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Peer Victimization Among Children and Adolescents: A Meta-Analytic Review of Links to Emotional Maladjustment

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Clinical Pediatrics
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© The Author(s) 2015
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DOI: 10.1177/0009922814567873
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Commentary
Introduction
Peer victimization among children and adolescents has
been the central issue of hundreds of studies over the
past 3 decades. Cross-sectional and longitudinal studies
have explored the relationship between peer victimiza-
tion and emotional adjustment, and provide robust evi-
dence that peer victimization is linked to emotional
adjustment difficulties.1,2 However, some studies failed
to examine the correlation between peer victimization
and individual indicators of emotional maladjustment.3
Moreover, the strength of this link varies greatly between
studies. For example, the correlation between peer vic-
timization and anxiety ranges between 0.11 and 0.61.4,5
Past research concentrated on overt victimization,
whereas relational victimization has only recently been
recognized.6 However, this type of peer victimization
may have potentially strong deleterious effects on emo-
tional adjustment. Since the beginning of the 21st cen-
tury, a large number of empirical studies considered the
different types of peer victimization, including relational
victimization, and their effect on emotional adjustment.
The aim of the current study was to provide a quantita-
tive review of these studies, examining the linkages
between peer victimization and emotional maladjust-
ment in children and adolescents as well as the factors
moderating this relationship.
Forms of Peer Victimization
Peer victimization is defined as repeated exposure to
physical, verbal, or interpersonal relationship attacks
from age-mates.7 Currently, most researchers agree that
peer victimization includes 3 basic types: physical, ver-
bal, and relational.8 Physical and verbal victimization
are collectively known as “overt victimization.”
Relational victimization, characterized by indirectness
and concealment, is considered the most harmful vic-
timization type. It involves behaviors that harm others
through damaging their relationships, feelings of accep-
tance, and inclusion in social groups.9
Association Between Peer Victimization and
Emotional Maladjustment
Many children and adolescents suffer from prolonged
peer victimization, leading to various maladjustments.10
Loneliness, anxiety, and depression are generally con-
sidered the 3 indicators of emotional maladjustment.11
The following theories may explain this relationship.
According to the social information-processing
model, children acquire causal and intent attributions
from encoded social cues among peers. Such cue inter-
pretations may indicate the presence of hostile intent.
Children’s tendency to derive negative self-evaluations
from social experiences may, in the long term, affect
their self-schemas and evaluations of self-competence.12
These processes may explain internalizing symptoms,
like depression, loneliness, and anxiety.
Early peer interaction forms the basis of future social
communication, as children and adolescents rely on per-
sonal peer experience to evaluate themselves and oth-
ers.9 Peer victimization, and relational victimization in
particular, directly destroys positive peer relationships,
potentially resulting in a decline in trust. As children
internalize the experiences of being victimized, they
gradually form negative self-evaluations, which in turn
leads to emotional and other types of maladjustment.13
Results from empirical studies indicate that, relative
to their peers, victimized children and adolescents are
more lonely,5 anxious, and depressed.14 This result was
supported by Hawker and Boulton’s meta-analysis of
cross-sectional research published between 1978 and
1997 examining the correlations between peer victimiza-
tion and indices of psychosocial maladjustment as well
as Reijntjes’ meta-analysis of longitudinal studies.8,15
567873CPJXXX10.1177/0009922814567873Clinical PediatricsWu et al
research-article2015
1Southwest University, Chongqing, China
Corresponding Author:
Dajun Zhang, Faculty of Psychology, Research Center of Mental
Health Education, Southwest University, Tiansheng Road, No. 2,
Beibei District, Chongqing 400715, China.
Email: zhangdj@swu.edu.cn
Peer Victimization Among Children and
Adolescents: A Meta-Analytic Review of
Links to Emotional Maladjustment
Lili Wu, MS1, Dajun Zhang, Prof.1, Zhiqiang Su, PhD1, and Tianqiang Hu, PhD1
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2 Clinical Pediatrics
With regard to the different types of victimization,
recent research suggests that these modulate individual
adjustment problems.16 It has been demonstrated that
relational victimization is more strongly related to inter-
nal issues than is overt victimization.17 However, other
studies suggest that overt victimization is more strongly
correlated with psychosocial adjustment.18
Based on the above theoretical considerations and
empirical evidence, our first hypothesis in this study is
that peer victimization and emotional maladjustment
indices (depression, loneliness, and anxiety) are signifi-
cantly correlated. In addition, we hypothesize different
effect sizes between different peer victimization types
and emotional maladjustment indices.
Moderator Effects
Age may moderate the relationship between peer vic-
timization and emotional maladjustment. Peer victim-
ization form, frequency, and level all change with age,1
and so do the form and content of emotional adjustment
issues.19
Another potential moderator may be the information
source of peer victimization assessment. Self-report and
peer nomination are 2 typical methods of measuring
peer victimization. Self-report involves questions
regarding the frequency with which a child bullied
another child or was bullied himself or herself. Peer
reports consist of nominations or ratings by group mem-
bers. A study comparing different methods of peer vic-
timization assessment found that different methods of
assessment involving different informants are not well
correlated, and the differences between them may also
affect the correlations between peer victimization and
maladjustment.11
Gender is another factor that may moderate the rela-
tionship between victimization and emotional malad-
justment. Some studies have shown that gender does not
regulate the relationship between peer victimization and
emotional maladjustment20; however, Duncan21 found
that girls feel embarrassed after being victimized, which
makes them internalize the victimized experience and
negative feedback thereby causing them to experience
severe emotional adjustment issues. On the other hand,
Erath et al14 found that boys are more sensitive when
confronted with incidents of peer pressure, suggesting
that boys could be even more vulnerable to problems of
emotional adjustment. Therefore, the moderating effect
of gender on peer victimization and emotional malad-
justment still requires further research.14
Finally, cultural differences could also moderate the
link between peer victimization and maladjustment.
While Eastern culture is primarily collectivist, Western
cultures are largely more individualist. Such cultural dif-
ferences affect the process of individual socialization.
Peer victimization is one of the signs of poor individual
socialization. Ji et al22 found that the incidence of verbal
and relational victimization among children and adoles-
cents is lower in China than in England. Furthermore,
differences in cultural context also lead people to form
different concepts and attitudes. Research found that
Western children have a more passive attitude toward
dealing with peer victimization, which results in more
severe emotional adjustment symptoms.23 These results
suggest that the correlation between victimization and
maladjustment may be more robust in Western cultures
than in Eastern ones.
Methods
Search Strategy
We conducted a literature search for cross-sectional and
longitudinal studies of the association between peer vic-
timization and emotional maladjustment indices pub-
lished since 2000. The following electronic databases
were searched: Science Direct, EBSCO, PROQUEST,
Web of Science, Springer Link, Elsevier, and PQDD.
The search keywords were “peer victimization,” “bully-
ing,” “covert victimization,” “relational victimization,”
and “overt victimization” in conjunction with “emotional
adjustment,” “anxiety,” “loneliness,” and “depression.”
Study Inclusion and Exclusion Criteria
We included empirical studies published in English and
Chinese between 2000 and 2014. Studies had to include
randomly selected samples of typically developing chil-
dren and adolescents, and report simple correlations
between types of peer victimization and emotional
adjustment symptoms. In addition, measurements of
peer victimization needed to include self-report or peer
nomination.
Study exclusion criteria were the following: (1) the
sample was from a clinical population and (2) the study
was qualitative.
A total of 65 studies were retained, 10 of which were
conducted in Eastern countries. Regarding the relation-
ship between peer victimization and emotional maladjust-
ment symptoms, our analysis covered 114 independent
samples (n = 95 285). The subset of studies exploring the
overall correlation between peer victimization and emo-
tional maladjustment consisted of 27 effect sizes (n =
16 427). With respect to the relationship between peer
victimization types and emotional maladjustment symp-
toms, our analysis covered 90 effect sizes (n = 69 291).
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Wu et al 3
Coding
All independent samples meeting the inclusion criteria
were coded for possible moderators of the relationship
between peer victimization and emotional maladjust-
ment. These moderators were as follows: age groups
(childhood, 0-12 years; adolescence,13-18 years), gen-
der composition (percentage of male participants) and
information source of peer victimization assessment
(self-report, peer nomination). In terms of variables, we
coded information on peer victimization types (overt vic-
timization, relational victimization) and emotional mal-
adjustment measures (anxiety, depression, loneliness).
Studies were coded independently by the first author and
a research assistant at 2 different times. Interrater agree-
ment was 93% (kappa coefficients between .83 and 1).
Differences were resolved by discussion.
Data Analysis
Aggregate r effect sizes were estimated with
Comprehensive Meta-Analysis 2.0, using a fixed-effects
approach. This approach yields a more precise and reli-
able estimate of the peer victimization–emotional mal-
adjustment relationship than a random effects approach
would.24 Homogeneity tests of the effect sizes were also
conducted. Significant heterogeneity suggests that effect
size differences are due to factors other than sampling
error, such as study characteristics.25 Moderator analy-
ses were then conducted to obtain explanations for the
variability in effect sizes across studies. Categorical
moderator tests are analogous to analysis of variance
(ANOVA) and result in 2 homogeneity estimates, a
within-groups Q (Qw) and a between groups Q (Qb). A
significant Qw indicates heterogeneous effect sizes
within one category of the moderator variable, whereas
a significant Qb indicates significantly different effect
sizes across different categories of the moderator
variable.25
We used Pearson’s r as the effect size metric. The
standard error formulation of correlation coefficients is
problematic, but we applied the Fisher’s Zr-transform to
solve this problem.26 Since larger samples yield more
precise results, we corrected for sample size by multi-
plying the effect sizes by their inverse variances. Finally,
we back-transformed the Fisher’s z coefficients to raw
correlation coefficients for ease of interpretation. For
studies reporting separate effect sizes, mean effect sizes
for the total sample were calculated. We computed a
95% confidence interval (CI) around each mean effect
size. Confidence intervals not including zero were taken
to indicate a statistically significant result. Following
Cohen, we interpreted correlation effect sizes greater
than 0.40 as large, approximately 0.25 as medium, and
less than 0.10 as small.27
Publication bias was evaluated using Rosenthal’s
fail-safe number (FSN), which represents the number of
studies that would be required for the observed effect to
disappear. A tolerance level was calculated around the
FSN, which was equal to 5 times the number of the
effect size (k) plus 10 (5k + 10 benchmark).28 When the
FSN consistently exceeds the 5k + 10 benchmark, it is
concluded that no additional research is needed to estab-
lish the phenomenon.
Results
The overall correlation between peer victimization and
emotional maladjustment was examined using 27 inde-
pendent samples (n = 16 427). We calculated the fixed-
effects model of the correlation coefficients between peer
victimization and emotional maladjustment (Table 1). As
predicted, peer victimization was positively associated
with emotional maladjustment (k = 27, r = 0.255, 95%
CI = 0.241-0.268, Z = 34.880, P < .001), with a medium
effect size.
Next, we calculated the correlation coefficients for
peer victimization across emotional adjustment disorder
clusters. As shown in Table 2, peer victimization was
positively associated with emotional maladjustment
symptoms: anxiety (k = 41, r = 0.192, 95% CI = 0.181-
0.204, Z = 32.324, P < .001), depression (k = 50, r =
0.248, 95% CI = 0.240-0.257, Z = 52.675, P < .001), and
loneliness (k = 23, r = 0.286, 95% CI = 0.274-0.298, Z =
43.509, P < .001).
As Table 3 shows, both relational victimization and
overt victimization were positively associated with
emotional maladjustment indices. Furthermore, rela-
tional victimization was more strongly related to emo-
tional problems than was overt victimization: Q =
29.887, P < .001.
The homogeneity of variance test revealed signifi-
cant, high heterogeneity across studies (Table 4), Q =
2332.120, P < .001, I2 = 93.825%. Therefore, mixed
effects moderator analyses were conducted to examine
the association between study characteristics and their
effect sizes. The results of the moderator analyses are
summarized in Tables 5 and 6.
Table 1. Fixed Effects Analysis of the Association Between
Peer Victimization and Emotional Adjustment.a
k N Mean r Effect Size 95% CI Z
27 16427 0.255 0.241-0.268 34.880***
ak indicates number of samples.
*P < .05. **P < .01. ***P < .001.
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4 Clinical Pediatrics
Table 4. Homogeneity Test.a
k Q df P I2τ2pτ
114 2332.120 113 < 0.001 93.825 0.020 <.001 0.142
aQ = test for homogeneity of effect sizes. Significant scores indicate heterogeneity. τ2 is the estimate of between-study variance.
*P < .05. **P < .01. ***P < .001.
First, we evaluated the role of age group as a modera-
tor of peer victimization and emotional maladjustment.
Age group did account for a significant portion of the
variability in peer victimization (Qb = 4.240, P < .05),
with adolescents showing a stronger relationship (k =
11, r = 0.274, 95% CI = 0.251-0.297) than children (k =
16, r = 0.243, 95% CI = 0.226-0.261).
Second, we evaluated the role of assessment method
(self, peer) as a moderator of peer victimization and
emotional maladjustment. We found that assessment
method significantly moderated peer victimization
(Qb = 27.533, P < .001), with self-report having a stronger
relationship (k = 21, r = 0.289, 95% CI = 0.271-0.307).
Third, a fixed-effects homogeneity statistic was com-
puted to determine whether there was a significant dif-
ference in the average r effect size in different cultures
(Qb = 357.810, P < .001). Eastern children and adoles-
cents were found to have a significantly weaker average
r effect size (k = 3, r = 0.222).
Last, as shown in Table 6, sample gender signifi-
cantly moderated the peer victimization–emotional
maladjustment relation (QModel = 20.17, P < .001), with
the correlation being stronger for female than for male
respondents. Because the unstandardized slope was neg-
ative (β1 = −0.011; 95% CI = −0.015 to −0.006) and the
gender variable was fixed between 0.00 (all female
respondents) and 1.00 (all male respondents), meta-
regression could be used to predict the effect size for
these 2 extreme cases. An increase in the proportion of
male respondents was associated with a decrease in the
strength of the peer victimization–emotional maladjust-
ment relation.
To evaluate the existence of a publication bias, a fun-
nel plot of standard errors plotted against effect sizes
was created. The funnel plot indicated no systematic
publication bias, with studies distributed symmetrically
around the mean effect size (Figure 1).
A fail-safe N and the 5k + 10 benchmark were calcu-
lated. The FSN suggested that there would need to be at
least 8868 studies with a null effect size added to the
analysis before the cumulative effect would become
negligible.
Table 2. Fixed Effects Analysis of the Association Between Peer Victimization and Emotional Adjustment Symptoms.a
Emotional
Adjustment k N Mean r Effect Size 95% CI Z Q
Anxiety 41 27899 0.192 0.181-0.204 32.324*** 70.858***
Depression 50 29490 0.248 0.240-0.257 52.675***
Loneliness 23 18948 0.286 0.274-0.298 43.509***
aQ = test for homogeneity of effect sizes. Significant scores indicate heterogeneity.
*P < .05. **P < .01. ***P < .001.
Table 3. Peer Victimization Types and Indices of Emotional Adjustment.
Peer
Victimization
Emotional
Adjustment Index k N
Mean r
Effect Size 95% CI Z Q
Relational
victimization
Anxiety 18 9526 0.165 0.150-0.180 21.189*** 29.887***
Depression 20 13403 0.259 0.248-0.269 45.901***
Loneliness 11 15667 0.245 0.232-0.257 35.840***
Overt
victimization
Anxiety 14 6037 0.216 0.202-0.230 28.826***
Depression 16 12088 0.293 0.281-0.305 45.218***
Loneliness 11 10567 0.313 0.300-0.327 42.944***
*P < .05. **P < .01. ***P < .001.
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Wu et al 5
Discussion
Previous studies of peer victimization focused on overt
victimization, and disregarded relational victimization.
The present meta-analysis considered the correlation
between different victimization types and emotional
maladjustment, resulting in a more systematic analysis.
It demonstrated that peer victimization is related to emo-
tional maladjustment (r = 0.255). This is consistent with
results from most previous research,29 and supports the
social information-processing model. In addition, we
found that peer victimization is positively associated
with each form of emotional maladjustment. The largest
effect size was for loneliness (r = 0.286), and the small-
est for anxiety (r = 0.192), with the effect size for depres-
sion in between (r = 0.248).
Self- and peer perceptions may partially account for the
relation between peer victimization and emotional adjust-
ment difficulties. With age, children’s self-perceptions
become more self-critical, and their concern for peer
acceptance increases. This may be particularly detri-
mental for children who are victimized by peers. The
majority of children and adolescents cannot effectively
cope with pressure of peer exclusion and rejection. They
may gradually adopt a negative attributional style, which
could eventually result in emotional maladjustment.30
On the other hand, children are also believed to
develop generalized cognitive representations of oth-
ers.12 Victimized children may develop cognitive repre-
sentations of their aggressors as hostile, and these
negative perceptions may generalize to the entire peer
group if they do not offer help.29 Thus, the behaviors and
attitudes of bystanders may affect how victimization is
experienced, which could, in turn, have negative effects
on victimized children.31 Some studies indicated that
associations between peer victimization and loneliness
are at least partially mediated by children’s self- and
peer perceptions.29
Regarding the correlation between different victim-
ization types and emotional maladjustment, the present
study obtained similar results to those of Western stud-
ies, in that both overt and relational victimization are
significantly correlated with emotional maladjustment.9
However, we also found that relational victimization has
a greater negative impact on emotional adjustment than
does overt victimization. This is probably because rela-
tional victimization involves the manipulation of social
relations.
Compared with the results of two previous meta-
analyses, our mean effect size (0.255) is substantially
higher than the total effect size of 0.18 in the study by
Reijntjes et al,15 although we have to keep in mind that
Reijntjes’s meta-analysis included correlations obtained
from structural equation model and regression analysis,
while the present meta-analysis only considered literature-
reported Pearson correlation coefficients. In addition, the
difference may be because emotional maladjustment
and internalizing problems are different constructs.
Regarding the correlations between peer victimization
and emotional maladjustment, both the present and
Hawker’s meta-analysis obtained small to medium
effect sizes,8 with slight differences. This may be
because the effect sizes in Hawker are separated accord-
ing to whether there was shared method variance or not.8
Furthermore, the studies included in previous meta-
analyses focused on overt victimization, whereas the
studies in this meta-analysis presented a comprehensive
consideration of peer victimization and hence may have
obtained more accurate results.8
In Reijntjes’s meta-analysis, the ability to detect mod-
erator effects was limited by the relatively small number
of studies.15 Contrary to Reijntjes’s analysis,15 we found
that age was a moderator of the linkages between victim-
ization and emotional maladjustment. In childhood and
adolescence, more severe peer victimization is related to
more serious emotional adjustment issues, and adolescents
Table 5. Categorical Moderators of Peer Victimization: Emotional Adjustment.a
Moderator Qbk N Mean r Effect Size 95% CI Qw
Age group 4.240*
Childhood 16 7278 0.243 0.226-0.261 229.761***
Adolescence 11 9149 0.274 0.251-0.297 122.548***
Assessment method 27.533***
Self-report 21 14241 0.289 0.271-0.307 200.218***
Peer nomination 6 2818 0.203 0.180-0.225 121.049***
Culture 357.810***
East 3 4257 0.222 0.199-0.245 107.469***
West 24 12170 0.274 0.256-0.290 237.849***
aSignificant Q statistic rejects null hypothesis of no variation either between groups (Qb) or within the specified group (Qw).
*P < .05. **P < .01. ***P < .001.
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6 Clinical Pediatrics
have more severely affected than children. This may be
related to the increased importance of friendships in ado-
lescence. At this age, poor peer relationships easily result
in increasing in internal issues such as social anxiety.32
The information source of peer victimization assess-
ment was also found to moderate the correlation between
peer victimization and emotional maladjustment, with
self-report having a stronger relationship. This is consis-
tent with previous work, which has shown that self-
reports of victimization are predominantly related to
internalizing problems.33 On the other hand, peer vic-
timization is often a private and subjective experience,
hidden from other group members. Therefore, some vic-
tims may be easily overlooked by self-report question-
naires and consequently constitute a group at higher risk
for adjustment difficulties.31
Gender was also found to influence the correlation
between peer victimization and emotional maladjust-
ment. The correlation was stronger for female respon-
dents than for male respondents. This is at odds with the
results of Reijntjes’s meta-analysis,15 but it is in line
with Grills’ conclusion.34 Rose and Rudolph proposed a
peer-socialization model in which children are more
inclined to assimilate the characteristics of same-gender
groups, placing their members at-risk for particular
adjustment outcomes (emotional problems for girls;
behavioral problems for boys).35
Additionally, there are sex differences in coping with
peer victimization. Female victims tend to have internal
reactions, and continually internalize them.36 The greater
likelihood of rumination in females may keep them
dwelling on negative events, which would lead to emo-
tional problems.35 In contrast, male victims are inclined
to blame others, display hostility toward peers, and pres-
ent external reactions.37
Finally, cultural factors were also shown to affect the
correlation between peer victimization and emotional
maladjustment. In Western cultural contexts, peer vic-
timization was more strongly related to emotional mal-
adjustment. As mentioned above, differences between
China and Western countries in terms of social environ-
ment and cultural background may also influence cogni-
tion and attitudes toward peer victimization. Chinese
children have been shown to be more active in dealing
Table 6. Meta-Regression Analyses With Effect Size Regressed Onto Proportion of Men in Sample.a
Parameter Estimate Z95% CI for β
β00.798 6.654 0.563 to 1.033
β1–0.011 –4.491 –0.015 to –0.006
QModel (1, K = 23) = 20.17, P < .001
aβ0 is the intercept (when β1 equals 0); β1 is the unstandardized slope (the change in the predicted effect size with a unit change in the
predictor).
Figure 1. Funnel plot of all effect sizes in this study.
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Wu et al 7
with bullying than children in England.24 Such differ-
ences in attitude may lead to Eastern children showing
less serious emotional adjustment issues than Western
children.
Conclusions
The results of the present study suggest that peer victim-
ization is closely related to emotional maladjustment.
And there is a positive linear correlation between peer
victimization and emotional maladjustment indices,
including loneliness, depression, and anxiety.
Overt and relational victimization both have a nega-
tive impact on emotional adjustment, but the impact of
relational victimization is stronger. Age, gender, source
of informants, and cultural context moderate the rela-
tionship between peer victimization and emotional mal-
adjustment. So parents and teachers should be trained in
effective ways of intervening in bullying and victims’
emotional problems.
Appendix A
Selected Study Characteristics of the Included Studies.a
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Barchia and
Bussey (2010)
Western 1285 adolescents (M = 13),
Sex: 46.1% male
Self-report r0.41 — —
1177 adolescents (M = 13),
Sex: 46.1% male
r0.43 — —
Biggs et al (2010) Western 160 adolescents(M = 15.5),
Sex: 43.5% male
Self-report r — 0.5
r 0.37 —
91 adolescents (M = 15.5),
Sex: 63.7% male
r 0.33 —
r — 0.56
Catterson and
Hunter (2010)
Western 110 children (M = 10.08),
Sex: 49% male
Self-report r — — 0.43
Cheng et al
(2008)
Eastern 712 adolescents (M = 15.7),
Sex: 53.7% male
Self-report r — 0.42
Cole et al (2010) Western 403 children (M = 10.9), Sex:
48.9% male
Self-report r0.46 — —
r10.39 — —
r20.53 — —
Peer
nomination
r0.34 — —
r10.36 — —
r20.33 — —
Crawford and
Manassis (2011)
Western 85 children (M = 10.41), Sex:
43.5% male
Self-report r0.17 — —
Crick and Nelson
(2002)
Western 496 children (M = NR), Sex:
49.2% male
Self-report r 0.21 —
r1 0.19 —
r2 0.23 —
r — — 0.33
r1 — — 0.33
r2 — — 0.37
DeRosier and
Mercer (2009)
Western 1193 children (M = 9.16),
Sex: 49% male
Peer
nomination
r — — 0.18
r — 0.09
r— 0.16
Desjardins and
Leadbeater
(2011)
Western 664 adolescents (M = 15.5),
Sex: 48.3% male
Self-report r — 0.33
580 adolescents (M = 17.5),
Sex: 47% male
r — 0.27
540 adolescents (M = 19.5),
Sex: 45.6% male
r — 0.32
Dill et al (2004) Western 731 children (M range from
10-12), Sex: 48.6% male
Self-report r 0.106 —
466 children (M range from
10-12), Sex: 47.2% male
Self-report r 0.18 —
(continued)
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8 Clinical Pediatrics
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Erath et al (2007) Western 84 adolescents(M = NR),
Sex: 44.7% male
Peer
nomination
r 0.24 —
Self-report r 0.6 —
Erath et al (2012) Western 63 children (M = 11.67), Sex:
50.7% male
Self-report r 0.58 —
Parent report r 0.51 —
Fredstrom et al
(2011).
Western 802 adolescents (M = 15.84),
Sex: 43% male
Self-report r 0.21 —
Self-report r — 0.23
Self-report r — 0.23
Self-report r 0.26 —
Ghoul et al (2013) Western 716 adolescents (M = 15.95),
Sex: 49.7% male
Self-report r — 0.59
r 0.61 —
Gomes et al
(2009)
Western 241 adolescents(M = 18.3),
Sex: 0% male
Self-report r2 — 0.29
Graham et al
(2006)
Western 1985 children (M = 11.5),
Sex: 45.5% male
Peer
nomination
r — — 0.25
r 0.15 —
r — — 0.16
Griese and Buhs
(2013)
Western 511 children (M = 10.62),
Sex: 48.7% male
Peer
nomination
r — — 0.34
r1 — — 0.3
r2 — — 0.38
r — — 0.16
r1 — — 0.14
r2 — — 0.19
Grills and
Ollendick
(2002)
Western 279 children (M = 11.75),
Sex: 47% male
Peer
nomination
r 0.23 —
Guo and Zhang
(2002)
Eastern 744 children (M =
10.96±1.32), Sex: NR
Peer
nomination
r 0.01 —
Hoglund and
Leadbeater
(2007)
Western 337 adolescents(M = 15),
Sex: 42.7% male
Self-report r — 0.49
r1 0.465 —
r2 — 0.59
Iyer et al (2013) Western 157 adolescents (M = 12.21),
Sex: 42%
Self-report r — 0.22
r1 — 0.15
r2 — 0.13
r — 0.5
r1 — 0.35
r2 — 0.36
Ji et al (2011) Eastern 1767 children (M = 9.25),
Sex: 49.5% male
Self-report r — 0.46
r1 — 0.39
r2 — 0.48
r — 0.42
r1 — 0.36
r2 — 0.47
r — 0.45
r1 — 0.39
r2 — 0.49
r — 0.47
r1 — 0.42
r2 — 0.51
Kawabata et al
(2010).
Eastern 138 children (M range: 9-10),
Sex: 50% male
Teacher report r — 0.26
r1 — 0.25
r2 — 0.28
(continued)
Appendix (continued)
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Wu et al 9
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Kelly et al (2008) Western 199 children (M = 9.02), Sex:
52.8% male
Self-report r0.21 — —
Peer
nomination
r0.27 — —
Khatri et al (2000) Western 471 children (M = NR), Sex:
46% male
Peer
nomination
r — 0.4
r — 0.44
r0.44 — — —
Levinson et al
(2013)
Western 108 adolescents (M = 19),
Sex: 48% male
Self-report r2— 0.12
r2— 0.05
Lim et al (2011) Western 96 adolescents (M = 12.8),
Sex: 46.9% male
Self-report r — 0.56
Ma and Bellmore
(2012)
Western 831 adolescents (M = 12.1),
Sex: 50.8% male
conbine r0.08 — —
r1-0.13 — —
r2-0.02 — —
Malti et al (2010) Western 175 children (M = 6.1), Sex:
51.4% male
Self-report r0.3 — —
r0.28 — —
r0.2 — —
Perren et al
(2010)
Western 1320 adolescents (M = 13.7),
Sex: 47.2% male
Self-report r — 0.26
374 adolescents (M = 14.3),
Sex: 46.8% male
r — 0.24
Price et al (2013) Western 211 children (M = 11.26),
Sex: 49.9% male
Self-report r 0.45 —
r1 0.42 —
r2 0.47 —
r — 0.41
r1 — 0.4
r2 — 0.43
Putallaz et al
(2007)
Western 1397 children (M = NR),
Sex: 45.5% male
Peer
nomination
r 0.09 —
r1 0.15 —
r2 -0.02 —
Self-report r 0.05 —
r1 0.04 —
r2 0.06 —
r — 0.09
r1 — 0.07
r2 — 0.12
r — — 0.13
r1 — — 0.07
r2 — — 0.19
Raskauskas (2010) Western 96 children (M = 10.36), Sex:
54.1% male
Self-report r0.68 — —
Rawana and
Kohut (2012)
Western 311 adolescents(M = 15.37),
Sex: 43.1% male
Self-report r — 0.34
r1 — 0.28
r2 — 0.41
Rodkin and
Berger (2008)
Western 508 children (M range: 10-
11), Sex: 54.1% male
Peer
nomination
r0.37 — — —
r0.37 — — —
Rudolph et al
(2011)
Western 132 children (M = 9.46), Sex:
51.5% male
Self-report r — 0.49
r — 0.43
Schad et al (2008) Western 97 adolescents(M = 15), Sex:
42.7% male
Peer
nomination
r2 — 0.18
r0.27 — —
r10.24 — —
r20.31 — —
(continued)
Appendix (continued)
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10 Clinical Pediatrics
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Schwartz et al
(2002)
Eastern 122 children (M range from
10-12), Sex: 54.1% male
Peer
nomination
r — — 0.38
Self-report r — — 0.64
Seeds et al (2010) Western 101 adolescents(M = 15.51),
Sex: 36.6% male
Self-report r — 0.29
Shapero et al
(2013)
Western 179 adolescents (M = 14),
Sex: 42% male
Self-report r — 0.49
r 0.26 —
r — 0.36
r 0.17 —
Siegel et al (2009) Western 228 adolescents(M range:
16), Sex: 42% male
Self-report r 0.31 —
r1 0.02 —
r2 0.43 —
r 0.23 —
r1 0.13 —
r2 0.35 —
Singh and Bussey
(2011)
Western 2161 adolescents (M =
12.74), Sex: 50.4% male
Self-report r 0.48 —
Western Self-report r — 0.41
Storch et al
(2003)
Western 205 children (M = 10.83),
Sex: 46.3% male
Self-report r1 — 0.49
r2 — 0.49
r1 0.47 —
r2 0.51 —
r1 — — 0.44
r2 — — 0.34
Storch et al
(2003)
Western 383 adolescents(M range:
13-16), Sex: 37.9% male
Self-report r1 0.14 —
r2 0.6 —
r1 — — 0.41
r2 — — 0.58
Storch and Masia-
Warner (2004)
Western 561 adolescents(M range:
13-17), Sex: 0% male
Self-report r 0.45 —
r1 0.57 —
r2 0.32 —
r — — 0.47
r1 — — 0.54
r2 — — 0.35
Taylor et al
(2013)
Western 326 adolescents (M = 12.1),
Sex: 46.3% male
Self-report r 0.21 —
r1 0.17 —
r2 0.26 —
r — 0.16
r1 — 0.19
r2 — 0.29
Terranova (2009) Western 140 children (M = 10), Sex:
45% male
Self-report r0.22 — —
Terranova et al
(2011)
Western 311 children (M = 10.8), Sex:
43% male
Self-report r0.42 — —
Tillfors et al
(2012)
Western 1528 adolescents (M = 14.7),
Sex: 50.7% male
Self-report r0.12 — —
r0.18 — —
Totura et al
(2014)
Western 469 adolescents (M = 12.9),
Sex: 46.4% male
Self-report r0.36 — —
r0.25 — —
r0.27 — —
r0.26 — —
(continued)
Appendix (continued)
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Wu et al 11
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Tran et al (2012) Western 598 children (M = 10.8), Sex:
49.3% male
Self-report r — 0.34
r1 — 0.24
r2 0.445 —
Peer
nomination
r — 0.31
r1 0.385 —
r2 0.335 —
Self-report r — 0.45
r1 0.415 —
r2 — 0.48
Peer
nomination
r — 0.33
r1 — 0.29
r2 — 0.39
Uba et al (2010) Eastern 242 adolescents(M = 14.67),
Sex: 49.2% male
Self-report r 0.296 —
Vaillancourt et al
(2011)
Western 168 children (M = 12), Sex:
54.2% male
Self-report r — 0.43
156 adolescents (M = 12.6),
Sex: NR
r — 0.51
139 adolescents (M = 13.2),
Sex: NR
r — 0.35
van den Eijnden et
al (2014)
Western 835 adolescents (M = 13.2),
Sex: 49.7% male
Self-report r — — 0.26
r 0.2 —
r — — 0.21
r 0.14 —
r — — 0.18
r 0.11 —
van Hoof et al
(2008)
Western 194 adolescents(M = 14.7),
Sex: 49.8% male
Self-report r — 0.43
Visconti and
Troop-Gordon
(2010)
Western 420 children (M = 9.4), Sex:
46.9% male
Self-report r— — 0.09
r — 0.09
r 0.01 —
r — 0.23
r — 0.19
r 0.07 —
Vuijk et al (2007) Western 448 children (M = NR), Sex:
49% male
Self-report r — 0.12
r1 — 0.14
r2 — 0.13
r 0.13 —
r1 0.14 —
r2 0.13 —
Wang et al (2002) Eastern 827 children (M = 11.69),
Sex: 45.7% male
Self-report r — — 0.309
r0.26 — —
r — 0.272 —
r 0.206 —
Wang et al (2007) Eastern 827 adolescents (M = 14.86),
Sex: 53.1% male
Self-report r — — 0.295
r — 0.27
r 0.18 —
r0.25 — —
Xiong et al (2007) Eastern 299 children (M = NR), Sex:
52.8% male
Peer
nomination
r 0.332 —
r — 0.29
(continued)
Appendix (continued)
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12 Clinical Pediatrics
Appendix B
Studies Included in the Meta-Analysis
1. Barchia K, Bussey K. The psychological impact of peer
victimization: exploring social-cognitive mediators of
depression. J Adolesc. 2010;33:615-623.
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3. Catterson J, Hunter SC. Cognitive mediators of the effect
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6. Crawford AM, Manassis K. Anxiety, social skills, friend-
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within friendships: nobody told me there’d be friends like
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ity as a predictor of social rejection and peer victimiza-
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depressive symptoms in adolescence: moderating effects
of mother, father, and peer emotional support. J Youth
Adolesc. 2011;40:531-544.
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BK. Negative affect in victimized children: the roles of
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peer relations in early adolescence: behavioral and cogni-
tive factors. J Abnorm Child Psychol. 2007;35:405-416.
12. Erath SA, Tu KM, El-Sheikh M. Socially anxious and
peer-victimized preadolescents: “doubly primed” for dis-
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13. Fredstrom BK, Adams RE, Gilman R. Electronic
and school-based victimization: unique contexts for
Study Culture
Sample Size and
Characteristics Measure
Effect Size
Reported
Effect Size Included
Emotional
Maladjustment Anxiety Depression Loneliness
Zhang et al (2009) Eastern 2603 children (M = 9.05±
0.53), Sex: 55.2% male
Self-report r — 0.38
r1 — 0.31
r2 — 0.45
r 0.32 —
r1 0.26 —
r2 0.38 —
r — 0.37
r1 — 0.32
r2 — 0.42
r0.36 — —
Zhou et al (2006) Eastern 274 children (M = NR), Sex:
52.2% male
Peer
nomination
r — 0.14
r — 0.15
Zhu and Liang
(2011)
Eastern 868 children (M = NR), Sex:
50.5% male
Self-report r— 0.23 — —
r— 0.36 — —
Zimmer-Gembeck
et al (2014)
Western 366 adolescents (M = 12.1),
Sex: 49.5% male
Self-report r — 0.4
r1 — 0.39
r2 — 0.51
r — 0.43
r1 — 0.37
r2 — 0.49
Zimmer-Gembeck
and Pronk
(2012)
Western 335 adolescents (M = 12.5),
Sex: 47.2% male
Self-report r2 0.55 —
r2 — 0.5
Peer
nomination
r2 — 0.07
r2 0.13 —
aM refers to mean age of samples. NR refers to no report. r represents the correlation between peer victimization and emotional
maladjustment; r1 represents the correlation between overt victimization and emotional maladjustment; r2 represents the correlation between
relational victimization and emotional maladjustment.
Appendix (continued)
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Wu et al 13
adjustment difficulties during adolescence. J Youth
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Acknowledgments
We are grateful to Qian Zhang, Ling Gong, and the faculty and
staff of the Research Center of Mental Health Education for
their generous support and precious advice. Furthermore, none
of this would have been possible without the help of those
individuals and organizations hereafter mentioned with grati-
tude: our school library and its staff, the library of Southwest
University and its staff.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
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... ch component with different antecedents and outcomes. For instance, compared with direct (physical and verbal) victimization, relational (indirect) victimization is linked more strongly to emotional maladjustment and internalizing problems (e.g., depression, anxiety, loneliness, sadness, worry, fear) and to low peer acceptance (Casper et al., 2020;L. Wu et al., 2015). Such bipartite conceptualizations have been the basis of widely cited metaanalyses (e.g., Casper & Card, 2017;Casper et al., 2020;Crick & Grotpeter, 1996;L. Wu et al., 2015). This rejection of a unidimensional approach is appropriate. ...
... e strongly to emotional maladjustment and internalizing problems (e.g., depression, anxiety, loneliness, sadness, worry, fear) and to low peer acceptance (Casper et al., 2020;L. Wu et al., 2015). Such bipartite conceptualizations have been the basis of widely cited metaanalyses (e.g., Casper & Card, 2017;Casper et al., 2020;Crick & Grotpeter, 1996;L. Wu et al., 2015). This rejection of a unidimensional approach is appropriate. ...
... However, a tripartite model better fits theory and empirical evidence (e.g., Marengo et al., 2019;Marsh et al., 2011;L. Wu et al., 2015). Furthermore, multidimensional conceptualizations of bullying typically include three dimensions, so adopting a tripartite model of victimization contributes to better integrating bullying and victimization research. To address the question of "How many components?" research findings have shown how victimization's three components (a) f ...
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Peer victimization at school is a worldwide problem with profound implications for victims, bullies, and whole-school communities. Yet the 50-year quest to solve the problem has produced mostly disappointing results. A critical examination of current research reveals both pivotal limitations and potential solutions. Solutions include introducing psychometrically sound measures to assess the parallel components of bullying and victimization, analyzing cross-national data sets, and embracing a social-ecological perspective emphasizing the motivation of bullies, importance of bystanders, pro-defending and antibullying attitudes, classroom climate, and a multilevel perspective. These solutions have been integrated into a series of recent interventions. Teachers can be professionally trained to create a highly supportive climate that allows student-bystanders to overcome their otherwise normative tendency to reinforce bullies. Once established, this intervention-enabled classroom climate impedes bully-victim episodes. The take-home message is to work with teachers on how to develop an interpersonally supportive classroom climate at the beginning of the school year to catalyze student-bystanders' volitional internalization of pro-defending and antibullying attitudes and social norms. Recommendations for future research include studying bullying and victimization simultaneously, testing multilevel models, targeting classroom climate and bystander roles as critical intervention outcomes, and integrating school-wide and individual student interventions only after improving social norms and the school climate.
... Rather, they contended that clarifying the extent to which different victimization components are distinct phenomena has important implications for theory, practice, and intervention. The Wu et al. (2015) meta-analysis also found that emotional maladjustment (e.g., depression, anxiety, loneliness) was more strongly correlated with relational victimization than overt victimization. However, both these meta-analyses and much of the research that they considered focused on two components, rather than the three components, of victimization (also see Crick & Grotpeter, 1996;Giesbrechtet al., 2011). ...
... In contrast to victimization research, the tripartite model (with verbal, relational, physical components) is widely recognized in bullying theory and research (e.g., Author1 et al., 2011;OECD, 2019a;Woods & Wolke, 2004;Wu et al. 2015). This tripartite model is also typical in more general VICTIMIZATION IN EDUCATIONAL SETTINGS 6 aggression research reviews (e.g., Archer, 2004). ...
... The Wu et al. (2015) meta-analysis also found that relational victimization was more strongly related to emotional maladjustment (e.g., depression, anxiety, loneliness) than was overt (physical and verbal) victimization. In their meta-analysis, Casper and Card (2017) similarly reported that compared to physical victimization, relational victimization in adolescence correlated more strongly with internalizing problems (sadness, worthlessness, depression, worry, fear). ...
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Current victimization studies and meta-analyses are based mainly on a unidimensional perspective in a few developed OECD countries. This provides a weak basis for generalizability over multiple victimization (relational, verbal, physical) components and different countries. We test the cross-national generalizability (594,196 fifteen-year-olds; 77 countries) of competing victimization models. In support of our three-component model, differentiating the multiple components of victimization facilitated understanding: gender differences (girls experience less physical and verbal victimization and stronger anti-bullying attitudes, but relational differences are small); paradoxical anti-bullying attitudes (physical victims have less –not more--anti-bullying attitudes); and well-being (policy/practice focuses primarily on physical victimization, but verbal and relational victimization effects are larger). These key findings provide theoretical advances with implications for policy, practice, and intervention.
... Moreover, the association of peer victimization with depressive symptoms may vary across sociodemographic backgrounds. Evidence has shown that girls experienced more psychological problems (e.g., depressive symptoms) from victimization than boys (Fredrick et al., 2021;Wu et al., 2015), but others showed victimized boys were more likely to experience depressive symptoms compared with those who reported no victimization (Rothon et al., 2011). Liao et al. (2022)'s meta-analytic study found that the relationship between peer victimization and depressive symptoms was stronger in children younger than 12 years old, whereas Wu et al. (2015)'s meta-analytic study found a stronger relationship in adolescents older than 13 years old. ...
... Evidence has shown that girls experienced more psychological problems (e.g., depressive symptoms) from victimization than boys (Fredrick et al., 2021;Wu et al., 2015), but others showed victimized boys were more likely to experience depressive symptoms compared with those who reported no victimization (Rothon et al., 2011). Liao et al. (2022)'s meta-analytic study found that the relationship between peer victimization and depressive symptoms was stronger in children younger than 12 years old, whereas Wu et al. (2015)'s meta-analytic study found a stronger relationship in adolescents older than 13 years old. In addition, children or adolescents with low socio-economic status may be at high risk for peer victimization and depressive symptoms (Jansen et al., 2012). ...
Article
Peer victimization is detrimental to child mental health. Research has indicated a reciprocal relationship between peer victimization and mental health problems. Yet limited evidence was from children and adolescents in China. The present study used the random intercepts cross‐lagged panel model (RI‐CLPM) to examine both between‐person and within‐person associations between peer victimization and depressive symptoms among Chinese children and adolescents. Participants were 1205 Chinese students (Mage = 11.27 years; ranged from 9 to 15 years; SD = 1.75; 55% boys) who completed four surveys (Time 1 to Time 4) between 2017 and 2019 on demographics, peer victimization, and depressive symptoms. At the between‐person level, peer victimization was positively associated with depressive symptoms. Controlling for between‐person effects, RI‐CLPM suggested positive within‐person effects from peer victimization to depressive symptoms across adjacent waves. The model also suggested a positive within‐person effect from Time 2 depressive symptoms to Time 3 peer victimization. The multi‐group analysis showed that these effects did not differ by gender, age, or subjective socioeconomic status. Peer victimization and depression appear to be reciprocally related at the transitioning period between late childhood and early adolescence in Chinese students. Mental health interventions should attend to peer victimization for children and adolescents in China.
... Siswa yang menjadi korban agresi relasional cenderung mengalami depresi, kecemasan, kesulitan hubungan sosial, dan ide bunuh diri (Prinstein et al., 2001). Beberapa faktor risiko yang dikaitkan dengan agresi relasional, seperti: pembohongan (Wu et al., 2015;Zimmer-Gembeck & Pronk, 2012) dan perbuatan dari agresi relasional dikaitkan dengan gejala depresi dan kecemasan (Card et al., 2008). Untuk itu perlunya alat untuk mengukur perilaku agresi relasional siswa, agar guru bimbingan dan konseling dapat menginterpretasi lebih awal dalam mencegah agresi relasional di sekolah. ...
... relasional cenderung mengalami depresi, kecemasan, kesulitan hubungan sosial, dan ide bunuh diri (Prinstein et al., 2001). Beberapa faktor risiko yang dikaitkan dengan agresi relasional, seperti: pembohongan (Wu et al., 2015;Zimmer-Gembeck & Pronk, 2012) dan perbuatan dari agresi relasional dikaitkan dengan gejala depresi dan kecemasan (Card et al., 2008). Selain itu, berbagai faktor risiko sosial atau interaksi remaja dengan orangtua terkait dengan keterlibatan mereka dalam agresi relasional, seperti prosedur keluarga dan pengasuhan (Voulgaridou & Kokkinos, 2020). ...
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This study aims to validate by measuring the psychometric properties of the Indonesian version of the Relational Aggression (RA) scale. The study used a survey method and was collected from December 2019 to January 2020 and involved 241 participants in Indonesia (14 to 18 years). In this study the Rasch model was used to measure the psychometric properties of 17 RA items, with the help of WINSTEPS 3.73. The results of this study indicate that RA fulfills the psychometric measurement aspect by providing evidence as a valid and reliable instrument, with a very good item reliability value (.98) and sufficient person reliability (.75), and a Cronbach alpha value (KR-20) of (.81), meaning that the quality of the items is very good for revealing relational aggression. Furthermore, the results are reinforced by the Principal Component Analysis (PCA) value of the residual of 45.2%, meaning that the items in RA are representative for measuring relational aggression. The implications of this RA research can be accepted by researchers for collecting data or information related to the problem of relational aggression in Indonesia.
... In the educational field, teachers strive to instill values in students, work on emotional education (Wu et al., 2015), and carry an intercultural education since, as stated by Sánchez and Vargas (2017), an education-oriented toward interculturality is ideal for achieving a respectful and peaceful coexistence and a cohesive society. However, conflicts continue to be frequent in schools and, in many cases, lead to violence between equals in which all students take part, either as aggressors, victims, or witnesses (Garaigordobil and Oñederra, 2010). ...
... The consequences that cyberbullying causes are serious for all those involved. Although it seems that the victim should be the only one affected, these behaviors also negatively influence aggressors and witnesses since they are at risk of suffering psychosocial and psychopathological imbalances in adolescence and their adult life (Ostrov and Kamper, 2015;Wu et al., 2015;Carrascosa et al., 2016;Sidera et al., 2021). A possible and the most severe consequence of bullying and cyberbullying is suicide, and becoming criminals or aggressors in the relatively near future (Nocito, 2017;Barlett et al., 2021;Martínez-Ferrer et al., 2021). ...
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The development of Information and Communication Technologies has favored access to technological resources in adolescents. These tools provide access to information that can promote learning. However, they can also have a negative effect against people, as they can be used with other functionality, in which cyberbullying situations are caused during the interactions that arise when using social networks. The objective of this study was to determine the predictive value of the role of cyberbullying victims based on variables related to other roles involved in cyberbullying and bullying (aggressors and witnesses), as well as personal characteristics (sex and age), contextual characteristics (type of educational school in which they are attending) and positive teamwork habits. (cooperation, responsibility, dialogue, listening, respect). Information was collected from 227 students of the educational stages of Primary Education and Secondary Education, aged between 11 and 15 years, in a city with a high index of cultural diversity. The step-by-step technique was used to build the regression model. The results indicate that the model has a good goodness of fit coefficient (adjusted R ² : 0.574; p < 0.001). The role of cyberbully is the most important predictive variable of the role of the victim in cyberbullying and, to a lesser extent, the role of the witness in cyberbullying, the role of the witness in bullying, and the role of the victim of bullying. The role of the bullying aggressor and the variables sex, age, type of educational center, and teamwork habits are excluded in the predictive model.
... Of note, the ventral striatum is preferentially engaged in emotional processes and its dysregulation can lead to anxiety (Lago et al., 2017). The link between BV and anxiety is well noted in the literature and supported by meta-analytic findings (Reijntjes et al., 2010;Wu et al., 2015;Moore et al., 2017) and longitudinal studies (Takizawa et al., 2014;Sentse et al., 2017;Drazdowski et al., 2021). Silk et al. (2014) also has shown that reactivity of the ventral striatum (nucleus accumbens) and insula is moderated by depression in adolescence. ...
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Bullying victimization is a form of psychological stress that is associated with poor outcomes in the areas of mental health and learning. Although the emotional maladjustment and memory impairment following interpersonal stress are well documented, the mechanisms of complex cerebral dysfunctions have neither been outlined nor studied in depth in the context of childhood bullying victimization. As a contribution to the cross-disciplinary field of developmental psychology and neuroscience, we review the neuropathophysiology of early life stress, as well as general psychological stress to synthesize the data and clarify the versatile dynamics within neuronal networks linked to bullying victimization. The stress-induced neuropsychological cascade and associated cerebral networks with a focus on cognitive and emotional convergence are described. The main findings are that stress-evoked neuroendocrine reactivity relates to neuromodulation and limbic dysregulation that hinder emotion processing and executive functioning such as semantic cognition, cognitive flexibility, and learning. Developmental aspects and interacting neural mechanisms linked to distressed cognitive and emotional processing are pinpointed and potential theory-of-mind nuances in targets of bullying are presented. The results show that childhood stress psychopathology is associated with a complex interplay where the major role belongs to, but is not limited to, the amygdala, fusiform gyrus, insula, striatum, and prefrontal cortex. This interplay contributes to the sensitivity toward facial expressions, poor cognitive reasoning, and distress that affect behavioral modulation and emotion regulation. We integrate the data on major brain dynamics in stress neuroactivity that can be associated with childhood psychopathology to help inform future studies that are focused on the treatment and prevention of psychiatric disorders and learning problems in bullied children and adolescents.
... These high levels may reflect the increased frequency of cyber-bullying in young people associated with symptoms of depression suicide ideation, suicide attempts (266). Humiliation in terms of relational victimization has shown a linear correlation with loneliness, symptoms of depression and anxiety in adolescents, with higher levels in girls (267). ...
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El objetivo de esta revisión sistemática es buscar y analizar estudios publicados respecto al autoconcepto, bullying, y educación física, en los últimos cinco años. Se lleva a cabo un proceso exhaustivo de búsqueda utilizando la metodología PRISMA, mediante las bases de datos WOS y ERIC en el cual se han seleccionado un total de 12 artículos en inglés y español. Para ello se han seguido distintos criterios de inclusión y exclusión Los resultados muestran que desde la mejora del AC se reduce las situaciones de BU en el alumnado. Se concluye que la mejora del autoconcepto a través de las clases de Educación Física disminuye las situaciones de bullying.
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Background: Bullying, as one of the unsolved problems in schools, leads to undesirable consequences. Effective factors associated with bullying, like moral disengagement, are crucial. However, no qualitative study has been conducted to build a model for moral disengagement and bullying. Aims: Identifying fundamental, procedural, and consequential factors of moral disengagement in bullying. Method: The study was qualitative, based on grounded theory. The statistical population included all male students of middle and high schools of the Abhar city. 17 students and a focus discussion group with the average age of 15.5 were selected through purposive sampling in the 2018-19 academic year. The method was semi-structured interviewing. Data analysis was performed using the Corbin and Straus methodology (2008) and the ATLAS.ti 8 software. Results: From initial 630 open codes, 19 secondary subjects and 7 main subjects were obtained. Results showed that the core category of beliefs and functional attitude to bullying are influenced by fundamental factors including determinant experiences, violent atmosphere, and bullying, and procedural factors including weak emotional perception, dysfunctional social perception, and externalization. Conclusions: Fundamental and procedural factors and related matters result in leveraging the moral disengagement mechanism and perpetrating bullying. Key Words: Bullying, moral disengagement, adolescent boys.
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Adolescence is marked by increases in stressful life events. Although research has demonstrated that depressed individuals generate stress, few studies investigate the generation of emotional victimization. The current study examined the effects of rumination and internalizing symptoms on experiences of peer victimization and familial emotional abuse. Participants were 216 adolescents (M = 14-years-old; 58% female; 47% African-American) who completed two assessments. Results showed that rumination predicted peer victimization and emotional abuse. The effect of rumination on emotional victimization is heightened for those who have higher levels of depression symptoms. That is, individuals who ruminate and who have depression symptoms experience increases in both peer emotional victimization and parental emotional abuse. This study builds upon prior research and indicates that rumination may be a stronger predictor of emotional victimization than symptoms of depression or anxiety. Identifying underlying mechanisms may yield targets for interventions aimed at addressing the chronic nature of depression.
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A majority of peer victimization research focuses on its associations with negative outcomes, yet efforts to understand possible protective factors that may mitigate these negative outcomes also require attention. The present study was an investigation of the potential moderating effect of prosocial behaviors on loneliness for youth who are peer victimized. Participants were fourth and fifth grade students (511 total; 49 % boys) who were primarily European American (43.4 %) and Hispanic (48.2 %). Structural Equation Modeling was used to test the interaction of prosocial behavior and peer victimization (relational and overt forms) on loneliness 1 year later. The results indicated that prosocial behavior significantly moderated the relationship between peer victimization (for the relational form only) and loneliness while controlling for levels of perceived peer support. A multi-group comparison by gender further indicated the moderation was significant for boys only. Potential implications for intervention/prevention efforts focused on developing children’s prosocial skills as a possible protective factor for relationally victimized youth are discussed.
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The present study sought to gain a better understanding of cyber bullying (i.e., the use of information technologies to inflict harm on another person) by examining its prevalence, its relationship with traditional bullying, and the relationship between bullying, anxiety, and depression in a sample of rural and ethnoracially diverse youth (N = 211; ages 10–13). Thirty-three percent of participants reported being victims of traditional bullying and 9 % reported perpetrating traditional bullying behavior. Seven percent of participants were victims of cyber bullying, 4 % reported that they participated in cyber bully behavior, and 2 % were both of victims and perpetrators of cyber bullying. Bullying victims reported significantly higher levels of anxiety and depression compared with non-victims and bullies endorsed significant anxiety and depression. Results suggest that while cyber bullying does occur in rural communities, it often co-occurs with traditional bullying. Additionally, a novel cyber bullying measure was developed and utilized, and information regarding its reliability and validity is included.
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Not all children react to being bullied in the same way. Some children may be more predisposed to depression when bullied than are other children. Using a G × E approach, this study examined the influence of a genetic polymorphism in the serotonin transport gene (5-HTTLPR) on the victimization-depression link. The validity of the diathesis-stress versus environmental susceptibility hypothesis was tested. A total of 157 adolescents (Mage = 12.21) took part in this study. For adolescents with the S,S/S,L variants, victimization was positively related to depression. No relationship between victimization and depression was found for children with the L,L variant. Findings further suggest that the influence of 5HTTLPR on the association between victimization and depression more closely follow an environmental susceptibility model.