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The Emotional Impact of Bullying and Cyberbullying on Victims: A European Cross-National Study

Volume 38, pages 342–356 (2012)
The Emotional Impact of Bullying and Cyberbullying on
Victims: A European Cross-National Study
Rosario Ortega1, Paz Elipe2, Joaquin A. Mora-Merch´
an3, M. Luisa Genta4, Antonella Brighi4,
Annalisa Guarini4, Peter K. Smith5, Fran Thompson5, and Neil Tippett5
1Department of Psychology, University of C ´
ordoba, C´
ordoba, Spain
2Department of Psychology, University of Ja ´
en, Ja´
en, Spain
3Department of Developmental and Educational Psychology, University of Seville, Seville, Spain
4Department of Psychology, University of Bologna, Bologna, Italy
5Department of Psychology, Goldsmiths, University of London, London, United Kingdom
Past research has demonstrated the effects of bullying can be severe and long term for the individuals involved. The main aim of
this study is to analyze the emotional impact on victims of traditional bullying, both direct and indirect forms, and of cyberbullying
through mobile phones and the Internet. A sample of 5,862 adolescents from three different countries, Italy (N =1,964), Spain
(N =1,671), and England (N =2,227), responded to a questionnaire that asked if they had experience of various forms of bullying,
and the consequent emotional impact. The results show that both traditional bullying and cyberbullying have a significant prevalence
in the samples. Emotional responses are linked to types of bullying. Analysis of answers identified specific emotional profiles for
the different types of bullying and cyberbullying. Direct bullying and cyberbullying via mobile phone showed similar profiles, and
also indirect bullying and cyberbullying using the Internet. Similarities and differences between profiles are discussed and some
hypotheses are presented to explain the results. In addition, school grade, gender, country, and severity of bullying episodes were
related to the specific emotional profiles of each type of bullying. Aggr. Behav. 38:342–356, 2012. C2012 Wiley Periodicals, Inc.
Keywords: cyberbullying bullying; emotions; impact; victims
Cyberbullying is usually defined as a form of bul-
lying that uses electronic means such as email, mo-
bile phone calls, text messages, instant messenger con-
tact, photos, social networking sites, and personal web
pages, with the intention of causing harm to another
person through repeated hostile conduct. This can
include forms of aggression such as humiliation, ha-
rassment, social exclusion, mockery, and unpleasant
comments [Smith et al., 2008]. After almost a decade
of research, it seems clear that cyberbullying has a
direct relationship with traditional forms of bullying.
Several studies have pointed out the links between
cyberbullying and traditional bullying, and the ten-
dency for students involved in cyberbullying also to
participate in episodes of face-to-face bullying [Frisen
and Slonje, 2010; Juvonen and Gross, 2008; Mora-
an et al., unpublished results; Raskauskas and
Stoltz, 2007; Smith et al., 2008]. Nevertheless, it is
also clear that, although linked, the two phenomena
each have their own features [Wang et al., 2009], as a
consequence of the means used.
The impact that traditional bullying has on the psy-
chological well being of victims has been described in
numerous studies [e.g., Arseneault et al., 2010; Frisen
and Bjarnelind, 2010; Gini and Pozzoli, 2009; Klomek
et al., 2008; Sch¨
afer et al., 2004]. The impact of
Contract grant sponsor: National Research Plan; Contract grant num-
ber: PSI2010-17246; Contract grant sponsor: Excellence Research Pro-
gram from Junta de Andaluc´
ıa; Contract grant number: SEJ-6156;
Contract grant sponsor: European Daphne Programme from Euro-
pean Union; Contract grant number: JLS/2096/DAP-1/241YC 30-
Correspondence to: Rosario Ortega, Department of Psychology, Fac-
ulty of Educational Sciences, University of Cordoba, Avda. San Al-
berto Magno, s/n 14071 Cordoba, Spain. E-mail:
Received 13 May 2011; Accepted 25 May 2012
Published online 10 July 2012 in Wiley Online Library (wileyonlineli- DOI: 10.1002/ab.21440
C2012 Wiley Periodicals, Inc.
Emotional Impact of Bullying and Cyberbullying 343
experiences of cyberbullying has been evaluated
in fewer studies; these have used two different
The first perspective has assessed the impact of cy-
berbullying by comparing its effects with those of
traditional bullying. The most common approach has
been to ask students about what forms of aggression
(face-to-face or online) seem more damaging. Most of
these studies [e.g., Smith et al., 2008; Staude-M¨
et al., 2009] have found that the impact depends on
the form of cyberbullying. Thus, there are types of
cyberbullying that are perceived as less harmful than
traditional bullying, such as insults and threats, while
other forms are considered more damaging, especially
those where images or videos are used and when there
is a perception of high risk of personal injury such as
blackmail. Perceptions can differ between countries
an et al., 2010], which indicate that the
impact of cyberbullying may depend on the cultural
importance given to social relationships established
in cyberspace.
The second perspective has analyzed the corre-
lates of cyberbullyingvictimization. The negative out-
comes these studies have found in relation to cyber-
victimization are not very different to those found
in relation to traditional bullying victimization [see
Tokunaga, 2010]. Some studies have found negative
effects on academic performance [Beran and Li, 2007;
Katzer et al., 2009; Patchin and Hinduja, 2006]. Psy-
chosocial problems such as depression, social anxiety,
and low levels of self-esteem have also been found
as correlates of cyberbullying victimization [Blaya,
2010; Didden et al., 2009; Juvoven and Gross, 2008;
Katzer et al., 2009; Ybarra, 2004]. Some studies have
assessed the emotional impact of cybervictimization.
Raskauskas and Stolz [2007] found that 93% of cy-
bervictims were negatively affected, reporting sad-
ness, hopelessness, depression, and anxiety. Katzer
and Fetchenhauer [2007] found that the emotional
responses of the victims of bullying in chatrooms
included anger (41%); upset (over 30%); frustration
(20%); vulnerability (15%); depression (11%), and fear
(8%). Cybervictimization has also been related to af-
fective disorders [Patchin and Hinduja, 2006; Topcu
et al., 2008; Ybarra, 2004].
Personal variables are important in understanding
why different victims show different emotional im-
pact. Those studied include perceived control and
threat, personality traits, levels of self-esteem, social
support, coping style, and the individual role (i.e., ex-
clusively victim as opposed to bully victim) [Catterson
and Hunter, 2010; Egan and Todorov, 2009; Hunter
and Borg, 2006; Hunter et al., 2004; Nabuzoka et al.,
2009; O’Moore and Kirkham, 2001; Salmivalli et al.,
1999; Schmidt and Bagwell, 2007; Ortega et al., 2009a;
Slee and Rigby, 1993].
There are also specific characteristics related to
the bullying incidents that have been associated with
emotional consequences on victims. Persistence of
episodes over time is related to an increased emo-
tional impact on mental health [Aluede et al., 2008;
Brighi et al., 2012; Dyer and Teggart, 2007]. Brighi
et al. [2012] have shown that the impact on victims’
self-esteem varies according to the intensity and kind
of bullying experienced, pointing out that the specific
form of aggression (i.e., direct or indirect) could be
another factor.
Also, the specific type of bullying could be related
with the emotional impact. Ortega et al. [2009b] ar-
gued that the emotional impact of cyberbullying is
similar to that produced by indirect bullying in its
traditional form (e.g., spreading nasty rumors; writ-
ing malicious notes). Gradinger et al. [2009] found
that cooccurrence of traditional and cybervictimiza-
tion was related to a higher risk for internalizing ad-
justment problems. Sontag et al. [2011] found that
combined victims of traditional and cyberaggression,
as well as those who were exclusively cybervictims
were more likely to be cyberaggressors themselves
compared to traditional victims or nonvictims.
However, only a few studies have analyzed and com-
pared the various emotional consequences for victims
of different types of bullying, both traditional and cy-
berbullying [Borg, 1998; Brighi et al., 2012; Gradinger
et al., 2009; Juvonen and Gross, 2008; Ortega et al.,
2009b; Sontag et al., 2011]. These studies have shown
that victims of different types of bullying, experience
different emotional responses.
The transactional theory of stress and coping
[Lazarus and Folkman, 1984] is a useful theoreti-
cal framework for understanding the origin of these
emotional differences. This theory proposes that the
way in which people cope with a stressful situation,
such as bullying, does not depend exclusively on the
event itself but also on how people appraise it. The
same event could lead to different reactions by dif-
ferent people. Nevertheless, previous studies about
victims have taken a variable-centered approach and
largely considered victims as a homogeneous group.
Such aggregation of data sources (from different vic-
tim groups) can lead to misrepresentation of findings,
as Schmitz [2000] has shown. In fact, a victims group
is shaped by unique individuals who show a number
of behavioral or psychological patterns. A person-
centered approach has been argued as having ecologi-
cal validity [Bergman and Magnusson, 1997; von Eye
and Bogat, 2006] and there is some empirical evidence
that person-oriented research can be useful above and
Aggr. Behav.
344 Ortega et al.
beyond variable-oriented research [von Eye and Bo-
gat, 2006].
The current study aims to assess the emotional
consequences of bullying on victims, by mixing a
person-centered approach and a variable-centered
approach. The person-centered approach allows us
to identify subgroups of victims, and the variable-
centered approach allows us to analyze the influence
of variables, whose importance in relation to victim-
ization has been shown by previous research, on these
This study investigated the emotional impact of tra-
ditional bullying and cyberbullying on victims, com-
paring three countries: Italy, Spain, and England.
This objective was operationalized through four spe-
cific aims:
(1) To report the prevalence of victimization for four
different types of bullying: traditional bullying
(direct and indirect) and cyberbullying (using mo-
bile phones and the Internet).
(2) To assess the emotional impact of the four types
of bullying on victims.
(3) To identify and characterize the emotional pro-
files or pattern of victims for each type of bully-
(4) To assess the relationship between variables
traditionally considered in the bullying field
and the emotional profiles; specifically, gender,
school grade, country, and frequency of the
The total sample was composed of 5,862 stu-
dents from three countries, Italy (N =1,964), Spain
(N =1,671), and England (N =2,227) (M =14.20-
years old, SD =1.77), distributed at three educa-
tional levels1: Year 8 (M =12.24, SD =0.53), Year
10 (M =14.34, SD =0.64), and Year 12 (M =16.38,
SD =0.67). Overall, 48.8% of participants were girls.
The Spanish sample was collected from seven sec-
ondary schools, selected according to a random pro-
cess from the area of Cordoba (five public and two
direct-grant secondary schools, from broadly aver-
age socioeconomic status). In Italy, students were re-
cruited from 39 public secondary schools of Emilia
Romagna (a region in the Center-North of Italy) in
particular the provinces of Bologna, Ferrara, and
1In Spain: first and third level of compulsory secondary school and
first level of high school. In Italy: second year of lower secondary
school and first and third year of upper secondary school.
ı. The schools were representative of the types
of school (lower and upper secondary schools: licei,
technical institutes, professional institutes) and were
located in areas with different socio-economic status.
In each school, all classes of corresponding age level
were recruited. In England, there were nine schools,
selected from London (three secondary) and a re-
gional city in the Midlands (six schools, three mid-
dle, and three secondary). The sample represented a
good socio-economic and cultural mix. Comparative
numbers from each year group were recruited in all
schools, although there were slightly fewer students
recruited from the oldest year group. Data were gath-
ered in late 2007 and early 2008.
The instrument used was the DAPHNE Question-
naire [Genta et al., 2012] that was developed within
the framework of the project “An investigation into
forms of peer–peer bullying at school in preadolescent
and adolescent groups: new instruments and prevent-
ing strategies.” This is a self-report instrument made
up of some preexisting questionnaires and other new
measures (for more detailed information on the full
questionnaire see Brighi et al., 2012; Genta et al.,
2012]. The information used in this study comes from
the “About bullying and cyberbullying” section. This
section collected information using a multiple-choice
format about student access to ICT (three items), and
four areas of bullying: direct bullying (five items), indi-
rect bullying (five items), cyberbullying using mobile
phones (12 items), and cyberbullying using the inter-
net (12 items). All bullying questions were related to
the last 2 months; this time frame is commonly used
since school terms are often organized in 3-month pe-
riods. Data were collected in the last month of term
and pupils could think about one complete term pe-
riod of regular attendance at school. In each bullying
area, questions included role played (victim, bully, or
both) and other contextual aspects such as emotions
and coping strategies. Only those items relevant to
this study are shown in the Appendix.
The original questionnaire was developed in En-
glish, and native speaker researchers of each coun-
try translated it to their language. Following Van de
Vijver and Hambleton’s [1996] recommendations, we
aimed to minimize cross-cultural bias. Construct and
method bias were minimized through the multilingual
composition and research expertise of the team mem-
bers (for an overview, see Smith, 2010]. To minimize
item bias, the definitions of bullying and cyberbul-
lying were included in the first part of the question-
naire (see Appendix). Regarding items related to emo-
tional impact, Mantel–Haenszel statistical tests were
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 345
run to check possible differential item functioning
depending on countries. The results showed no differ-
ences depending on countries in the majority of the
emotional items. However, there were some excep-
tions: the item “it does not bother me,” as an answer to
the impact of the four types of bullying, showed differ-
ences between England and Spain; the item “alone”
showed differences between England and Italy. These
differences should be taken in account in interpreting
Peer-victimization. Victims were identified by
answers to the direct questions about victimization;
Q1, Q6, Q11, and Q23 in the Appendix. Students who
answered that they had suffered bullying or cyberbul-
lying at least once or twice in the last 2 months were
considered victims. When the victim reported having
suffered bullying only once or twice it was consid-
ered occasional; when they reported having suffered
bullying more frequently, it was considered frequent
Emotions. The emotional impact on victims was
assessed through questions Q2, Q7, Q13, and Q25
in the Appendix. In all cases the victims could tick
one or more of the emotions listed. The answer op-
tion “other (please write here)” was not coded in the
current analyzes. However, these answers were only a
small percentage of the total (1.5% in direct bullying;
2% indirect bullying; 0.5% mobile cyberbullying; and
0.6% internet cyberbullying).
The concordance between the peer-victimization
answers and emotions referred to was analyzed in
order to check the validity of answers. In the four
types of bullying the percentage of inconsistencies,
that is students who said they had not been bullied
but ticked at least one emotion as an impact of being
bullied, was very low (eight students, 0.2% of victims,
in direct and indirect bullying; and only one student
in mobile phone and Internet cyberbullying, less than
0.1% of victims).
Questionnaires were administered in school time
during lessons. Before completion, researchers de-
fined traditional bullying and cyberbullying follow-
ing the descriptions given in the questionnaire (see
Appendix). Participants were asked to answer hon-
estly and were reminded that their responses would
remain anonymous. The researchers emphasized that
participation was voluntary, and gave students the
opportunity to leave if they so wished. Prior consent
was obtained from parents and schools. The appro-
priate institutional ethics committees in each country
approved the procedures.
Data Analysis
To analyze the relationships between prevalence of
victimization and country, and emotions and coun-
try, we ran chi-square contrasts and, when appropri-
ate, two proportion ztests. Bonferroni correction was
used to determine the level of significance because
multiple comparisons were made.
A hierarchical cluster analysis using Ward’s method
with squared Euclidean Distance for binary data was
used to group individuals according to the emotional
impact experienced. We proceeded in two phases
to decide the most accurate cluster solution. In the
first step, we examined the distance between clus-
ters for each consecutive step. The cluster solution
was selected when the values in the cluster coeffi-
cient changed significantly, because this change would
show that if we added the next case to the clus-
ter a decrement in the homogeneity of such clus-
ter would happen. Once the more adequate cluster
solutions were decided, we analyzed the dendro-
gram to select the most suitable. A rescaled dis-
tance cluster combination with 15 as a maximum
was used. To facilitate comparison between clusters,
they were arranged in order of size from large to
small. To describe the clusters we also show the me-
dian, to give an idea of the amount of emotions re-
ferred by the majority of students that compose each
Finally, we ran a logistic regression to analyze the
impact of gender, school grade, country, and fre-
quency of aggression in classifying participants in
emotional clusters.
Missing data ranged from 0.1% for school grade to
2.3% for emotional consequences of direct bullying on
victims; this was below 5%, the strict cut-off suggested
by Schafer [1999].
The statistical analyzes were run with software
SPSS version 15.0.
Prevalence of Victimization of Traditional
Bullying and Cyberbullying
Table I shows the percentage of occasional and fre-
quent victims in each country. In all three countries,
the proportion of victims of traditional bullying, di-
rect and indirect, is higher than the proportion of
cyberbullying victims, using mobile phone or the In-
We also examined if some victims were suffering
multivictimization, that is, victims of more than one
type of bullying. Taking in account all types of bully-
ing, 60.2% of the total number of victims (1,017) were
Aggr. Behav.
346 Ortega et al.
TABLE I. Prevalence of Victimization by Country, Type of
Bullying and Frequency of the Aggression
England Italy Spain
(A) (B) (C)
Direct bullying
(N =5,844)a
Nonvictims 81.3% 85.0%
4.3% 3.2%
Indirect bullying
(N =5,821)a
Nonvictims 79.9% 77.0% 84.2%
14.0% 15.7%
Mobile phone
(N =5,776)a
Nonvictims 95.9%
90.5% 95.7%
2.1% 7.3%
(N =5,793)a
Nonvictims 93.4% 92.7% 92.5%
4.0% 5.4% 6.2%
1.9% 1.3%
Notes. Results are based on two-sided tests with significance level 0.05.
For each significant pair, the letter of the category with the smaller
column proportion appears under the category with the larger column
aThe differences in N are because of missing data.
victims of exclusively one type of bullying; 28% (473)
were victims of two types; 8.6% (145) of three types;
and 3.2% (54) of all four types.
The relationships between victimization and
country were significant for all types of bul-
lying: (χ2DIRECT BULLYING [4] =56.06,
χ2[4] INDIRECT BULLYING =37.07, χ2[4]
.001, χ2[4] INTERNET CYBERBULLYING =18.20, P<
.01). The contrasts tests showed a significantly higher
percentage of non victims of traditional bullying
(direct and indirect) in Spain, compared to Italy
and England; and a higher prevalence of frequent
victims of direct bullying in England, than in
Spain and Italy. The prevalence of frequent vic-
timization in indirect bullying and mobile phone
cyberbullying was lower in Spain than in Italy or
England, with cybervictimization through mobile
phone especially high in Italy. For cyberbullying
through the Internet, occasional victimization was
highest in Spain, but frequent victimization was
Emotional Impact on Victims
The percentage of pupils that reported experienc-
ing the range of emotions described in the question-
naire as a consequence of being bullied was analyzed
and compared across countries. Table II shows these
percentages, by country, for traditional forms of bul-
lying, direct and indirect; and Table III shows the
corresponding data for cyberbullying, through mo-
bile phone and Internet.
The emotion most often reported by pupils, for
both traditional bullying and cyberbullying, was feel-
ing “angry” (with the exception of Spanish cybervic-
tims). For the less frequently reported emotions, there
was more variation depending on country and type
of bullying. However, victims reporting feeling “de-
fenseless” was consistently the least chosen item for
cyberbullying through Internet.
Contrasts tests showed some variations of reported
emotions in the three countries, see Tables II and
III. There were few differences between “angry” and
“embarrassed” responses across type of bullying phe-
nomena, and also in the “not bothered” responses as
regards traditional bullying, and the “worried” and
“afraid” responses as regards cyberbullying. English
victims were generally the most affected, particularly
compared to the Italian sample. Spanish victims were
the least affected, particularly in comparison to En-
glish victims for cyberbullying.
Emotional Profiles of Victims
We used a cluster analysis in order to obtain emo-
tional profiles. The results are presented for each of
the four kinds of bullying.
Direct bullying. A solution of three clusters was
adequate in the case of direct bullying. The first clus-
ter was composed of 620 individuals (76.3% of vic-
tims), the second of 148 individuals (18.2%), and the
third of 45 pupils (5.5%). These clusters are shown in
Figure 1.
The first cluster is composed of students that re-
ported some negative emotions, but not a lot of them
at the same time; no more that 25% of the group
reported any emotion, with the exception of being
“angry,” reported by almost half; being “upset” re-
ported by almost 40%; and being “worried” reported
by 27%.
The second cluster is composed of students that
reported not being bothered by the bullying situation,
with only a few reporting any negative emotions such
as being “embarrassed,” “angry” or “upset.”
The third cluster is characterized mainly by students
that reported feeling a lot of negative emotions at
the same time. More than 80% reported almost all
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 347
TABLE II. Percentage of Victims of Traditional Bullying that Reported Each Emotion, in the Total Sample and by Country
Direct bullying (N =845) Indirect bullying (N =1,114)
England Italy Spain England Italy Spain
(A) (B) (C) Total (A) (B) (C) Total
Not bothered 20.0 17.7 23.4 20.0 23.0 25.1 26.2 24.5
Embarrassed 26.4 24.5 25.7 25.7 22.3
16.9 11.7 17.8
Angry 48.2
Upset 43.5
17.5 34.8 32.3
13.6 23.4
Stressed 34.7
10.9 10.5 22.4 29.7
10.8 9.0 17.7
Worried 26.9
25.7 15.8 24.3 19.5
10.8 19.1
Afraid 24.0
10.9 15.2 18.1 10.9
4.75.5 7.3
Alone 19.1
7.513.5 14.315.5
13.3 7.4 12.8
Defenseless 20.0
12.5 11.7 16.0 12.5
8.7 5.19.3
Depressed 26.9
7.9 17.0
18.9 21.6
9.6 14.8 15.4
Notes. The more and least selected categories for each type of bullying are shown in boldface. Results are based on two-sided tests with significance
level 0.05. For each significant pair, the letter of the category with the smaller column proportion appears under the category with the larger column
the negative emotions, with the exception of feeling
“defenseless” that was reported by 62%, and feeling
“alone,” reported by 58%.
On the basis of these characteristics, we named the
first cluster “moderately affected victims,” the sec-
ond “non affected victims” and the third “strongly
affected victims.” The mean number of emotions re-
ported by each victim was, in the “moderately af-
fected victims” cluster, from 1 to 7 (Me =2); in
the “non affected victims” from 1 to 5, (Me =1);
TABLE III. Percentage of Victims of Cyberbullying that Reported Each Emotion, in the Total Sample and by Country
Mobile phone Cyberbullying (N =338) Internet Cyberbullying (N =406)
England Italy Spain England Italy Spain
(A) (B) (C) Total (A) (B) (C) Total
Not bothered 18.0 25.3 35.8
25.4 29.6 34.8 43.9
Embarrassed 12.4 9.3 6.0 9.5 17.6
8.5 6.5 11.1
Angry 39.3 35.7 31.3 35.8 35.2 36.2 29.3 33.7
Upset 25.8
13.2 22.4 18.3 31.7
9.2 17.1 19.5
Stressed 23.6
10.4 7.5 13.3 19.0
5.7 8.9 11.3
Worried 23.6 15.9 23.9 19.5 17.6 13.5 15.4 15.5
Afraid 19.1 10.4 13.4 13.3 16.9 12.1 8.9 12.8
Alone 16.9
6.0 7.5 9.2 16.9
2.10 7.3 8.9
Defenseless 13.5
3.3 13.4
8.0 12.7
2.8 5.7 7.1
Depressed 18.0
6.0 13.4 10.7 17.6
2.8 10.6
Notes. The more and least selected categories for each type of bullying are shown in boldface. Results are based on two-sided tests with significance
level 0.05. For each significant pair, the letter of the category with the smaller column proportion appears under the category with the larger column
Aggr. Behav.
348 Ortega et al.
Fig. 1. Individuals that reported each emotion by cluster in direct
Fig. 2. Individuals that reported each emotion by cluster in indirect
and in the “strongly affected victims” from 4 to 10,
(Me =8).
Indirect bullying. A two-cluster solution was
the most appropriate for indirect bullying. The first
cluster was composed of 816 pupils (76.6%) and the
second cluster of the remaining 250 victims (23.4%).
These clusters are shown in Figure 2.
The first cluster is composed of a majority of vic-
tims who felt “angry,” with about a quarter reporting
being “upset,” “embarrassed,” “stressed,” “worried,”
or “depressed”. The number of emotions reported
for each individual of this cluster was from 1 to 10
(Me =2).
The second cluster is composed of victims char-
acterized by not feeling bothered. In this case, the
number of emotions reported was from 1 to 4
(Me =1).
Cyberbullying using mobile phone. As for di-
rect bullying, a three-cluster solution was the most
suitable. The first cluster was formed of 221 victims
(72.2%), the second cluster of 67 (21.9%), and the
third cluster of 18 (5.9%). These clusters are shown in
Figure 3.
Fig. 3. Individualsthat reported each emotion by cluster in cyberbullying
through mobile phone.
As with direct bullying, the first cluster consisted
of “moderately affected victims” with the majority
reporting feeling “angry,” with some (less than 25%)
also reporting other negative emotions. The number
of emotions reported by each victim was from 1 to 5
(Me =1).
The second cluster was of “non affected victims,”
formed exclusively by victims that reported not being
bothered and reporting no negative emotions.
The third cluster was of “strongly affected victims,”
of whom 100% reported feeling “depressed” and more
than half all the other negative emotions too, with the
exception of embarrassment, which was reported by
about a third. The number of emotions reported for
each victim was from 3 to 10 (Me =6).
Cyberbullying using the Internet. Two cl u s -
ters were found in cyberbullying using the Internet.
The first cluster consisted of moderately affected 263
victims (68.5%), more than half of who reported feel-
ing “angry.” The number of emotions reported for
each victim was from 1 to 10 (Me =1).
The second cluster was made up of 121 victims
(31.5%), all of who reported not feeling bothered,
with no other negative emotions.
These two clusters are shown in Figure 4.
Gender, School Grade, Country, Frequency of
Victimization, and Emotional Profiles of
Logistic regressions were run, using as depen-
dent variables the clusters previously obtained, bi-
nary to indirect and internet bullying and multinomial
to direct and mobile phone bullying. These showed
different levels of impact of these variables de-
pending on the type of bullying. All the regression
models obtained for the different types of bullying
were significant, but Nagelkerke’s R2, a measure to
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 349
Fig. 4. Percentage of individuals that reported each emotion by cluster
in cyberbullying through the Internet.
estimate the strength of the relationship, varied be-
tween them.
Direct bullying. The model was significant
(2LLG =193.36, χ2[12, 807] =84.76, P<.001) and
explained 13.4% of the variance in clusters (Nagelk-
erke’s R2). All variables included, gender, school
grade, country, and frequency of victimization, were
significant. Specifically, moderately affected victims,
compared to non affected, were more likely to be
younger pupils compared to older ones, female than
male, and frequent rather than occasional victims
(see Table IV). Strongly affected victims, compared to
non affected, were more likely to be younger, female,
and frequent victims. Also, English victims were more
likely to be strongly affected.
Indirect bullying. The model was significant
(2LLG =163.75, χ2[6, 1,061] =27.97, P<.001),
and Nagelkerke’s R2was 0.039. The significant vari-
ables were gender, school grade, and frequency of vic-
timization, but not country. Specifically, we found that
being affected was more likely for girls, for youngest
rather than older pupils and for frequent rather than
occasional victims (see Table V).
Mobile phone cyberbullying. The model was
significant (2LLG =142.23, χ2[12, 304] =28.25,
P=.005), and explained about 11.5% of the variance
in clusters (Nagelkerke’s R2). Specifically, we found
that English victims, compared to Spanish ones, were
more likely to be moderately and strongly affected
victims than non affected. Also, strongly affected vic-
tims, compared to nonaffected, were younger and
more often frequent than occasional victims (see
Table VI).
Internet cyberbullying. The model was signifi-
cant (2LLG =115.16, χ2[6, 380] =31.86, P<.001),
and explained about 11.3% of the variance. The sig-
nificant variables were country, gender, and frequency
of victimization, but not school grade. Specifically,
affected victims were more likely to be English, girls,
and frequently victimized (see Table VII).
TABLE IV. Logistic Regression Parameters for Emotional Profile of Victims of Direct Bullying
ProfileaβSE Wald df Sig. Exp. (β)Exp.(β)
Interceptb1.63 0.35 22.21 1 <.001
Italy 0.36 0.26 1.89 1 .17 1.43 0.86, 2.36
England 0.11 0.24 0.20 1 .65 1.11 0.70, 1.77
Spain 0d0
8 years 0.58 0.25 5.50 1 .02 1.79 1.10, 2.91
10 years 0.69 0.27 6.63 1 .01 2.00 1.18, 3.38
High School 0d0
Male 0.59 0.20 8.82 1 <.005 0.55 0.37, 0.82
Female 0d0 1.22, 2.68
Occasional 0.68 0.22 9.58 1 <.005 0.51 0.33, 0.78
Frequent 0d0 1.28, 3.03
Interceptc0.54 0.73 0.56 1 .46
Italy 0.57 0.95 0.36 1 .55 0.56 0.09, 3.63
England 1.83 0.65 8.08 1 <.005 6.25 1.77, 22.17
Spain 0d0
8 years 0.21 0.44 0.22 1 .64 0.81 0.34, 1.93
10 years 1.01 0.58 3.04 1 .08 0.36 0.12, 1.13
High School 0d0
Male 1.11 0.37 9.12 1 <.005 0.33 0.16, 0.68
Female 0d0 1.48, 6.20
Occasional 1.52 0.37 16.56 1 <.001 0.22 0.11, 0.46
Frequent 0d0 2.19, 9.45
aThe reference category is: not affected victims. bModerately affected. cStrongly affected. dThis parameter is set to zero because it is redundant.
Aggr. Behav.
350 Ortega et al.
TABLE V. Logistic Regression Parameters for Emotional Profile of Victims of Indirect Bullying
Emotional 95% CI
profileaβSE Wald df Sig. Exp. (β)forExp.(β)
Interceptb1.60 0.24 43.52 1 <.001
Italy 0.01 0.19 0.00 1 .97 0.99 0.68, 1.44
England 0.13 0.19 0.47 1 .50 1.14 0.78, 1.67
Spain 0c0
8 years 0.43 0.19 5.37 1 .02 1.54 1.07, 2.21
10 years 0.02 0.18 0.01 1 .93 0.98 0.69, 1.41
High School 0c0
Male 0.31 0.15 4.46 1 .04 0.73 0.55, 0.98
Female 0c0 1.37 1.02, 1.82
Occasional 0.64 0.18 12.95 1 <.001 0.53 0.37, 0.74
Frequent 0c0 1.90 1.34, 2.69
aThe reference category is: not affected victims. bAffected victims. cThis parameter is set to zero because it is redundant.
TABLE VI. Logistic Regression Parameters for Emotional Profile of Victims of Mobile Phone Cyberbullying
Emotional 95% CI
profileaβSE Wald df Sig. Exp (β)forExp.(β)
Interceptb1.15 0.47 5.94 1 .02
Italy 0.23 0.35 0.43 1 .51 1.26 0.63, 2.51
England 1.10 0.47 5.39 1 .02 3.01 1.19, 7.61
Spain 0d0
8 years 0.02 0.37 0.01 1 .94 0.97 0.47, 2.00
10 years 0.11 0.35 0.10 1 .76 1.12 0.56, 2.23
High School 0d0
Male 0.32 0.29 1.23 1 .27 0.72 0.41, 1.28
Female 0d0
Occasional 0.29 0.35 0.71 1 .40 0.75 0.38, 1.48
Frequent 0d0
Interceptc1.47 1.03 2.07 1 .15
Italy 0.68 0.82 0.67 1 .41 0.51 0.10, 2.56
England 1.48 0.84 3.15 1 .08 4.41 0.86, 22.70
Spain 0d0
8 years 1.72 0.86 3.98 1 .05 5.58 1.03, 30.17
10 years 0.87 0.92 0.92 1 .34 2.41 0.40, 14.53
High School 0d0
Male 0.89 0.61 2.14 1 .14 0.41 0.13, 1.35
Female 0d0
Occasional 1.23 0.60 4.18 1 .04 0.29 0.09, 0.95
Frequent 0d0
aThe reference category is: not affected victims. bModerately affected. cStrongly affected. dThis parameter is set to zero because it is redundant.
TABLE VII. Logistic Regression Parameters for Emotional Profile of Victims of Internet Cyberbullying
Emotional 95% CI
profileaβSE Wald df Sig. Exp. (β)forExp.(β)
Interceptb1.21 0.38 10.07 1 <.005
Italy 0.38 0.28 1.93 1 .17 1.47 0.86, 2.51
England 0.81 0.30 7.41 1 .01 2.25 1.26, 4.04
Spain 0c0
8 years 0.19 0.29 0.43 1 .51 1.21 0.68, 2.16
10 years 0.03 0.28 0.01 1 .92 1.03 0.59, 1.79
High School 0c0
Male 0.79 0.23 11.55 1 <.005 0.45 0.29, 0.72
Female 0c0
Occasional 0.75 0.29 6.90 1 .01 0.47 0.27, 083
Frequent 0c0
aThe reference category is: not affected victims. bAffected victims. cThis parameter is set to zero because it is redundant.
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 351
Our first aim was to establish a clear idea of the
prevalence of different types of traditional bullying
and cyberbullying. The data collected show clearly
that traditional bullying and cyberbullying are present
in a significant way in all of the three countries. Some
national differences were found, with the Spanish
sample having lowest rates of victimization, especially
in the case of face-to-face bullying. The English sam-
ple showed higher prevalence of frequent victimiza-
tion overall compared to the Spanish sample. Italy
showed a significant higher percentage of victims of
direct, indirect, and mobile phone bullying compared
to Spain. These data are consistent with previous
works in the bullying field (see Fonzi et al., 1999]
and also with some recent researches on cyberbullying
(see Mora-Merch´
an et al. 2010]; however, differences
in definitions, instrument and methodology used to
assess these phenomena across studies make the com-
parisons of results difficult to interpret. In general, it
was in Internet cyberbullying where fewer differences
were found, with the percentages of victims across
countries quite similar.
We propose two different hypotheses to explain
these differences: The first explanation is that there is
a different level of sensitivity in each country towards
these bullying phenomena, probably related to edu-
cational campaigns developed in each country and
to variations in the perception of traditional bully-
ing and cyberbullying [Nocentini et al., 2010; Smith
et al., 2002], such that, depending on the country, stu-
dents associate different levels of severity and social
acceptance to episodes of bullying. The second expla-
nation is that there are differences, not in sensitivity
to perceive bullying but in the nature of the bully-
ing itself. In this case, the differences could be related
to the factors underlying relationships established in
schools, maybe due to specific educational initiatives
or to other social factors in each country. However,
participant countries were not selected based on such
factors, but more on convenience, so this hinders the
extent to which we can meaningfully explore the im-
pact of such factors on our cross-country differences.
In addition, neither of these explanations helps us to
understand why there are differences in most types of
bullying but not in Internet cyberbullying. Is this lat-
ter kind of bullying more “global,” and thus similar
among countries? Further studies considering these
variables in their design may help us to get a better
explanation about this. However, the variations found
between the three countries studied, lead us to think
that although we are dealing with phenomena that
occur in all countries, the socio-cultural differences
between them are important in understanding how
victimization appears and develops.
Our second aim was the analysis of emotional
responses. We found that emotional responses are
linked to the type of bullying experienced. Across all
types of bullying, and all three countries, the most
common reported emotion was anger, with the only
exception of Spanish cybervictims who mostly re-
ported not feeling bothered. These results are partly
consistent with those of Borg [1998] concerning tradi-
tional bullying, and Katzer and Fetchenhauer [2007]
concerning cyberbullying through chat rooms; both
these studies reported about 40% of victims who
felt angry. This finding can be interpreted from the
social-functionalist perspective of emotions. Within
this framework, previous research has pointed out
that anger is a reaction to violations of autonomy,
and disregard for the personal rights or freedoms of
the individual [Rozin et al., 1999] and serves to facili-
tate a vigorous response to resolve the danger when an
action received immediately impacts negatively on the
self [Hutcherson and Gross, 2011]. Maybe the lower
percentage of pupils that say they feel anger in cyber-
bullying versus traditional bullying can be related to
the greater perception of attacks as less close to self.
It is also interesting that the emotions least
frequently reported in episodes of cyberbullying
were feeling “defenseless” and “embarrassed.” Per-
haps students experiencing cybervictimization have
a greater sense of control over what is happening
than victims of traditional forms of bullying. But this
finding could also indicate that the victims have an
unadjusted perception of the situation, which could
be detrimental to the development of effective cop-
ing strategies. A third possibility, as previously com-
mented in relation to anger, is that the perception of
these attacks varies in relation to self.
Regarding feelings of embarrassment, the results
suggest that, in spite of its wide potential audience, cy-
berbullying can be perceived as a distant phenomenon
given that victims are not confronted, face-to-face,
with the aggressors, which could protect them from
exposure to this emotion. Embarrassment is a socio-
moral emotion that, from its origins, as toddlers,
needs the presence of other people to be felt. So,
maybe the absence of the direct presence of other
people could explain these results. However, embar-
rassment is probably dependent on the specific type
of bullying that the victim receives. The proportion
of English victims affected by different negative emo-
tions was higher than in Italy and Spain. This could
be because there has been an increased awareness of
bullying in England since the mid-1990s, and more
recently, of cyberbullying [Cowie and Colliety, 2010],
Aggr. Behav.
352 Ortega et al.
so perhaps pupils feel relatively well able to recog-
nize and express negative emotions associated with
bullying experiences.
Spanish victims seem to be less affected by cyber-
bullying; which could be due to a lack of awareness
and that it might be perceived as less serious than
traditional bullying. Possibly this variation relates to
a delayed access to the use of ICTs among Spanish
adolescents [Fundaci´
on Orange, 2009]; or maybe in-
cidents of cyberbullying are less serious than in other
In general, the proportion of victims that reported
negative emotions in cyberbullying was lower than
in traditional bullying. These differences could be re-
lated to the characteristics, real or perceived, of these
two kinds of bullying. Some pupils do seem to re-
gard cyberbullying as (mostly) not being as serious as
traditional bullying, because it is not "real" and can
be ignored in a way that face-to-face bullying cannot
[Smith et al., 2008]. However, there are also other pos-
sibilities, so the differences found could be related to
the presence or absence of face-to-face contact. As we
have proposed previously [Ortega et al., 2009b], with
face-to-face contact victims have more emotional in-
formation about their aggressors, so it could be easier
to ‘‘read’’ their intentions, which could affect the emo-
tional response. This hypothesis would also explain
the higher percentage of victims that reported nega-
tive emotions in direct versus indirect bullying. How-
ever, further research is necessary to explore these
The third of our aims focused on identifying emo-
tional response profiles across the several kinds of
bullying. Again, the findings showed the importance
of differentiating each type of bullying. We established
two main types of emotional profiles. The first pro-
file included feelings produced by direct bullying and
cyberbullying through mobile phone, and the second
profile included the feelings generated by indirect bul-
lying and cyberbullying on the Internet. In the first
group, the emotional response was more complex and
was more clearly associated to the three degrees of
damage unaffected, moderately affected and strongly
affected. We hypothesize that these differences, be-
tween direct and mobile phone on one hand, and in-
direct and internet on the other hand, can be signaling
that cyberbullying using mobile phones was perceived
as more direct than cyberbullying using the Internet,
although in both there is a technological device that
operates as an intermediary between the aggressor
and victim.
However, it was also interesting that in both forms
of cyberbullying, mobile phones, and Internet, there
was an almost identical cluster of victims who re-
ported exclusively not feeling bothered. These results
partially replicate those found by Ortegaet al. [2009b],
who found that the emotional responses of cybervic-
tims was almost equivalent to those reported by vic-
tims of indirect bullying. In this study, however, the
emotional impact on the students who were cyberbul-
lied through their mobile phone seemed to be closer
to the feelings experienced during direct bullying.
These results suggest that with cyberbullying, we
are confronted by a general phenomenon with very
different “branches.” The current categorization, tra-
ditional vs. cyberbullying, may be insufficient to cap-
ture the complexity of these phenomena. Some spe-
cific types of cyberbullying could be closer or more
similar, in some sense, to some specific types of tra-
ditional bullying. So, maybe it is not very different to
be insulted face to face than through a mobile phone,
unless the insult is published on a social network in
which there are many classmates. What is most im-
portant may not be the use of mobile phone or the
Internet, but other factors such as the kind of rela-
tionship previously established between victim and
aggressor, or the specific behaviors involved. In any
event, regardless of how it is mediated, it is important
to take into account different factors to analyze how
bullying phenomena appear and develop, and the im-
pact it has on those involved in it. As Tokunaga [2010]
has suggested, the development of a common theo-
retical framework seems a necessity to take research
It is also important to highlight the fact that in all
types of bullying there is a group of “not bothered”
victims. There could be different explanations for this.
Maybe it is related to some features of the incident not
researched here, such as number of witnesses, iden-
tity of the aggressor, or previous relationship between
victim and aggressors. On the other hand, it could
be related to some victim features such as perceived
reason for victimization or some kind of adaptive re-
silience, maybe related to the use of problem-solving
coping skills [Baldry and Farrington, 2005] and a pos-
itive appraisal of a stressful situation [Hunter et al.,
2004]; or possibly to factors like intrinsic develop-
mental strengths (e.g., self-esteem, self-efficacy) and
extrinsic developmental strengths (e.g., family, school,
community, peers) that allow some victims to mini-
mize the emotional damage [Donnon and Hammond,
2007]. A final possibility could be that “not bothered”
victims are denying their suffering. This study cannot
answer these questions, but further research can use-
fully clarify to the situation of these victims who seem
resilient to their negative experiences.
Our fourth aim was to examine the impact of gen-
der, school grade, country, and frequency of bullying
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 353
on the victims who had been identified into clusters of
emotional responses. The results showed interesting
differences across different types of bullying. All fac-
tors were related to the emotional impact of all types
of bullying with a few exceptions: country in indirect
bullying, gender in mobile phone and school grade in
Internet cyberbullying. However, the amount of vari-
ance explained by logistic regression models was very
different between indirect bullying (only 3.9%) and
the rest of types of bullying, which showed similar
explained variances (from 11.3 to 13.4%). This means
that these variables are not equally useful to predict
emotional impact. In addition, in general the variance
explained by these variables was not very high. As re-
viewed in the introduction, there are several variables,
related to bullying episodes and to person charac-
teristics, which could moderate or mediate the rela-
tionship between aggression and emotional impact.
Some of these variables, such as self-esteem and cop-
ing strategies used, have shown to be useful to distin-
guish vulnerable and resilient adolescents on experi-
ences of stress and depression [Dumont and Provost,
In relation to gender, our findings partly agree with
those of Bond et al. [2001], who found that repetitive
bullying episodes were predictive of intense emotional
responses of anxiety and depression in girls but not
for boys. The results suggest that emotional responses
were conditioned by gender stereotypes, where boys
tend to show themselves as less affected by what hap-
Concerning school grade, our results show that
younger students are more likely to be affected than
older ones. Thus, it seems that the emotional impact
was managed better as students matured. This is sup-
ported by previous studies that show that victim rates
for traditional bullying reduce with age, possibly due
to better coping strategies [Smith et al., 1999]. In his
review, Tokunaga [2010] hypothesized a curvilinear
relationship between age and frequency of cyberbul-
lying victimization, as found in traditional bullying
literature but at a slightly later age. Better manage-
ment of the emotional impact, as a result of experi-
ences in particular kinds of attacks, could explain the
lesser impact with older students; but this does not ex-
plain why this does not work in Internet cyberbullying
situations. A more detailed analysis about specific use
of technologies along adolescence could help us to
interpret these results.
Limitations of the Current Study
This study had some limitations concerning the de-
sign, measurement, samples, and cross-cultural na-
ture. The cross-sectional design limited the under-
standing of the direction of the relationship between
variables. For example, we cannot be sure if the oc-
casional victims, who were found to be less affected,
are occasional because of their coping strategies and
resilience (because they are genuinely "not bothered")
or, on the contrary, if they are not in a long-term bul-
lying situation just by chance, and because of this
they are not affected. Measurement was made by
self-report answers and victimization was assessed
through single-item measures. There is a long tradi-
tion of this kind of questionnaire in researching bul-
lying that has produced acceptable results. However,
there is a tendency toward the use of instruments cen-
tered on specific behaviors. According to Tokunaga
[2010], “future research on cyberbullying should fo-
cus on the development of a reliable and valid measure
of the cyberbullying construct based on summated
Concerning sampling, although several schools
were sampled in each country, this cannot be seen to
give a national representation. Also, in spite of being a
strong point of the study, the cross-national aspect has
some limitations; selection of the participant coun-
tries was primarily by convenience, rather than being
selected to test specific aspects of cross-country com-
parisons. Thus, differences found between countries,
and the explanations proffered, must be treated as
provisional. Also, we found some country differences
in relation to some emotions; but the emotional uni-
verse, understanding, feeling, expressing, and manag-
ing emotions is strongly related to the cultural con-
text. So, to be “angry” maybe does not mean the
same for English victims as for Spanish or Italian
ones. Thus, we need to be careful in interpreting these
Conclusions and Directions for Future
To summarize, our findings suggest that both bul-
lying and cyberbullying experiences, independently
of whether they are face-to-face, indirect or through
different technological devices, have a damaging im-
pact on the majority of victims. It seems likely that
this impact could mediate the broad range of distur-
bances associated with bullying and cyberbullying:
academic and psychosocial problems, depression, low
self-esteem, and externalized hostility, among others
[Tokunaga, 2010]. Direct bullying and cyberbullying
via mobile phone showed similar profiles, and also in-
direct bullying and cyberbullying using the Internet.
More studies are required to research the emotional
impact on victims of multiple victimization, bully-
ing, and cyberbullying, as well as to identify specific
aspects of the bullying behaviors, of whatever type,
Aggr. Behav.
354 Ortega et al.
responsible for or related to the emotional impact on
Adolescence is a very important stage in which some
of the emotional and cognitive schemes that will shape
our “adult personality” are being developed. So, the
practical implications of the experiences in this pe-
riod are clear. However, the person-centered approach
used in this study has allowed us to show that, regard-
less of the specific type of bullying experienced, not all
victims are equally emotionally affected. This points
to the need for further research to identify that are
the specific characteristics important in the complex
process of victimization. In addition, we would like
to highlight the importance of researching the char-
acteristics of “non affected” victims. This would allow
us to understand why, and how, some pupils are ap-
parently able to face very difficult situations in a way
that they are not strongly affected. This knowledge
could help us to design interventions and resources
directed to improve these abilities. Besides helping to
reduce aggression and bullying occurring, an effective
emotional response by victims can also play a part in
the success of intervention programs.
This study was carried out in the framework
of the European Daphne II Programme (Project
JLS/2096/DAP-l/241YC 30-CE-0120045/00–79:
An investigation into new forms of bullying among
European adolescents”). The Spanish team also
received support from the National Research Plan
(PSI2010–17246), and from the Excellence Research
Program from Junta de Andaluc´
ıa (SEJ-6156). The
authors are grateful for the support received.
APPENDIX. Questionnaire 3. “About Bullying and
Cyberbullying.” Items used in this study.
Extracted from the DAPHNE Questionnaires
[Genta et al., 2012].
This questionnaire will helps us find out how do
you use the new technologies (mobiles and internet)
and how you get on with each other in and out of the
Please answer the following questions as truthfully
as you can. [ . . . ].
Now, we want to ask you some questions about
your experiences of bullying and cyberbullying but it
is important to be clear what these words mean.
Bullying is a behavior carried out by an indi-
vidual, or a group, which is repeated over time in
order to hurt, threaten or frighten another individ-
ual with the intention to cause distress. It is dif-
ferent from other aggressive behavior because it in-
volves an imbalance of power that leaves the victim
Cyberbullying is a new form of bullying that in-
volves the use of mobile phones (texts, calls, video
clips) or the Internet (e-mail, instant messaging, chat
rooms, websites) or other forms of information and
communication technology to deliberately harass,
threaten, or intimidate someone.
We would like to know about your experience of
bullying and cyberbullying wherever it happens, in or
out of school.
About bullying:
First, we had like you to answer some questions on
traditional types of bullying. The next five questions
are about direct forms of bullying, which include:
(1) Hitting, tripping up, taking belongings.
(2) Name calling and taunting (perhaps about race,
gender, sexuality, or disability) to someone in per-
son, face-to-face.
Remember, this does not include cyberbullying.
Q1: Have you been directly bullied in the last 2 months?
No, I have not been bullied in the last 2 months
It has only happened once or twice
Two or three times a month
About once a week
Several times a week or more
Q2: How did you feel when someone directly bullied you in the
last 2 months? (For this question you can cross several answers)
I have not been directly bullied in the last 2 months
Afraid and scared
Alone and isolated
Defenseless, no one can do anything about it
It does not bother me
Other (Please write here)
The next five questions are about indirect forms of
bullying, which includes:
(1) Telling lies or spreading false rumors about some-
one behind their back.
(2) Sending mean notes to try and make someone
(3) Excluding someone from a social group on pur-
Again, this does not include cyberbullying.
Aggr. Behav.
Emotional Impact of Bullying and Cyberbullying 355
Q6. Have you been indirectly bullied in the last 2 months? (Answers
options were the same given in the item Q1)
Q7. How did you feel when someone indirectly bullied you in the
last 2 months? (Answers options were the same given in the item
About cyberbullying:
The next questions are about your experiences of
cyberbullying. First, we will ask you about bullying
through mobile phone use and then we will ask you
about bullying using Internet.
About mobile phones:
Examples of bullying using a mobile phone are:
(1) Sending or receiving upsetting phone calls (e.g.,
malicious prank calls).
(2) Taking, sending, or receiving unpleasant photos
and/or videos using mobile phones (e.g., happy
(3) Sending or receiving abusive text messages by mo-
bile phone.
Q11. Have you been bullied through mobile phone use in the last 2
months? (Answers options were the same given in the item Q1)
Q13. How did you feel when someone bullied you through mobile
phone use in the last 2 months? (Answers options were the same
given in the item Q2)
About the Internet:
Now, we need to know if someone has bullying you
using the Internet.
Examples of bullying through the Internet are:
(1) Malicious or threatening emails directly to you or
about you to others.
(2) Intimidation or abuse when participating in chat
(3) Abusive instant messages (MSN, Yahoo, AIM,
(4) Websites where secret or personal details are re-
vealed in an abusive way or where nasty or un-
pleasant comments are being made. Examples of
(5) Social networking websites (myspace, facebook,
bebo, piczo, etc.).
(6) File sharing websites (YouTube, flickr, etc.).
(7) -Blogs (blogger, blogspot, LiVEJOURNAL,
Q23. Have you been bullied on the Internet in the last 2 months?
(Answers options were the same given in the item Q1)
Q25. How did you feel when someone bullied you on the Internet in
the last 2 months? (Answers options were the same given in the
item Q2)
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This article reports the results of a study of the over training of apprentices by large manufacturers in the Middle East countries. The term over training was traditionally used to refer to the way in which nationalized industries trained more apprentices than they needed, with the surplus being released at the end of their training to find another employer .in contrast, the evidence reported in this article indicates that over training now typically involves large employers helping to train apprentices who are employed and paid by other firms from the outset. The project examines the extent and nature of over training, the reason why employers become involved in over training, and policy implications. The evidence suggest that over training can increase the number of high-quality apprenticeships. Large employers need to be made more aware of over training. Government can help and promote overtraining via its catapult centers.
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The relationship between cyberbullying victimization, lower self-esteem, and internet addiction has been well-established. Yet, little research exists that explains the nature of these associations, and no previous work has considered the inability to identify or describe one’s emotions, namely alexithymia, as a potential mediator of these links. The present study sought to investigate the indirect effects of cyberbullying victimization on self-esteem and internet addiction, mediated by alexithymia. The sample consisted of 1,442 participants between 12 and 17 years (Mage = 14.17, SD = 1.38, 51.5% male) from Germany, the Netherlands, and the United States. Results showed a direct relationship between cyberbullying victimization and self-esteem and an indirect association mediated by alexithymia in the Dutch sample. However, in the German and U.S. samples, only an indirect relationship via alexithymia, but not a direct effect of cyberbullying victimization on self-esteem, was found. Consistent across the three country samples, cyberbullying victimization and internet addiction were directly and also indirectly associated via alexithymia. In sum, findings indicate that alexithymia might help better understand which detrimental effects cyberbullying victimization has on adolescent psychological health. Thus, cyberbullying prevention programs should consider implementing elements that educate adolescents on the ability to identify and describe their own emotions.
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A pesar del aumento de las cifras de uso de Internet y redes sociales en Latinoamérica, y de la prevalencia de ciberacoso, existe poco conoci-miento de la realidad que enfrentan los docentes de esta región. A través de una aproximación cualitativa, esta investigación explora discursos y experiencias de docentes en Chile y México en las ciudades de Santiago y Guadalajara sobre esta problemática, y sus herramientas para lidiar con estas situaciones. Para ello se entrevistó en profundidad a 57 docentes de escuelas de bajo, medio y alto nivel socioeconómico y que tienen a su cargo alumnos entre 12 y 17 años. Los principales resultados indican que la confianza de los docentes para identificar ciberacoso aumenta cuando ellos mismos son usuarios de redes sociales, que su preparación para pre-venirlo e intervenirlo es crucial, y que las instituciones deben poner este tema como prioridad, pues es un fenómeno creciente y aún inexplorado por los profesores. Despite rising figures on use of the internet and social networks in Latin America, and on the prevalence of cyberbullying, there is scant knowledge of the reality teachers in the region face. Through a qualitative approach, this investigation explores discourses and experiences of teachers in Chile and Mexico, in the cities of Santiago and Guadalajara, related to this issue, and the tools they use to cope with such situations. For this purpose, we conducted in-depth interviews with 57 teachers at schools classified at low, middle, and high socioeconomic level, who are responsible for students between 12 and 17 years of age. The main results indicate that teachers' confidence in identifying cyberbullying increases when they themselves are users of social networks, that their preparation to prevent it and intervene is crucial, and that institutions need to make the issue a priority because it is a growing phenomenon which remains largely unexplored by teachers.
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Este artigo tem o objetivo de apresentar algumas questões transversais a quatro projetos de pesquisa desenvolvidos por membros de uma linha de pesquisa sobre os Processos psicológicos nas migrações, Tecnologias da Informação e da Comunicação (TICs) e interculturalidade do Laboratório de Interação Social e Humana (LabInt) do PPG em Psicologia da Universidade Federal de Pernambuco (UFPE) 3. Partindo das bases teóricas e epistemológica da psicologia intercultural, segundo as quais o sujeito é produto e produtor de cultura, os dois primeiros estudos visam compreender os aspectos interculturais do uso das TICs por adolescentes do Brasil, França e Vietnam enquanto que os dois outros analisam o risco de cyberbullying por adolescentes do Brasil, de Portugal e de Angola. De metodologia mista, os estudos apresentados associam métodos quantitativos e qualitativos. Os instrumentos de coleta dos dados foram devidamente adaptados transculturamente. Dos resultados obtidos, espera-se identificar elementos que favoreçam a elaboração de programas de prevenção de riscos que levem em conta pertencimentos culturais diversos, através de relações pautadas em valores éticos, no respeito à diversidade e a promoção dos Direitos Humanos.
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One major problem with cyberbullying research is the lack of data, since researchers are traditionally forced to rely on survey data where victims and perpetrators self-report their impressions. In this paper, an automatic data collection system is presented that continuously collects in-game chat data from one of the most popular online multi-player games: World of Tanks. The data was collected and combined with other information about the players from available online data services. It presents a scoring scheme to enable identification of cyberbullying based on current research. Classification of the collected data was carried out using simple feature detection with SQL database queries and compared to classification from AI-based sentiment text analysis services that have recently become available and further against manually classified data using a custom-built classification client built for this paper. The simple SQL classification proved to be quite useful at identifying some features of toxic chat such as the use of bad language or racist sentiments, however the classification by the more sophisticated online sentiment analysis services proved to be disappointing. The results were then examined for insights into cyberbullying within this game and it was shown that it should be possible to reduce cyberbullying within the World of Tanks game by a significant factor by simply freezing the player's ability to communicate through the in-game chat function for a short period after the player is killed within a match. It was also shown that very new players are much less likely to engage in cyberbullying, suggesting that it may be a learned behaviour from other players.
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Bullying is not a phenomenon exclusive to the school environment. Pupils also become victims of verbal aggression (teasing, threats, insults, or harassment) in the context of internet chatrooms. The present study addresses the following questions: (1) How often does bullying occur in internet chatrooms? (2) Who are the victims of bullying in internet chatrooms? (3) What are the determinants of victimization in internet chatrooms? A total of 1700 pupils from various German secondary schools participated in the study. Results revealed a strong relationship between victimization in school and victimization in internet chatrooms; school victims are significantly more often chat victims. Furthermore, the predictors of chat and school victimization show both commonalities (gender, self-concept, child-parent relationship) and differences (social integration, popularity, and bullying behavior).
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Bullying in a school setting is an important social concern that has received increased scholarly attention in recent years. Specifically, its causes and effects have been under investigation by a number of researchers in the social and behavioral sciences. A new permutation of bullying, however, has recently arisen and become more common: Techsavvy students are turning to cyberspace to harass their peers. This exploratory article discusses the nature of bullying and its transmutation to the electronic world and the negative repercussions that can befall both its victims and instigators. In addition, findings are reported from a pilot study designed to empirically assess the nature and extent of online bullying. The overall goal of the current work is to illuminate this novel form of deviance stemming from the intersection of communications and computers and to provide a foundational backdrop on which future empirical research can be conducted.
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This study examined the long-term correlates of victimization in school with aspects of functioning in adult life, using a specially designed Retrospective Bullying Questionnaire, which also included questions about short-term effects (e. g. suicidal ideation and intrusive memories) and victimization experiences in adulthood. Current relationship quality was assessed in terms of self-perception, attachment style and friendship quality. In total, 884 adults (35% male) from two occupations (teacher, student) and three countries (Spain, Germany, UK) participated. Victims and especially stable victims (in both primary and secondary school) scored lower on general self-esteem and higher on emotional loneliness, and reported more difficulties in maintaining friendships, than non-victims. Victims in secondary school had a lower self-esteem in relation to the opposite sex and were more often fearfully attached. The data revealed additional differences by gender, occupation and country level, but no further interactions with victim status. This indicates a general association between victimization in school and quality of later life predominately robust to variations in gender, occupation and country. Possible limitations caused by the retrospective nature of victimization reports are acknowledged.
School‐based surveys of reports of being bullied reveal a fairly steady downward trend through ages eight to 16 years. Four hypotheses are examined which may explain this age‐related decline: (1) younger children have more children older than them in school, who are in a position to bully them; (2) younger children have not yet been socialized into understanding that you should not bully others; (3) younger children have not yet acquired the social skills and assertiveness skills to deal effectively with bullying incidents and discourage further bullying; and (4) younger children have a different definition of what bullying is, which changes as they get older. We test these hypotheses against existing data, and new data, in Study A from interviews with 48 pupils (aged seven‐eight, nine‐ten, 11‐12 and 13‐14 years); and in Study B from interviews with 159 participants (aged five‐six, nine‐ten, 15‐16 and 18‐29 years). The relative strength of the four hypotheses is evaluated. There is support for both (1) and (3); (2) appears to have little impact before age 15; and (4) may explain high rates of report in children under nine years. Implications of these findings are discussed.