungis, & Steingard, 2004;
Zelechoski et al., 2013). Zelechoski et al. (2013)
reported that 65,949 youths were in residential care in
2003; 75 percent were between the ages of 13 and 17
(Warner & Pottick, 2003), and 66 percent of youths
in RT programs are female (Briggs et al., 2012).
Trauma exposure among adolescents placed in RT
programs ranges from 50 percent to over 70 percent
(Bettmann, Lundahl,Wright, Jasperson, &McRoberts,
2011; Warner & Pottick, 2003; Zelechoski et al.,
2013). RT programs offer services that include
drug and alcohol treatment, confidence building,
military-style discipline, and psychological counseling
for a variety of addiction, behavioral, and emotional
problems. Many of these programs are intended to
provide a less restrictive alternative to incarceration or

hospitalization (Federal Trade Commission, 2008).
Adolescents who are placed in an RT facility typically
have experienced a wide range of psychiatric disor-
ders, particularly traumatic stress. Traumatic stress can
stem from physical, sexual, or emotional abuse;
neglect; accidents; exposure to domestic and
community violence; natural disasters; and other
adverse events (Griffin et al., 2011). Studies sug-
gest that early traumatic stress is linked to future
psychiatric care, poor mental and physical health
throughout life, low educational attainment, home-
lessness, early pregnancy, poverty, unemployment,
reliance on public assistance, impulsivity, dissociation,
aggressive behavior, and relationship difficulties
(Price, Higa-McMillan, Kim, & Frueh, 2013;
Zelechoski et al., 2013).

Educational opportunities vary greatly in RT
settings, from off-campus, public school partner-
ships in the local community to educational ser-
vices offered on-site at the RT facility. Although
traumatic experiences can affect students in public
school environments (Overstreet & Mathews, 2011;
Smithgall, Cusick, & Griffin, 2013; Vidourek, King, &
Merianos, 2016), youths in RT school settings may
have unique trauma-related issues (Crosby, Day,

doi: 10.1093/cs/cdx018 © 2017 National Association of Social Workers 227Downloaded from https://academic.oup.com/cs/article-abstract/39/4/227/4100182/Trauma-and-Triggers-Students-Perspectives-on
by Adam Ellsworth, Adam Ellsworth
on 29 September 2017

Baroni, & Somers, 2015; Day et al., 2015). This arti-
cle is restricted to understanding the educational ex-
periences of RT youths in educational programs
offered on-site at an RT facility. Effective schooling
for foster and other adjudicated youths can lead to
more positive outcomes (Mathur & Schoenfeld,
2010); however, traumatic stressmay affect adolescents’
perceptions, interactions, and learning (Hoagwood &
Cunningham, 1992). The current study was designed
to address the paucity of research that has been con-
ducted to explore the role of RT schools in the heal-
ing and treatment of traumatized, court-involved
youths who are placed in RT programs.

At school, students are expected to concentrate
on their schoolwork, actively listen, participate in
class discussions, and respond to corrections and dis-
cipline (Wolpow et al., 2009). For adolescents in
an RT facility, school expectations may be compro-
mised by trauma, which can undermine cognitive
abilities and skills acquisition key to school success
(Smithgall et al., 2013; Snowman & McCown,
2012). Trauma exposure may also lead to social and
behavioral difficulties in the classroom; students
who have experienced traumatic events exhibit
more externalizing behaviors in school, such as
aggressiveness, impulsivity, and fighting (Shonk &
Cicchetti, 2001; Smithgall et al., 2013). As a result,
these behavioral difficulties often lead to harsh
school discipline (for example, suspension or expul-
sion), involvement in the juvenile justice system, or
school dropout (Baroni, Day, Somers, Crosby, &
Pennefather, 2016; Smithgall et al., 2013).

RTs must include an emphasis on academics in
addition to custodial care. Successful implementa-
tion of quality academic programs in RT facilities
is complicated by the characteristics of struggling
youths and the design of RT facilities. Indeed,
court-involved youths bring skill deficits, severe
behavioral issues, and mental health challenges
into the classroom; moreover, RT facilities are
held accountable to security and safety considera-
tions that largely supersede any educational efforts
(Mathur & Schoenfeld, 2010). Specific, attainable,
program-based changes with buy-in from students
have the potential to make a genuine difference in
the educational outcomes of court-involved youths.
From a social–emotional perspective, effective RT
schools must increase school engagement by creating
a climate that promotes (a) positive teacher–student
relationships, (b) positive peer relationships, (c) a
personal sense of self, and (d) an ability to manage

emotions (Becker & Luthar, 2002). Identifying
interpersonal cognitive problem solving as part of
soft skill development, including social competence,
is often a goal for education-based RT programs to
address student engagement and disengagement
(Small & Schinike, 1983).

To address the gap in understanding how schools
in RT facilities meet the educational needs of court-
involved youths, this study seeks to apply phenome-
nology (Palmer, Larkin, de Visser, & Fadden, 2010)
to explore traumatized RT students’ often hidden
perspectives and lived experiences in their education
environment. Recent research has illustrated the con-
nection between students’ moods and emotional
states and their ability to engage effectively in the
classroom (Crosby et al., 2015; West, Day, Somers, &
Baroni, 2014; Wolpow et al., 2009). In the current
study, we explore the following research question:
What factors trigger negative moods (school dis-
engagement) or enhance positive moods (school
engagement) among court-involved youths enrolled
in an RT facility school, and how do students per-
ceive how RT staff, teachers, and other school offi-
cials respond to behaviors manifested in the academic
setting?

METHOD
Description of Curriculum and Intervention
The school where the study took place implemented
a modified version of the curriculum described
in The Heart of Teaching and Learning: Compassion,
Resiliency, and Academic Success (HTL) as the pri-
mary intervention (Wolpow et al., 2009). HTL is
an integrated, manualized curriculum founded on
research, theory, and clinical practice and is grounded
in ecological and attachment theories applied using
psychoeducational, cognitive–behavioral, and rela-
tional approaches. Additional information on the cur-
riculum intervention is described in Day et al. (2015).

In addition to the curriculum intervention, the
school implemented the Monarch Room (MR) as an
alternative to traditional school discipline practices, to
increase classroom seat time and maximize school
engagement. When students become too escalated to
remain in the classroom setting, they are sent to the
MR for redirection and de-escalation or choose to go
to the MR on their own. Once students are in the
MR, a trauma-trained paraprofessional helps them de-
escalate, refocus, and return to class. Various interven-
tion strategies are used in the MR, including problem
solving, talk therapy, and sensorimotor activities. The

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MR is available throughout the school day, with each
specific MR episode lasting approximately 10 min-
utes. Additional details describing the MR interven-
tion are published in Baroni et al. (2016).

Participants and Study Site
Participants included 45 randomly selected female
students currently or previously involved in juve-
nile court. All study participants were enrolled
between September 2013 and June 2014 in a pub-
lic, chartered, strict discipline academy colocated at
a large child welfare placement agency for girls in a
midwestern state. Eighty-six percent were current
residents in the facility, and 14 percent had re-
turned to the community but continued attending
the school. Participants were ages 13 to 19 years.
Similar to the rates of foster care youths in the
Midwest, over 60 percent of the study partici-
pants were African American (U.S. Department
of Health and Human Services, Administration for
Children and Families, 2012). The racial and eth-
nic composition and age of the study participants
is representative of the school enrollment as a
whole and is consistent with the national preva-
lence rates of juvenile justice–involved youths of
color who experience placement in RT facilities
(Office of Juvenile Justice and Delinquency Preven-
tion, 2013) (see Table 1). Individual-level demographic
data (student race and age) were obtained from the
school’s administrative database and de-identified
before they were provided to the research team
for analysis.

The study site is a school that provides educa-
tional services exclusively to female students who
are or have been in an RT facility, and all have
experienced exposure to child abuse and neglect.
Due to these traumatic histories, the majority of
enrolled students are three to four years below
standard grade level. Also, average length of stay in
the RT facility is four to six months. Despite these
limitations, the school aims to assist these students
by adhering to a school discipline system that
focuses primarily on treatment. The goal is to pro-
vide an effective social–emotional learning envi-
ronment to teach students emotion self-regulation
and positive social skills, including how to make
more responsible choices.

Procedures and Data Collection
The study was approved by the institutional review
board atWayne State University. Information about
the study was distributed to participants and their
legal guardians during school registration. An assumed
consent process was used, whereby students, their
caregivers, or both could opt out of participation
at any time. The phenomenological approach
provides the opportunity to uncover hidden pro-
cesses and phenomena (Palmer et al., 2010), which
is critical to understanding the unique needs and
experiences of this vulnerable population. Six
focus groups were conducted by independent re-
searchers and were held at the school building
where the intervention was targeted. Although not
commonly used in phenomenology, focus group

Table 1: Characteristics of Student Focus Group Participants versus Total School
Population

Characteristic

Study Participants
(n = 45)

Total School Population
(N = 124)

n % n %

Race or ethnicity
White 3 7.0 26 21.0
African American 29 64.0 66 53.2
Other 4 9.0 8 6.4
Multiracial 9 20.0 24 19.4

Age (years)
13 1 2.0 8 6.0
14 2 4.5 17 14.0
15 8 18.0 21 17.0
16 22 49.0 43 35.0
17 10 22.0 28 23.0
18 2 4.5 6 5.0
19 0 0.0 1 <1

Note: For race or ethnicity, χ2(5) = 5.836, p = .32; for age, χ2(6) = 4.538, p = .60.

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methodology was selected because the data can
uncover specific shared lived experiences; elicit new
perspectives as group members confirm or deny
each other’s experiences; and provide rich, inter-
group interpretation (Bradbury-Jones, Sambrook, &
Irvine, 2009). Each focus group participant was
assigned a number; these ID numbers and their
corresponding responses were documented in the
transcripts to ensure that the researchers could offer
an account of each individual participant’s claims
and concerns and capture commonalities of experi-
ence to account for context. Prevalence rates of
identified themes were captured by frequency and
participant. In addition, middle and high school
girls participated in separate focus groups to ensure
that younger student voices were not compro-
mised. Students were asked five open-ended ques-
tions: (1) If your mood changes throughout the
day, what makes it change? (2) When I am having
a bad moment at school, what helps is . . . ; (3)
When I am having a bad moment at school, what
makes it worse is . . . ; (4) How do your teachers
and the school staff react to you when you are having
a bad moment at school? and (5) If you were princi-
pal for a day, what advice would you give to teachers
to work with students like yourself ?

Three focus groups each were held in Septem-
ber 2013 and June 2014. Each group consisted of
six to eight students and lasted for approximately
one hour. Students were randomly selected to par-
ticipate in focus groups and were informed that
participation was strictly voluntary. All selected
participants agreed to and participated in the focus
groups. Two participants who preferred not to
verbalize their comments during the focus groups
were provided blank sheets of paper and were asked
to share their responses in writing. These written
comments were collected and added to the end of
the focus group transcript before analysis was con-
ducted. Focus groups were audio-recorded and tran-
scribed verbatim.

Data Analysis
Transcripts were analyzed for themes using a criti-
cal hermeneutics process (a line-by-line coding of
the experiential claims, perspectives, and under-
standings of each participant) (Kinsella, 2006).
Three researchers coded the transcripts indepen-
dently; these researchers then came together as a
group using constant comparison methods to
explore commonalities, differences, and main ideas

derived from the experiential material (Dye, Schatz,
Rosenberg, & Coleman, 2000). Final themes and
subthemes were derived through group dialogue,
which developed a more interpretive account of the
data. Focus group transcripts were uploaded into
NVivo (version 10) (QSR International, 2010), and
reports were run to assess prevalence rates by theme
across all transcripts.

FINDINGS
Seven major themes and subthemes, along with
their prevalence rates, are all displayed in Table 2.

Theme 1: ClassroomDynamics
Students identified several classroom dynamics
that impeded learning progress: boredom, non-
challenging assignments, constant classroom dis-
ruptions, and teachers’ inability to respond timely
to questions about the curriculum, as reflected in
the following quotes:

I think school is too easy, like, there is no chal-
lenge. I think that is why you get bored so
quick, ’cause in real school you have challenges,
this school they just give you kindergarten
work.

***

Deal with they [student] attitudes even if you
feel like they being wild and obnoxious… you
have 10 or 15 other students in the class that
have attitudes and you hear them say, oh my
gosh, can you go head on with the, uh,
lesson ’cause they feel like they really tryin’ to
learn work.

***
I had a test to do, and I was, like, I need help
on this, kept asking them. Five minutes go by
and I asked her and she assumes I’m being sar-
castic about the help. But I asked her for help,
then when the test came around and I’m like, I
don’t know this stuff, she want to get mad at
me ’cause. . . I asked you five days ago to help
me, now you sitting here cutting me up.

Theme 2: Family Issues External to the
School Environment Affect Learning
Students described how personal family issues
affected classroom learning. Specifically, students
described their family environments prior to place-
ment in residential treatment.

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Table 2: Major Themes of the Study Findings

Theme

Total Student
References

(n)

Focus Group’s
Theme Appeared

(n)

Unduplicated
Students Refs

(n)

1. Classroom dynamics
Boredom: “I hate being bored. I get real irritated and I’ll just go
off on a teacher, I probably get sent back to the building.”

33 3 14

Classroom disruptions: “Everybody tryna do they work . . . ; it’s
people talking, and then the teachers gotta stop and they lose
focus on what’s going on.”

38 4 24

Lack of challenging work: “In real school you have challenges;
this school . . . , kindergarten work.”

19 3 9

Slow response rates on teacher feedback and assistance with
classwork: “I was, like, I need help on this, kept asking them.
Five minutes go by and I asked her, and she gonna say I’m
being sarcastic about the help.”

56 6 28

Total 146 75
2. Family issues external to school 27 6 24

“You dealin’ with so much that’s goin’ on at home. Your family
don’t think about you when you be here. They (teachers)
don’t think about how it’s goin’ to affect you.”

Total 27 24
3. Interpersonal behaviors and challenges

Avoidance: “I just ignore ’em. I leave it alone because it’s not
worth it.”

29 6 23

Peer conflict: “If you hit me then I’m gonna hit back, but it’s
gonna be ten times harder ’cause when I get mad, I just blank
out, I just see red and black.”

50 6 31

Problem-solving skills: “I be trying to problem solve like, I think
before I act now, you know, rather than just hit before I think.”

32 5 23

Thinking about positive things, future: “So I think to myself,
you’re about home soon, you about to see your dad again, see
your mom again, you have to do a lot of stuff—you about to
let that ruin everything?”

24 3 17

Verbal reactions: “I get real angry and I say bad things, but I wouldn’t
wanna fight. ’Cause I’mnot a fighter, but I just talk stuff.”

50 4 28

Total 185 122
4. Recommendations to improve school climate

Extracurriculars: “I think y’all should come up with more
activities, like sports after school.”

21 2 15

Food: “We got processed food. This food don’t ever get cooked;
it’s just warmed up.”

52 5 18

Living arrangements: “They’re grown but they still don’t clean
up after they self. It be vicious everywhere, the floor, in the
kitchen. It’s just nasty.”

19 3 12

Monarch Room: “I think we should have more peer counseling. Say
for instance, I’m in theMonarch Room and I ask, can they call
one of my peers outta class so I can talk to this person because I
can’t talk to the staff about what I really wanna talk about.”

54 5 26

Total 146 71
5. Peers

Creating drama: “It’s so much drama, like all you hear all day is
gossiping.”

73 5 18

Disrespectful actions: “People put themselves in the category of a
young lady, but that’s not what young ladies do—act catty all
the time, cuss all the time.”

105 6 35

(Continued)

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Every day the things besides just school affects
them every day, and that can also have a drastic
change ’cause it can take over their mind, and
when they are actually in the classroom and
they are exacted to do one thing, they’ve got a
million other things running through their
mind and it’s hard for them, it is.

***
For one, my momma call me bitches and hoes
all day every day at home; I get that enough
from my momma, so to come in here and get
locked up with a bunch of females I don’t
know calling out my name and I don’t even
respect my sister; well, I respect them, I don’t
get along with them.

Theme 3: Interpersonal Behaviors and
Challenges
Six interpersonal dynamics impeded or facilitated class-
room learning: peer conflict, perceived mistreatment,

avoidance, desire for problem-solving skills, positive
relationships, and understanding the benefits of educa-
tional attainment. Interpersonal factors that impeded
classroom learning were conflicts with peers and per-
ceived mistreatment by residential facility staff and
school faculty. Avoidance both inhibited and pro-
moted positive classroom learning. These behaviors
included avoiding physical and verbal altercations
when these situations presented themselves, as well as
choosing to avoid friendships and connections with
teachers and residential treatment staff. Interpersonal
strategies that fostered a positive learning environment
were the desire to learn problem-solving skills, develop
relationships with “positive” people, and understand
connections between educational attainment and
employment opportunities.

You come in an environment or on a campus
with lots of kids that have problems or issues
that they can’t solve, and they need someone

Table 2: Major Themes of the Study Findings (Continued)

Theme

Total Student
References

(n)

Focus Group’s
Theme Appeared

(n)

Unduplicated
Students Refs

(n)

Positive influences: “I hang around mostly leaders in this school,
positive people, and that just helps me.”

17 4 18

Total 195 71
6. Residential treatment staff

Helping behaviors: “They give you good advice and make you
feel up when you down.”

35 6 27

Lack of training, unprofessional behavior: “Half of these staffs be
sitting here talking about other students; students be going
back and tell students what the staff said.”

104 6 27

Overly restrictive behaviors: “When you actually sit there and see
that a kid don’t do nothing but obey and just be consistent in
doing what they have to do to out they treatment, they still
being locked up. They don’t have leeway; they can’t go out to
the mall with open placements.”

93 6 29

Total 232 83
7. Teachers

Intrusive communication: “They don’t care if you havin’ a bad
day, they just wanna keep askin’ you what’s wrong—I don’t
wanna talk about it.”

73 6 28

Negative behaviors: “The teacher don’t be even trying to be teaching;
they just be letting the kids do whatever they wanna do.”

82 6 33

Positive behaviors: “She always support me, like when she would
see that I’m down, she come see me if I didn’t even ask her.
Like, she helped me if I needed any question or any extra help
in our classes.”

42 5 25

Supportive communication: “Every time she see me cry she give me
a hug and ask me do I need to go somewhere to talk about it.”

26 6 24

Total 223 110

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to talk to. It be kinda frustrating for a minute
and then it’s like, people blow it out of propor-
tion to keep nagging or keep you frustrated
over the same thing.

***
What helps me is probably being around positive
people, ’cause I try to hang around positive
people ’cause I’ve had so many negative things
in my life that I don’t need any more negativity.

Theme 4: Recommendations for Improving
School Climate
Students offered the following suggestions for
improving school climate and culture: access to
extracurricular activities, provision of elective
courses, tutoring opportunities, and access to high
school traditions (for example, yearbooks, dances,
field trips). Students also discussed how food can
affect their ability to learn. They were provided
with three meals a day; however, students stated
that they needed access to additional meals. Stu-
dents said they would have a more positive attitude
if they felt full.

[I think y’all should] come up with more activ-
ities, like sports after school . . . yeah, volley-
ball, basketball, I like volleyball . . . track.

***
I feel like they should have, like, parenting
classes or something, like, that will help them
get out of here when they leave here and they
can be a better parent for their child or just
know what to do, instead of be like, “Oh,
when I go home I’m gonna see my baby, then
I’m gonna leave for a couples of hours and go
get high.”

***
They say we might not be able to get yearbooks
because some of the people that’s graduating are
from residential, and I feel that’s not fair.

***
You know you be cranky if you don’t eat; I
gotta eat at least six times a day.

Theme 5: Peer Dynamics
Students described how classmates instigated “unnec-
essary drama,” such as engaging in physical and verbal
altercations and gossip. Classmates were described as
being disrespectful to one another and residential and

school staff. Still, students expressed wanting friend-
ships and positive interactions with their peers.

It’s so much drama, like [name of residential
unit] all you hear is gossiping, ’cause that’s all
girls, who they don’t like, you can’t like a per-
son when they first got there; you don’t even
know me. That’s how I feel.

***
I was close to going home and I was telling
people, yeah, I’m going home, and I was tell-
ing people this and then they start bringing
you down with them so you can stay here
longer.

Theme 6: Dynamics Involving RT Care Staff
Students described how RT staff implemented
overly restrictive rules and regulations and dis-
played unprofessional behaviors. On the other
hand, they also described how RT staff helped in
the treatment process, and perceived them as posi-
tive role models. In addition, students provided
recommendations for training of residential staff to
improve student–staff relationships.

What makes me more mad is when I’m in a sit-
uation and then every staff worker from [name
of residential unit] just come out, then they say
step out the classroom . . . they have you repeat
the same story over and over again.

***
Give them, give the kids respect; we all going
through something.

Theme 7: Dynamics with School Faculty
and Other School Staff
Last, students discussed interactions with faculty
and other school employees. Specifically, they dis-
cussed how teachers remove misbehaving students
from classrooms and how students and other school
personnel sometimes disregard their opinions. Stu-
dents also expressed concerns about how teacher
turnover might affect learning. They also discussed
how some teachers were supportive of student
interests.

Before he left, he [math teacher] was teaching us
a different thing in math, but then when another
teacher came in; she teaches it in a totally differ-
ent way than he did. So it got some of the kids

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in that class so frustrated, then we just don’t do
the work no more.

***

Please don’t disregard these kids’ opinions
because, um, you know, we some, some of [us]
are some smart kids. We some smart children.

DISCUSSION
This study found several prevalent themes related
to student social, emotional, and academic function-
ing that both promote and hinder school engage-
ment and disengagement in a residential school
environment, including classroom dynamics; exter-
nal trauma triggers; interpersonal and other factors;
and issues with peers, residential staff, and school fac-
ulty. When discussing classroom dynamics, students
reported feeling bored, explained that their work
was not challenging, and also felt that teachers did
not respond to questions efficiently. This may have
been due, in part, to the high prevalence of court-
involved students who test below their academic
grade level (Courtney, Terao, & Bost, 2004) and the
difficulty of arranging classrooms to accommodate
needs due to limited physical space and student and
staff turnover. In addition, due to high student turn-
over and lack of timely access to school records for
incoming transfers, students’ academic abilities may
be unknown. Therefore, teachers must juggle cover-
ing lessons to accommodate academically challenged
students with addressing the academic needs of those
who are more advanced. In addition, students
pointed out that teachers do not always manage stu-
dent behavior with trauma sensitivity. School faculty
need to be mindful of students’ traumatic histories
and how trauma can manifest in the academic set-
ting. This demonstrates a need for deeper trauma
training, as well as efficient methods of training new
teaching staff to get them up to speed quickly,
including the need for implementation of classroom
observations and coaching to ensure that teachers are
able to appropriately translate trauma theory into
classroom practice. Some teachers have personal
trauma histories that can be retriggered through stu-
dent interaction. Teachers with personal trauma
backgrounds need to ensure that they get therapeu-
tic interventions before entering the classroom.

Another major finding is external problems that
hinder ability to thrive. Similar to other studies
focusing on students in both public (Overstreet &
Mathews, 2011; Smithgall et al., 2013; Vidourek

et al., 2016) and RT school settings (Crosby
et al., 2015; Day et al., 2015), students reported
experiencing stress before entering the classroom
due to overwhelming socioemotional histories and
peer or familial concerns. Students may become
consumed by personal dilemmas that may prohibit
school performance and attendance, and they are
unable to focus on lessons when they are truant.
Furthermore, the girls explained that interpersonal
issues that manifest in the classroom can be distract-
ing. These classrooms are filled with students
whose emotional, psychological, and physical
needs are unmet. Therefore, it is difficult to have
students focus on education-related tasks. To pre-
pare them to better manage educational demands,
students desire better problem-solving skills to help
them cope in the classroom and understand how
those skills can translate to future environments.

Students reported that some RT facility staff have
had a strong, positive influence on school engage-
ment and socioemotional well-being. However,
students also described the negative attitudes and
behaviors of RT staff, which negatively affect stu-
dent learning and engagement in the school envi-
ronment. Moreover, they explained that when they
felt upset and disengaged in the classroom (that is,
putting their heads down and not attending to class
material), RT staff resorted to the use of punitive
measures (that is, taking away a home pass) rather
than trying to understand the reason for classroom
disengagement. RT and school staff should work
collectively to identify and implement interventions
that are consistently applied across both systems.
The restriction of access to biological parents and
siblings does little to support general health or edu-
cation well-being. These issues highlight how
cross-system dynamics can both impede and sup-
port education well-being for students in RT set-
tings. When interacting on school grounds, RT
staff need to respond to behaviors in a consistent
manner aligned with the school’s philosophy. Pre-
vious studies asserted that well-qualified, trained
RT staff members help reduce recidivism rates,
and emphasis on education in the treatment process
is the most impactful way to influence behavior
(Lowenkamp, Flores, Holsinger, Makarios, & La-
tessa, 2010; Mathur & Schoenfeld, 2010).

Several students verbalized the importance of
food in mood stabilization and school engagement.
Attention must be paid to students’ physical health
and how the amounts and the types of foods offered

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may affect student learning. For example, some stu-
dents may be struggling with blood sugar issues that
necessitate the need for more frequent, smaller meals
throughout the day. In addition, pregnant students,
who are often overrepresented in alternative schools,
may also have different nutritional needs. The three-
square-meals-per-day general state guidelines offered
by public health officials for implementation in
schools may not apply to adolescents enrolled in
residential-based, alternative school environments,
such as those attending strict discipline academies.
Challenges to implementing changes in food con-
sumption and delivery include the fact that schools
and RT facilities do not have all-day cafeterias. In
addition, students may need nutritional education
training to ensure that they make healthy food
choices for themselves (and any unborn children).

Finally, students suggested that extracurricular
activities, tutoring, access to various school tradi-
tions (that is, school yearbooks, dances, field trips),
and for pregnant and parenting students access to
parenting classes would enhance overall school experi-
ence and promote school engagement. Challenges to
the implementation of extracurriculars include the fact
that RT facility schools and other alternative high
school settings tend to have small enrollment, which
limits the resources schools have to implement after-
school programs, including the ability to hire additional
teachers needed to offer tutoring during and after
school hours. In addition, system-level policies make it
difficult to offer such opportunities to students, as com-
petitive sporting events may pose a threat to safety and
yearbook photographs can jeopardize confidentiality.
In general, RT and traditional education systems have
competing and sometimes conflicting goals; for the
RT agency, safety, confidentiality, and permanency
goals are paramount and will often supersede educa-
tional goals.

Implications for Policy and Practice
Schools serving students with trauma histories in
residential placement cannot be expected to pro-
vide mental health treatment, but should engage in
strong cross-system communication and data shar-
ing to work effectively with professionals across
the mental health, child welfare, and juvenile jus-
tice service systems. These partnerships, when effec-
tively working together for the common goal of
educational success, can assist teachers with difficulties
in the classroom more effectively, and reduce high
teacher turnover, which for this population can be a

trauma trigger in and of itself. RT facilities and partner-
ing schools that enroll high populations of residential-
placed youths should offer employee incentives that
reduce teacher and staff turnover and support self-care
strategies. Also, schools and RT facilities should imple-
ment consistent instructional and disciplinary policies
and procedures supported by evidence to improve
education outcomes. This can ensure that student issues
are managed effectively, and can provide school staff
withmore educational tools. Finally, residential facilities
and their school partners should review existing system
policies for ways to incorporate normalcy program-
ming into school and treatment plans that foster
engagement in healthy activities, such as sports, tutor-
ing, and extracurricular events that do not compromise
safety.

For staff practicing in residential schools, it is
important to encourage a culture of trauma sensi-
tivity, supported by ongoing training that includes
information about childhood trauma, how trauma
affects brain development, and its impact on youth
functioning (that is, behavior and learning). Stu-
dents in RT settings may not demonstrate the so-
cioemotional skills necessary to be successful in
class. Therefore, school and residential staff alike
can engage students in learning academic material
and model appropriate ways to socially respond to
their environment. The need for development of
trauma-sensitive schools is a theme that has sur-
faced in prior studies (for example, Alisic, 2012;
Crosby et al., 2015). Students should be given op-
portunities to engage in social skills and other soft
skills development (that is, dealing with tasks that pres-
ent frustrations, accountability, empathy, problem solv-
ing, and delayed gratification). Schools that enroll high
numbers of youths from at-risk backgrounds, such as
those who are or have been served in RT facilities,
should be evaluated not only on strict academic test
scores, but also on gains related to attendance and soft
skills development.

Strengths and Limitations of the Study
One strength of the present study was that it used
random selection and focus group methodology
that allow for a deeper understanding of ways in
which adolescents in RT facilities struggle with
their academic and interpersonal relations—which
can potentially contribute to effective intervention
and prevention strategies—and ensure that the re-
ported themes are representative of the youths who
attended the observed school as a whole. Limitations

235Day et al. / Trauma and Triggers: Students’ Perspectives on Enhancing Classroom ExperiencesDownloaded from https://academic.oup.com/cs/article-abstract/39/4/227/4100182/Trauma-and-Triggers-Students-Perspectives-on
by Adam Ellsworth, Adam Ellsworth
on 29 September 2017

also need to be acknowledged. Study participants
were female and predominantly African American
students. Their experiences may not reflect the ex-
periences of male students served in RT facilities or
the opinions of those who identify with other racial
and ethnic groups. Finally, the perception of stu-
dents on school environment is inclusionary of one
important voice in the development of school poli-
cies and practice. The voices of faculty and staff
should be considered to capture a more complete
picture of these facilities.

CONCLUSION
In sum, this study both confirms what is known
about and sheds new light on the factors that either
promote or impede school engagement and dis-
engagement and other factors that promote the edu-
cational well-being of traumatized, court-involved
youths. A comprehensive understanding of these
themes is essential if we are to improve school cli-
mate and, ultimately, the high school retention and
graduation rates among this population. This, in
turn, requires the perspectives of all stakeholders,
including youths themselves. “Nothing about us
without us” best encapsulates this need to engage
youths as leaders in the development of strategies in-
tended to help them overcome the many educa-
tional challenges they face. CS

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Beverly Baroni, PhD, LMSW, is principal, Clara B. Ford
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Accepted May 22, 2017
Advance Access Publication August 31, 2017

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Vol.:(0123456789)

1 3

https://doi.org/10.1007/s40653-018-0207-y

SPECIAL ISSUE INTRODUCTION

Cyberbullying Experiences Among Marginalized Youth: What Do We
Know and Where Do We Go Next?

Guadalupe Espinoza1 · Michelle Wright2,3

Abstract
Cyberbullying experiences are a social and health concern that many children and adolescents are facing in their day-to-day
lives. One limitation of cyberbullying research is that studies have predominately focused on the experiences of youth from
majority groups (i.e., European-American youth living in the U.S.). This limitation is addressed by focusing on cyberbullying
involvement, both as victims and perpetrators, among marginalized groups. Specifically, studies examining cyberbullying
among youth with disabilities and from ethnic, cultural and sexual minority backgrounds are presented. Furthermore, sug-
gestions for future research on cyberbullying experiences among youth are outlined, namely taking into consideration the
intersectionality of various identities and the identification of factors that may protect vulnerable children and adolescents
from the pain of being victimized online.

Keywords Cyberbullying · Marginalized youth · Disabilities · Ethnic minorities · LGBTQ youth

Introduction

In the last decade there has been a steady increase in the
number of studies focused on youth’s experiences with
cyberbullying, both as perpetrators and victims. Impor-
tant strides have been made in better understanding not
only the prevalence rates but also the factors that influ-
ence the likelihood and consequences of involvement in
cyberbullying. As a result, numerous studies have shown
that cyberbullying, like school bullying experiences, are
robustly related to maladjustment among youth. A limita-
tion of research on cyberbullying is that studies have largely
focused on the experiences of youth from majority groups
(i.e., European-American youth living in Western countries).
Thus, many questions remain unanswered when it comes to

understanding cyberbullying among youth from marginal-
ized groups. For example, to what extent do ethnic minority
youth, such as Latino adolescents experience cyberbully-
ing and what factors buffer them from the pain of being
targeted? What is the long-term impact of being targeted
online for young adults who stutter? For youth with a dis-
ability, to what extent are they able to detect the presence or
absence of cyberbullying? To address some of the gaps in
the field, this special issue builds on the existing literature
on cyberbullying and expands it to cover the phenomenon
among youth who are marginalized and whose experiences
have been largely understudied. Specifically, we present a
set a studies that examine cyberbullying experiences among
youth with disabilities, from ethnic and cultural minority
backgrounds and youth who identify as LGBTQ.

What We Learn from the Contributions
of the Special Issue

In total, eight papers are included in this special section
focused on understanding the perpetration and victimiza-
tion experiences among marginalized youth. The first three
papers focus on the experiences of youth with disabilities.
Similar to traditional bullying, early research on cyberbul-
lying among youth with disabilities has shown that children

* Guadalupe Espinoza
guadespinoza@fullerton.edu

Michelle Wright
mfw5215@psu.edu

1 Department of Child and Adolescent Studies, California
State University, Fullerton, 800 N. State College Blvd.,
Fullerton, CA 92831, USA

2 Penn State University, State College, PA, USA
3 Masaryk University, Brno, Czech Republic

Journal of Child & Adolescent Trauma (2018) 11:1–5

Published online: 5 March 2018

http://crossmark.crossref.org/dialog/?doi=10.1007/s40653-018-0207-y&domain=pdf

1 3

with particular disabilities may have a greater likelihood
of being involved in cyberbullying (e.g., Blake et al. 2012;
Kowalski and Fedina 2011) and as such, more research is
needed to understand their experiences. These three studies
compare prevalence rates between youth with and without a
disability, identify protective factors, and consider the long-
term impact of being involved in cyberbullying for youth
with disabilities.

Specifically, in the first article, Kowalski and Toth (2018)
examine the prevalence and correlates of cyberbullying per-
petration and victimization among adolescents and emerging
adults, ages 16 to 20, with and without disabilities. Regard-
less of disability status, adolescents and emerging adults
reported cyberbullying victimization, with the highest rates
reported among individuals with disabilities. No significant
differences were found for cyberbullying perpetration for
either group. Kowalski and Toth suggest tailoring cyberbul-
lying prevention and intervention programs to group char-
acteristics as such characteristics might increase the risk of
cyberbullying victimization. In an article focusing on ado-
lescents with autism spectrum disorder, Wright (2018) found
that high levels of parental mediation of technology use and
social support made the association between cyberbullying
victimization and depression weaker among adolescents.
She concludes that perceived social support and parental
mediation of technology use reduce the risk of experienc-
ing cyberbullying victimization and the associated depres-
sive symptoms. Consequently, Wright argues for additional
research focused on investigating the protective factors for
reducing the negative consequences resulting from experi-
encing cyberbullying. Finally, Nicolai et al. (2018) focus
on examining the differences in the psychological effects of
cyberbullying among: (1) adults who stutter and who were
also cyberbullied as adolescents, (2) adults who stutter and
who were not cyberbullied as adolescents, (3) adults who do
not stutter and who were cyberbullied as adolescents, and
(4) adults who do not stutter and who were not cyberbullied
as adolescents. Overall, this retrospective study of cyberbul-
lying victimization suggests that there are long-term impli-
cations (e.g., greater levels of depression) of experiencing
cyberbullying, and that these effects could possibly continue
into adulthood.

The next five articles focus on the cyberbullying experi-
ences among youth from ethnic, cultural and sexual minor-
ity backgrounds. The “digital divide” that limited inter-
net and cell phone access to only more affluent, majority
groups has now largely diminished, and although there
may be some difference in how groups use their devices
(Tsetsi and Rains 2017), the ability to connect online, and
subsequently be targeted online, is now a concern among
most children and adolescents. Therefore, there is a need to
examine the links between cyberbullying and internalizing
symptoms, compare prevalence rates between majority and

minority youth, and identify protective factors for youth
from ethnic and cultural minority backgrounds. Focus-
ing on comparing the mental health symptoms based on
minority or non-minority status, Duarte et al. (2018) find-
ings revealed that sexual minorities experienced greater
mental health symptoms when compared to non sexual
minorities.

Comparing ethnic majority and minority youth, Barlett
and Wright (2018) found that the relationships between
cyberbullying victimization and cyberbullying perpetra-
tion as well as relational victimization and cyberbullying
victimization were significant for majority adolescents
but not for ethnic minority adolescents, whereas physical
bullying perpetration and cyberbullying perpetration were
associated for minority adolescents only.

In an article focused on identifying friendship factors
that may protect Latino youth from the pain of being bul-
lied online, Espinoza’s (2018) findings suggest that time
spent with friends reduces the association between cyber-
bullying victimization and distress, anger, and attend-
ance problems. Similar patterns were found for friendship
quality, however, friendship quality only attenuated the
link between cyberbullying victimization and feelings of
distress. Focusing on yet another understudied group of
youth, Broll et al. (2018) study the association between
traditional bullying and cyberbullying involvement and
depression, anxiety, and stress among Canadian indig-
enous adolescents. After accounting for age and gender,
cyberbullying victimization was associated with greater
reports of anxiety and stress while including traditional
bullying victimization in the analysis, suggesting a unique
contribution of experiencing cyberbullying.

Concluding this special section is a literature review
authored by Abreu and Kenny (2018) that includes 27 stud-
ies among LGBTQ youth conducted in the United States,
Canada, Australia, Sweden, and the United Kingdom. Find-
ings revealed that cyberbullying victimization of LGBTQ
adolescents ranged from 10.5% to 71.3%. LGBTQ adoles-
cents who experienced cyberbullying victimization reported
more suicidal ideation and attempts, greater depression,
lower self-esteem, physical aggression, body image prob-
lems, isolation, and lower grade point averages. Based on
the findings from the review, the authors make recommenda-
tions that may be particularly salient to protect youth who
identify as LGBTQ.

Overall, the manuscripts included in this special issue
highlight the importance of focusing on cyberbullying and
the associated mental health issues among marginalized
youth. These studies also highlight the need for research to
move beyond comparison of the cyberbullying prevalence
among marginalized and non-marginalized youth, and
instead for research to focus on the diverse cyberbullying
experiences of youth.

Journal of Child & Adolescent Trauma (2018) 11:1–52

1 3

Recommendations for Future Research
on Cyberbullying Among Marginalized
Youth

As cyberbullying research continues to extend the popula-
tion of youth who are studied and examine cyberbullying
experiences among youth with disabilities, who identify as
an ethnic minority, as LGBTQ, and/or who live in a non-
Western country, there are still important gaps that need to
be addressed. One such gap is the dearth of studies exam-
ining the intersectionality of various group memberships
(e.g., gender, ethnicity, generational status) and how this
may uniquely shape youth’s experiences with cyberbully-
ing. For example, it is not only important to test whether
boys or girls are more likely to be victimized online, but
also consider whether that boy or girl identifies as Asian-
American or Black and how their ethnicity may intersect
with gender to play a role in their likelihood of being tar-
geted. Another gap is the identification of factors that may
protect youth who are a part of marginalized groups and
experience cyberbullying. That is, from multiple past stud-
ies it is well recognized that being the victim of cyberbul-
lying is associated with a host of maladjustment problems
such as school absences, distress, and even suicidal idea-
tion (e.g., Bauman et al. 2013; Espinoza 2015; Juvonen
and Gross 2008; Wright 2015), yet, currently there are few
studies that aim to identify family, peer or school factors
that may serve as a buffer in the links between cyberbul-
lying and maladjustment.

An Intersectional Approach

Currently, most studies examine cyberbullying among
marginalized youth by focusing on one part of their iden-
tity in isolation, such as examining the frequency of cyber-
bullying involvement among LGBTQ youth compared to
heterosexual youth or studying the impact of being vic-
timized online among Latino youth. Although this has
been an important first step in extending research from
focusing more exclusively on experiences among White,
middle-class youth, we now need research to explore how
different identities intersect within an individual and how
these intersecting identities impact youth in terms of the
likelihood of being involved in cyberbullying, and also the
consequences of such involvement. For example, Kowalski
and Toth (2018) found that adolescents with a disability
were significantly more likely to report victimization expe-
riences online. However, they did not examine if those
differences may be amplified based on the adolescent’s
gender or ethnic background. That is, perhaps the risk of
being victimized online is even greater for adolescents

who both have a disability and are from an ethnic minority
group. Intersectionality research recognizes that multiple
identities coexist and may fuse together in unique ways
for individuals.

The research on intersectionality among children and ado-
lescents lags compared to research among adults (Ghavami
et al. 2016). However, there are some studies that have
started to tackle the challenge of taking into account numer-
ous identities and their intersection in the study of cyber-
bullying. In a study focused on examining the prevalence
of cybervictimization, Stoll and Block (2015) hypothesized
that the extent to which ethnicity is predictive of cyberbul-
lying involvement among high school students may depend
on their gender and sexuality. The results revealed that gen-
der and ethnicity did intersect. Specifically, among students
of color, rates of cybervictimization did not differ based
on their gender, but among white students, it was female
students who were most likely to be victimized online.
Although no intersection of ethnicity and sexuality was
found, the results reveal how the intersection of gender and
ethnic identities may impact victimization rates. In a differ-
ent study among adolescents that also examined the intersec-
tions of ethnicity, gender and sexual orientation, the results
showed that when examining the intersections of these iden-
tities in the associations between bullying (school and cyber)
and suicidal ideation, it was sexual orientation that most
robustly put adolescents at the greatest risk of suicidal idea-
tion (but did not intersect with ethnicity or gender; Mueller
et al. 2015). Thus, these two studies differ in their results
on the extent to which an adolescent’s ethnicity, gender or
sexual orientation intersect to impact bullying.

Overall, the limited studies in the area show mixed
results, but as this is an area in its nascent phase, more stud-
ies are needed to understand and account for how mutual and
simultaneous identities play a role in cyberbullying among
youth. It will certainly be challenging for research that uti-
lizes an intersectionality framework to take into account the
various and complex identities relevant for children and ado-
lescents, but it is important to note that in their day to day
lives, there are some identities that may be more relevant,
especially within the online context. Thus, researchers will
need to consider the unique aspects of both the online con-
text and their particular sample to identify the intersecting
identities that may be most critical to capture.

Identification of Protective Factors

As the research on cyberbullying among youth from
marginalized groups continues to grow, so does the evi-
dence that across all groups, youth who are victimized
online fare worse compared to youth who do not expe-
rience victimization. For example, in a study among
Asian and Pacific Islander high school students, reports

Journal of Child & Adolescent Trauma (2018) 11:1–5 3

1 3

of cyberbullying increased the likelihood of substance
use and suicide attempts (Goebert et al. 2011). Kowalski
et al. (2016) found that being cyberbullied was especially
linked to low self-esteem and greater depression among
college students with a disability. Moreover, research in
this special issue highlights how LGBTQ youth who are
cyberbullied report a number of psychological, emotional,
behavioral and academic problems (Abreu and Kenny
2018), and that Indigenous adolescents in Canada who
are cyberbullied report higher levels of anxiety and stress,
over and above the impact of school bullying (Broll et al.
2018). Thus, given our growing understanding of the ways
in which youth are impacted by cyberbullying and given
that this may be further complicated given the challenges
they face as members of marginalized groups, it is impor-
tant for future work to test and identify factors that may
protect youth from the pain of being victimized online.

In the current issue, some strides are made towards
filling this gap with Wright (2018) identifying that both
parental mediation of technology use and social sup-
port weakened the positive link between cyberbullying
victimization and depression among youth with autism
spectrum disorder, and Espinoza (2018) finding that time
spent with friends protects Latino adolescents from the
anger, distress, and attendance problems that result from
being bullied online. Given differences in culture, abil-
ity, context and a number of other factors that may differ
among youth from various marginalized groups, a pro-
tective factor for one group may not necessarily be pro-
tective for another group of youth. For example, it could
be hypothesized that family closeness and support may
serve a greater protective role for victims of cyberbullying
from collectivistic backgrounds (e.g., particular Latino or
Asian backgrounds) where the role of family is particu-
larly emphasized (Fuligni et al. 1999). Given that LGBTQ
youth tend to first come out to their friends before their
parents and other family members (Savin-Williams 1998),
then when they are victimized online, peer and friendship
support may be more protective against negative outcomes
than family support. Thus, more research is needed to test
and identify the factors that will protect youth from the
pain of being cyberbullied, as this will be paramount to
the continuing development and improvement of interven-
tion programs to help victims of bullying, especially those
youth who may be the most vulnerable. In conclusion,
understanding the cyberbullying experiences among mar-
ginalized youth that is presented in this special issue and
furthermore, future research extending this research area
will help educators, social workers and policy makers as
we all work towards addressing this important problem
of cyberbullying that many children and adolescents are
facing in their day to day lives.

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Cyberbullying Experiences Among Marginalized Youth: What Do We Know and Where Do We Go Next?

Abstract

Introduction

What We Learn from the Contributions of the Special Issue

Recommendations for Future Research on Cyberbullying Among Marginalized Youth

An Intersectional Approach

Identification of Protective Factors

References

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