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Exploring the Mediating Roles of State and Trait Anxiety on the Relationship between Middle Adolescents' Cyberbullying and Depression


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Cyberbullying is a global problem with significant negative implications, especially among more vulnerable populations, such as adolescents. Previous research suggested that cyberbullying is significantly associated with depression, and anxiety seems to partially or fully mediate this relationship. We aimed to investigate the prevalence and the relationships between cyberbullying status (i.e., cyberbully, cyber victim, double role, or non-cyber), gender, and age. We also explored the mediating roles of state and trait anxiety on the relationship between adolescents' cyberbullying victimization, cyber-aggressiveness, and depression. Our sample consisted of 501 middle adolescents aged from 12 to 15 years (M = 14.00; SD = 0.80; 51.1% males). The results suggested no significant associations between participants' status, gender, or age. Mediation analyses suggested that the relationship between cyber-victimization, cyber-aggressiveness, and depression was mediated by state anxiety and not trait anxiety. We discuss the implications of the current findings in understanding cyberbullying's psychological consequences and their relevant practical implications for prevention and intervention programs.
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Exploring the Mediating Roles of State and Trait
Anxiety on the Relationship between Middle
Adolescents’ Cyberbullying and Depression
Ana-Nicoleta Grigore and Alexandra Maftei *
Faculty of Psychology and Educational Sciences, Alexandru Ioan Cuza University, Bulevardul Carol I, Nr.11,
700506 Ia¸si, Romania;
Received: 9 October 2020; Accepted: 18 November 2020; Published: 19 November 2020
Cyberbullying is a global problem with significant negative implications, especially among
more vulnerable populations, such as adolescents. Previous research suggested that cyberbullying
is significantly associated with depression, and anxiety seems to partially or fully mediate this
relationship. We aimed to investigate the prevalence and the relationships between cyberbullying
status (i.e., cyberbully, cyber victim, double role, or non-cyber), gender, and age. We also explored
the mediating roles of state and trait anxiety on the relationship between adolescents’ cyberbullying
victimization, cyber-aggressiveness, and depression. Our sample consisted of 501 middle adolescents
aged from 12 to 15 years (M=14.00; SD =0.80; 51.1% males). The results suggested no significant
associations between participants’ status, gender, or age. Mediation analyses suggested that the
relationship between cyber-victimization, cyber-aggressiveness, and depression was mediated by
state anxiety and not trait anxiety. We discuss the implications of the current findings in understanding
cyberbullying’s psychological consequences and their relevant practical implications for prevention
and intervention programs.
Keywords: cyberbullying; state anxiety; trait anxiety; depression; adolescents
1. Introduction
1.1. Bullying and Cyberbullying
The bullying phenomenon has been studied since the early 1970s [
]. Various researchers
worldwide have agreed that bullying is a phenomenon increasingly present and that it has become a
worrying social problem in educational, organizational, or interpersonal settings [
]. In recent years,
with technology development, a new form of bullying emerged, namely cyberbullying,
also known
as electronic harassment or Internet harassment. Cyberbullying, an ongoing public health issue,
is generally defined as the online (i.e., through some media—e.g., text messages, calls, social networks,
or e-mails) aggressive act committed by a person or a group of people to repeatedly harm a person who
cannot defend himself/herself [9]. In addition to intentionality, imbalance of power, and repetition as
common features with traditional bullying, cyberbullying involves modern technology [
]. Features
such as anonymity, a possible larger audience, and the possibility of perpetuating the aggressive act at
any time, in addition to the physical distance that separates the victim from the aggressor, significantly
contribute to the increasing prevalence of the cyberbullying phenomenon [1215].
All forms of bullying imply three types of participants: aggressors, victims, and witnesses.
In general, aggressors are individuals who are hurt or scare, with pleasure, people they perceive
as weaker or smaller than themselves [
]. They do not like to lose, do play dirty, are aggressive,
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and generally have a low level of empathy [
]. Victims are people who are intentionally harmed
by the aggressor [
]. They are often shy, introverted, or sensitive, while having low self-esteem [
Finally, the bystanders represent those who witness the victim’s aggression. They can, most often,
encourage the aggressor, remain distant and silent, or defend the victim [
]. In the present study,
we were interested in both the aggressors and the victims of cyberbullying.
Cyberbullies usually exhibit school problems (i.e., substance use and aggressive behavior [
they have low self-esteem, show hyperactivity, they have diculty to express emotions appropriately
(e.g., anger), and usually use technology as a way to vent their frustrations [
]. Due to their ability
to keep their identity unknown and the lack of face-to-face contact with the victim, cyberbullies are
mostly unlikely to experience compassion or sympathy toward the victim [
]. On the other hand,
cyberbullying victims “feel less popular, take more internet-related risks, are more often a bystander
and perpetrator of internet and mobile phone bullying, and are less often a perpetrator and more often
a victim of traditional bullying” ([
] p.1349). Cyberbullying victims usually express social problems
and depressive symptoms, along with school refusal and various physical symptoms associated with
increased psychological distress [
]. These adverse eects can have long-term consequences on
both the victim and their family and peers [19].
1.2. Anxiety, Depression, and Cyberbullying
Previous research suggested that cyberbullying perpetration is significantly associated with
depression, and anxiety seems to partially or fully mediate this relationship in both clinical and
non-clinical populations [
]. High levels of depression and stress were found to increase the
probability of being both a cyberbullying victim as well as a cyberbullying perpetrator [
]. Furthermore,
cyber victims and cyber aggressors seem to have similar levels of depression [
]. A recent meta-analysis
conducted by Marciano, Schultz, and Camerini [
] explored the longitudinal data available concerning
cyberbullying perpetration and victimization in youth. Their study involved 56 longitudinal studies,
and the results suggested that cyberbullying perpetration generally determines externalizing problem
behaviors over time, while cyberbullying victimization represents a risk factor for depression and
anxiety. Additionally, depression, anxiety, and Internet use were found to be significant cyberbullying
victimization predictors over time.
Jenaro, Flores, and Fr
as [
] explored the medium- and long-term impacts of past experiences of
cyberbullying on students, and their results suggested that students who have been cyberbullied scored
significantly higher for anxiety and depression. Moreover, those students who were cyberbullied in
secondary school had a significantly lower adjustment at the university level. Similar associations
between cyberbullying victimization, depression, and anxiety were found in various samples of
children and adolescents worldwide [3133].
In line with previous findings reported by Na, Dancy, and Park [
], Wang, Xie, Wang, Lei,
and Jiang [
] suggested that cyberbullying victimization predicts depression directly and indirectly,
through the mediating role of social anxiety. Similarly, according to Mart
nez-Monteagudo, Delgado,
s, and Escortell [
], cyberbullying victims score highly for social avoidance and social distress.
One of the most worrying eects of cyberbullying victimization is related to suicidal thinking and
behavior [
], emphasizing the importance of cyberbullying research, prediction, and intervention
strategies to promote positive mental health, especially at younger ages, such as in childhood and
adolescence [39].
1.3. Cyberbullying, Gender, and Age
Several researchers highlighted the importance of gender in the emergence of bullying behavior [
generally suggesting that both girls and boys engage in this type of behavior [
]. However, studies
have shown that most perpetrators are males, whereas in victims, there is no link between gender and
the likelihood of them becoming victims [
]. Von Mar
es and Petermann [
] suggested that males
Children 2020,7, 240 3 of 11
are more likely to become aggressors as their age increases, in line with similar results presented by
Sentse, Kretschmer, and Salmivalli [45] or Tustin, Zulu, and Basson [46].
Barlett and Coyne [
] conducted a meta-analysis to explore whether there are significant gender
dierences in the occurrence of cyberbullying behaviors and the potential moderating role of age within
this relationship. Their results showed that male subjects were less prone to cyberbullying behaviors
than women, compared to other findings [
]. Age moderated this relationship; female participants
were found to be more likely to engage in cyberbullying behaviors during early adolescence compared
to male subjects, who had higher levels of cyberbullying in late adolescence, supporting other similar
results in this area [48,49].
Other studies suggested no gender dierences in victimization rates [
] and reported conflicting
results. For example, Kowalski and Limber [
] suggested that girls are more likely to experience
cyberbullying (as both victims and perpetrators), while other authors found no significant dierence
between girls and boys in neither cyberbullying perpetration nor victimization [
]. Cyberbullying
behaviors (i.e., aggressors) and victimization are subject to developmental variations. Cyber aggressors’
behaviors seem to increase in adolescent ages 12 to 16 [
], while cyber victimization seems to decline
throughout [
]. However, according to Sim
es and Matos [
], school satisfaction is more important
for oending and teenagers with double roles (both victims and aggressors), as the subjective health
complaints seem to be risk factors for all three profiles (i.e., victims, aggressors, and double roles).
1.4. The Present Study
According to a recent Eu Kids Online report [
], 84% of Romanian children access the Internet
through smartphones, with an average of 178 min spent online daily. Half of the youth (i.e., in the Eu
Kids Online sample) reported that negative experiences increased from 21% in 2010 to 33% in 2018.
In most countries, 14- to 16-year-old adolescents spend almost twice as much time online than 9- to
10-year-olds. Children and adolescents aged 9 to 16 years ranked as the highest group to access the
Internet and engage in daily online activities. Romanian boys reported being victims more than girls,
and out of those children who witnessed other teens being cyberbullied, half of them tried to help the
victim, 45% did not react, and 7% encouraged the aggressor. Furthermore, one-third of the children
reported negative comments received for personal content shared online (most of it without consent),
a frequent practice in Romania [57].
Given the significant negative consequences that cyberbullying has on one’s mental health,
in addition to the worrying data related to cyberbullying all over the world, Romania included,
in the current research, our aims were (1) to investigate the prevalence and the relationships between
cyberbullying status (i.e., cyberbully, cyber victim, double role, or non-cyber), gender, and age; and (2) to
explore the mediating roles of state anxiety (i.e., the psychological and physiological reactions toward
adverse situations in a specific moment; [
]) and trait anxiety (i.e., a trait of personality (therefore, stable
over time) describing individual dierences related to one’s tendency to present state anxiety; [
on the relationship between middle adolescents’ cyberbullying victimization, cyber-aggressiveness,
and depression. Furthermore, we also aimed to examine whether the existing shreds of evidence
suggested by fellow researchers from other countries are generalizable across other cultural samples,
such as in Romania.
Based on the earlier studies discussed, we assumed the following: (H1) a high prevalence rate
among cyber victims in both boys and girls [
]; (H2) higher rates of cyber-aggression among
older, male boys [
]; (H3) lower rates of cyber-victimization among older
participants [13,53,54]
(H4) significant associations between cyber status (i.e., cyberbully, cyber victim, double role,
or non-cyber), and depression, anxiety state, and anxiety trait. Concerning our fifth assumption (H5),
we expected state anxiety and trait anxiety to mediate the relationships between cyber-victimization
and cyber-aggression, in line with previous studies that confirmed partial or total mediation eects of
anxiety [
]. However, we were also interested in exploring which of the two anxiety dimensions
has a more substantial eect on the relationship between cyberbullying and depression.
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2. Materials and Methods
2.1. Participants
Our final cross-sectional sample consisted of 501 middle adolescents aged 12 to 15 years (M=14.00;
SD =0.80; 51.1% males). They were all students in a north-eastern public school in Romania, with similar
socio-economic backgrounds. The inclusion criteria were related to having and using a personal
smartphone (regardless of the frequency of use). Seven participants from our initial sample were
excluded due to incomplete demographic information (i.e., gender and age) or lack of responses to
one of the questionnaires. Participation was voluntary and all the middle adolescents in our sample
received a colorful sticker at the end of the research procedure as a reward for their participation.
2.2. Research Procedure
This study’s protocol was designed in concordance with the ethical requirements specific to the
faculty where the authors are aliated. All participants voluntarily participated in the study and
gave written informed consent, following the 2013 Declaration of Helsinki and the national laws from
Romania regarding ethical conduct in scientific research, technological development, and innovation.
Before administering the questionnaire, the informed consent of the legal representatives of the
adolescents (i.e., parents) was obtained. The research was conducted in late 2019, in participants’ usual
classrooms, following the school principal’s approval. The questionnaires were distributed by the
school psychologist and one research assistant, blind to the study’s aims.
2.3. Instruments
We used an adapted version of The Beck Depression Inventory-II (BDI II; Beck and Steer, [
adapted and validated on the Romanian population by David and Dobrean, [
]) to measure depression.
The scale consists of 21 items that measure depression on a scale from 0 (symptom absence) to
3 (severity of the symptom). We only used the first 20 items, given the age of our participants and the
nature of the last dimension (Loss of Interest in Sex). Participants were asked to read each group of
statements carefully and pick out the one statement in each group that best describes how they have
been feeling during the past two weeks, including the present day. Example items included “I feel my
future is hopeless and will only get worse” (a 3-score on the Pessimism dimension); “I dislike myself”
(a 3-score on the Self-Dislike dimension); or “I have much greater diculty in making decisions than
I used to” (a 2-score on the Indecisiveness dimension). Cronbach’s alpha coecient for the present
study indicated high reliability of 0.915.
We further used the State-Trait Anxiety Inventory (STAI, Spielberger [
]) to measure anxiety.
A self-report questionnaire was designed to assess levels of state anxiety and trait anxiety. Participants
answered each of the 40 items on a scale from 1 (almost never) to 4 (almost always). Example items
for the trait anxiety subscale include “I worry too much over something that really doesn’t matter”
and “I am content; I am a steady person.” For the state anxiety subscale, example items include
I am tense
”; “I am worried”, and “I feel calm; I feel secure.” Higher scores indicate higher levels of
anxiety. Cronbach’s alpha coecient for the present study indicated high reliability for both the state
anxiety subscale (0.920) and the trait anxiety subscale (0.893).
Finally, we used the short 9-item form of the European Cyberbullying Intervention Project
Questionnaire (ECIPQ, Brighi et al. [
]), to assess the experience of cyber victimization and cyber
aggression. Participants answered a total of 18 items (nine items for each dimension, i.e., aggressor
or victim) on a Likert-type scale from 1 (never) to 5 (almost daily). The experience as a victim
of cyberbullying dimension explored direct behaviors (i.e., direct aggression—”Someone told me
something nasty or threatened me via the Internet or texting”; posting or editing of embarrassing
personal pictures or videos—“Someone posted online embarrassing pictures or videos or modified
the one I posted”; identity theft—“Someone illegally logged into my e-mail or social network account
and stole personal information”), or indirect aggressions, such as releasing personal information
Children 2020,7, 240 5 of 11
(e.g., “Someone released personal information on me online”) or spreading rumors (e.g., “Someone
spread rumors about me online”). The same items were used in an active form to assess cyberbullying
behaviors perpetrated by subjects. A high score on each of the two dimensions indicated a higher
experience as a cyberbully or a cyber-victim. Cronbach’s alpha coecient for the present study indicated
satisfying reliability coecients for both the cyber-victim subscale (0.856) and the cyber-aggressor
subscale (0.755).
A demographic scale assessed participants’ gender and age. All instruments were first pre-tested
in a similar sample of middle adolescents (N=35, Mage =14.01), and no diculties were reported in
terms of understanding the concepts and the words used within the questionnaires.
3. Results
3.1. Cyber Status, Gender, Age
We used the SPSS 20.0 program to analyze our data. Based on the ECIPQ subscales’ scores
and the median test, participants were grouped in four cyber statuses: cyberbully, cyber victim,
double role (i.e., both cyber bullies and cyber victims), or none of the above (neither a cyber victim
nor a cyber aggressor). To be classified as a cyberbully, participants need to have higher scores on the
cyber-aggressor subscale (>Mdn =16) and low scores on the cyber victim scale (<Mdn =18). Similarly,
we classified participants who scored higher >Mdn =18 on the cyber victim subscale and lower than 16
on the cyber aggressor dimension as cyber victims. The adolescents with a double role scored highly
on both dimensions. Higher scores on both subscales implied a double role (both as a victim and a
cyber aggressor). The lowest possible score on the ECIPQ subscales was 9. Therefore, we considered
participants who scored nine or lower than the median on any of the two subscales as non-cybers
(neither a cyber victim nor a cyber aggressor) (see Table 1). Chi-square tests indicated no significant
associations between participants’ status (i.e., cyberbully, cyber victim, double role, or non-cyber) and
gender (X2(3, 501) =1.83, p=0.607), nor with participants’ age (X2(3, 501) =5.53, p=0.136).
Table 1.
Participants’ status (i.e., cyberbully, cyber victim, double role, or non-cyber) depending on
gender and age (N=501).
Gender N
Aggressor Male 39
(15%) * Female 36
Victim Male 43
(18.6%) * Female 50
Double role Male 76
(30.5%) * Female 77
Non-cybers Male 98
(35.9%) * Female 82
* Note: Percentages are calculated from the total sample of participants (N=501).
3.2. Cyber Status, Anxiety, and Depression
Further analyses suggested a significant association between participants’ status and state anxiety
(3, 501) =173.635, p<0.001). Participants with higher levels of state anxiety were more likely to
be victims (N=80). In contrast, participants with lower scores on the state anxiety subscale were
more likely to have a double role (N=96), to be aggressors (N=69), or to be non-cybers (N=157).
We also found a significant association between participants’ status and depression (X
(3, 501) =66.12,
p<0.001). Participants with higher levels of depression were more likely to be victims (N=77),
while participants
with lower scores on the depression scale were more likely to have a double role
(N=102) or to be non-cybers (N=91).
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Finally, a significant association was found between participants’ status and trait anxiety
(3, 501) =88.89, p<0.001). Participants with higher levels of trait anxiety were more likely
to be victims (N=72) or to have a double role (N=102). In contrast, participants with lower scores on
the trait anxiety subscale were more likely to be aggressors (N=56) or non-cybers (N=124).
3.3. The Mediating Role of Anxiety
To deepen our exploration, we further performed mediation analyses using the Hayes [
SPSS macro program PROCESS. The theoretical hypothesis model was tested by estimating the 95%
confidence interval (CI) for mediation eects with 5000 resampled samples. In the current study,
we selected Model 4 to analyze the mediating eect of state anxiety and trait anxiety on the relationship
between cyber aggressiveness and cyber victimization. We used the total scores of the cyberbullying
subscales (i.e., total scores for cyber victimization and cyber aggression) within the ECIPQ.
Descriptive analyses. The means, standard deviations, and correlation matrix of each variable are
shown in Table 2. We found significant positive associations between cyber victims and trait anxiety,
state anxiety, and depression. Similar significant positive associations were found between cyber
aggressors, state anxiety, and depression. A negative, significant association was found between cyber
aggressors and depression.
Table 2. Means, standard deviations, and correlations between the main variables (N=501).
Variables M SD 12345
1. Cyber victim 18.71 6.61 1 0.324 ** 0.785 ** 0.625 ** 0.516 **
2. Cyber aggressor 16.29 4.07 0.324 ** 1 0.208 ** 0.052 0.095 *
3. State anxiety 39.99 12.42 0.785 ** 0.208 ** 1 0.673 ** 0.650 **
4. Trait anxiety 44.56 12.44 0.625 ** 0.052 0.673 ** 1 0.478 **
5. Depression 13.97 11.48 0.516 ** 0.095 * 0.650 ** 0.478 ** 1
*p<0.005; ** p<0.001.
Mediation eect analysis
. Model 4 is a simple mediating model in the SPSS macro PROCESS
compiled by Hayes [
]. We used it to test the mediating eect of trait and state anxiety on the
relationship between cyberbullying (i.e., cyber-victimization and cyber-perpetration) and depression.
3.3.1. The Mediating Role of State Anxiety and Trait Anxiety on the Relationship between
Cyber-Victimization and Depression
The results suggested a positive, significant eect of cyber-victimization on state anxiety (b=1.47,
t=28.31, p<0.001) and on trait anxiety (b=1.17, t=17.89, p<0.001). State anxiety significantly
predicted depression (b=0.55, t=10.18, p<0.001), but trait anxiety did not have a significant predictive
eect on depression (b=0.06, t=1.57, p=0.11). The indirect eect of cyber-victimization and depression
was mediated by state anxiety (indirect eect =0.82, SE =0.11, 95% CI =[0.61
1.04]) but not trait
anxiety (indirect eect =0.007, SE =0.06, 95% CI =[0.004 0.019]).
3.3.2. The Mediating Role of State Anxiety and Trait Anxiety on the Relationship between
Cyber-Aggressiveness and Depression
The results suggested a positive, significant eect of cyber-aggressiveness on state anxiety (b=0.63,
t=4.74, p<0.001) but not on trait anxiety (b=0.15, t =1.17, p =0.24). State anxiety significantly
predicted depression (b=0.62, t=15.00, p<0.001), but trait anxiety did not have a significant predictive
eect on depression (b=0.03, t=0.80, p=0.42). The indirect eect of cyber- aggressiveness and
depression was mediated by state anxiety (indirect eect =0.39, SE =0.07, 95% CI =[0.259
but not trait anxiety (indirect eect =0.005, SE =0.01, 95% CI =[0.016 0.040]).
Children 2020,7, 240 7 of 11
4. Discussion
Our primary findings suggested no significant associations between participants’ status, gender,
or age. Therefore, H1, H2, and H3 were not confirmed. We assumed that our data would suggest
significant associations between cyber status (i.e., cyberbully, cyber victim, double role, or non-cyber),
depression, anxiety state, and anxiety trait (H4). The results confirmed this assumption, suggesting that
(a) participants with higher levels of state anxiety were more likely to be victims, while participants
with lower scores on the state anxiety subscale were more likely to have a double role, to be aggressors,
or to be non-cybers; (b) participants with higher levels of depression were more likely to be victims,
and adolescents with lower scores for depression were more likely to have a double role or to be
non-cybers; (c) middle adolescents with higher levels of trait anxiety were more likely to be victims
or to have a double role, while participants with lower scores for trait anxiety were more likely to be
cyber aggressors or to be non-cybers. Mediation analyses suggested that the relationship between
cyber-victimization, cyber-aggressiveness, and depression was mediated by state anxiety and not
trait anxiety.
The lack of significant associations between gender, age, and cyber status seem to confirm
previous results concerning this area of research (i.e., [
]), which might be explained by the
similar percentages in both girls and boys in this specific age group (12 to 15 years) concerning
cyberbullying exposure, victimization, and perpetration. However, further studies are needed to
better clarify the conflicting results concerning cyberbullying, age, and gender. Results concerning the
associations between cyber status and anxiety trait, anxiety state, and depression are probably our most
important findings, with relevant practical implications. First of all, we found that middle adolescents
with higher levels of depression and state and trait anxiety were more likely to be cyber-victims,
confirming previous findings in this area (e.g., [29]). This is an essential insight for future prevention
and intervention programs that would benefit from focusing on cultivating adolescents’ well-being
and emotional balance. Second, mediation analyses suggested the significant mediating role of state
anxiety, which adds to the importance of enhancing adolescents’ well-being. We already know that the
most frequently used intervention in the area of cyberbullying generally includes education on coping
skills, empathy training, social skills, and communication training [
]. However, in line with
similar previous findings [
], our results point out the usefulness of intervention programs aimed at
increasing adolescents’ well-being and to reduce psychological distress and, implicitly, cyberbullying,
such as cognitive behavioral programs [
], along with social support [
] and positive family and
peer relationships [70,71].
Children and adolescents generally spend time online on social media platforms. As we already
know, there might be a direct relationship between anxiety, depressive symptoms, and social media
use [
]. Hunt, Marx, Lipson, and Young [
] suggested that limiting social media use might
decrease loneliness and depression. Furthermore, spending less time online reduces the risks of
becoming a cyber victim and continuing to be a cyberbully. Therefore, intervention strategies in both
school and family settings should also aim to reduce the time spent online by children and teenagers
and replace it with valuable, family and peer oine time.
A series of limitations also need to be addressed. First, all measures were self-reported, which might
have generated biased responses. Second, the school setting might have inhibited participants and,
therefore, it might have also increased the likelihood of desirable answers. Third, we did not account
for other variables that were found to be significant for cyberbullying among middle adolescents,
such as diculties in emotion regulation and loneliness, sexual orientation [
], empathy and moral
disengagement [76], and several other individual, family, and neighborhood characteristics [77].
Despite these limitations, we consider the current findings relevant for therapeutical, school,
and family-based intervention strategies to prevent, reduce, and eradicate the risk factors and adverse
eects of cyberbullying.
Children 2020,7, 240 8 of 11
Author Contributions:
Both authors contributed equally to conceive and design the main goal of the study,
analyze the data, and write the manuscript. All authors have read and agreed to the published version of
the manuscript.
This paper was co-financed from the European Social Fund, through the Human Capital Operational
Program, project number POCU/380/6/13/123623 ”Doctoral students and postdoctoral researchers ready for the
labor market!”.
Conflicts of Interest:
The authors declare that there are no potential conflicts of interest associated with this
publication and that any financial support has been noted in the Funding section.
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... In the last decade, scientific literature continuously provided a lot of information about the consequences of the increasing use of the internet among children and young people. The more frequent use of mobile phones or the internet was associated with depression [2], self-isolation [3], anxiety [4], poor body image [5,6], and aggressive behaviors [7]. ...
... During the past 12 months, how many times did you travel away on holiday with your family? (Not at all [0]; Once [1]; Twice [2]; More than twice [3]), 4. ...
... How many computers do your family own? (None [0]; One [1]; Two [2]; More than two [3]). ...
Full-text available
The increasing phenomenon of cyberbullying among adolescents needs parental, educational, and social intervention. The study aimed to identify the prevalence of cyberbullying among Romanian adolescents and the importance of gender, family-related factors, self-esteem, and parental styles in both victims and perpetrators. A total of 835 adolescents aged 10–19 years were included in the research. An online questionnaire was specially constructed for this research, gathering socio-demographic and family-related data along with information about cyberbullying as a victim, aggressor, or bystander, and strategies used in order to deal with it. Four psychological scales were used to evaluate self-esteem, loneliness, cybervictimization/cyberaggression, and parental style. (3) Results showed that the most common age for a personal smartphone is M = 10.24 ± 2.43. The main reasons why students use these networks are primarily chatting and fun and less for academic tasks. During the week, adolescents spend 5.53 ± 2.75 h on social media, while during weekends, the duration of smartphone usage almost doubles. Girls are the most common victims of cyberbullying, and less than three-quarters of students believe that aggressors can be both girls and boys, and only a quarter of them have reported an incident. Family affluence, the relationship with parents and classmates, the presence of loneliness and sociodemographic factors were found to be in a strong relationship with the presence of aggression and/or victimization among adolescents. Cyberaggression was found to be positively correlated with the aggressive parental style and negatively correlated with the compassionate and avoidant parental styles. Results are crucial for identifying cyberbullying actors and preventing the negative effects of cyberbullying on psychological, social, and academic life for students, parents, and teachers.
... Both state and trait anxiety are related to cyber-victimization, but only state anxiety is related to cyber-aggressiveness [41]. Anxiety is higher in the perpetrators/victims and victims group than in the perpetrators group [42]. ...
... This could be attributed to variables of psychosocial functioning (self-esteem, depression, anxiety, and stress), since those four variables explained 18% of the 21% of experiencing variance, three times more than they contributed to explaining variance of committing cyber-violence (6%). Since some research only explores the relationship between negative emotional states and cyber-victimization [39], or it was found to be less potent in explaining cyber-bullying [41], it is clear that experiencing cyber-violence is related to elevated emotional distress. However, the data supporting the failure model [40] that explains the interrelation among aggression and depression in a way that prior aggression elevates depression, probably through the disruption of social relationships, indicate the possibility that committing cyber-violence could also be detrimental for mental health. ...
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Cyber-violence is the type of online risk behavior inclined to harm others. Development of new forms of cyber-violent behavior leads to the need to revise specific-item measures of cyber-violence periodically. The aim of this research was to explore the psychometric properties of the revised Committing and Experiencing Cyber-Violence Scale: its latent structure, reliability, and descriptive statistics of underlying dimensions, as well as the relation of some known correlates of cyber-violence, like indicators of psychosocial functioning and online behavioral problems, with cyber-violence. Online questionnaires (cyber-violence, depression, anxiety and stress, problematic Internet use, and problematic gaming) were filled out by 1725 adolescents from a convenient sample. Using exploratory factor analysis and hierarchical regression analysis, the questionnaire’s latent structure and contribution of relevant correlates for explaining cyber-violence variance was examined. Results: Exploratory factor analysis showed a five-factor solution with satisfactory reliability: shaming, information manipulation, hate speech, technology abuse, and information sharing. Participants commit and experience cyber-violence rarely, leading to a positive distribution of data in the factors. The Committing and Experiencing Cyber-violence subscales have a large positive correlation. Gender (male), grades, maternal education, depression, anxiety, stress, problematic Internet use, and problematic gaming are positive predictors of experiencing cyber-violence, whereas gender (male), grades, hours spent online on weekdays, depression, anxiety, stress, problematic Internet use, and problematic gaming are positive predictors of committing cyber-violence. Conclusions: Cyber-violence is connected with lower psychosocial functioning and more risky behavior online (problematic Internet use, problematic online gaming).
... Cyberbullying (CB) has been defined as an aggressive and deliberate behavior that is frequently repeated over time, carried out by a group or an individual using electronics and aimed at a victim who cannot defend himself/herself (11). The impact of cybervictimization has both short-term and long-term consequences, such as depression, anxiety, sleep-troubles, drop-off, suicide thoughts, self-isolation, and inconsistency in behavior (12)(13)(14)(15). Due to its consequences on students' psychological, physical and social lives, and considering the negative impact on their academic performance, teachers are the key to solving bullying problems. ...
... In addition to the high potential of cyberbullying means and contents to become viral (Casas et al., 2020), some specific particularities of cyberbullying (e.g., power imbalance, intentionality, the possibility of becoming a victim at any time, anonymity) anticipate its harmful consequences (Baldry et al., 2019). The consequences of cyberbullying victimization among adolescents include psychological distress and negative feelings such as anger, frustration, shame, and fear (Patchin & Hinduja, 2012), depression, anxiety (Grigore & Maftei, 2020;Turliuc et al., 2020), as well as suicidal thoughts and behavior (Nguyen et al., 2020; see Dorol-Beauroy-Eustache & Mishara, 2021 for a systematic review). Thus, exploring the factors that motivate and favor such actions is essential in order to identify efficient and comprehensive prevention strategies. ...
Cyberbullying represents repeated and intentional aggression through digital devices and implies multiple roles: cyberbullying perpetrators, cyber-victims, active witnesses (cyber-defending), and cyber-passive bystanders. The present study aimed to assess the predictive function of personal (e.g., humor style) and social factors (e.g., peer norms, parental education about Internet use) concerning the four roles in cyberbullying phenomenon: cyberbullying perpetration, cyber-victimization, cyber-defending, and cyber-passive bystander behavior. A sample of 601 adolescents (289 boys, Mage = 12.18 years, SD = 1.21) was included in the study. The participants completed scales measuring their cyberbullying experiences, humor style, peer norms, and parental education regarding their online activity. The results showed that aggressive humor positively predicted cyberbullying perpetration and negatively predicted cyber-defending. Furthermore, self-defeating humor positively predicted all four roles involved in cyberbullying. Affiliative humor positively predicted cyber-defending, while self-enhancing humor negatively predicted cyber-victimization. Finally, peer norms predicted all four roles involved in cyberbullying, while parental education about Internet use did not prove to be a significant predictor in our analyses. The practical implications of these findings for prevention and interventions are discussed.
... Cyberbullying generally creates problematic external behaviors over time, and virtual space is a risk factor for anxiety (Grigore & Maftei, 2020). Victimization of cyberbullying increases the likelihood of high anxiety (Martínez-Monteagudo, Delgado, Díaz-Herrero, & García-Fernández, 2020). ...
This exploratory sequential mixed-method study examines the mental health effects of cyberbullying on sexual minorities in India. In the first phase, 13 sexual minorities who encountered cyberbullying in the past month were interviewed. The second phase was a survey-based quantitative study (N=103) developed based on the qualitative findings. The qualitative result suggests that cyberbullying experienced by LGBTQIA+ persons takes three forms: Verbal-aggressive (abusive commenting, threatening), Sexual (asking for sexual favour, sending pictures of genitalia), and Attack on identity (calling one's identity immoral, unnatural). The participants coped with the cyberbullying through three strategies: Active responding to the bully (retaliation, exposing the bully, attempting to explain), Psychological blocking (adopting an ‘I don't care’ attitude, stop replying), and Technological blocking (blocking, deactivation, increasing filters). Cyberbullying led to aversive emotional outcomes (anger, sadness, shame), behavioural outcomes (reluctance to socialisation, displacing anger to family members, self-injury), and psychopathologies (Depression, Sleep Disorders, Anxiety). The quantitative study shows a significant negative relationship between cyberbullying and mental health. Also, a positive correlation is observed between acceptance received from social media and the mental health status. However, the acceptance from social media does not significantly moderate the relationship between cyberbullying and mental health status. Also, there was no significant difference in mental health status, severity and frequency of cyberbullying, and acceptance from family and social media, based on education, employment status, and life-stage of the participants.
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Objectives Cyberbullying is quite common in adolescents and college students, and it influences mental health in many aspects. The purpose of this study was to investigate the prevalence of cyberbullying in Chinese college students and to look for related factors. Methods Eight thousand and ninety-eight college students aged 17–26 were enrolled in this cross-sectional study. We collected information of their sociodemographic data, depression (evaluated by Self-Rating Depression Scale), anxiety (evaluated by Self-Rating Anxiety Scale), lifetime suicidal behaviors (including suicidal ideation, suicidal plans, and suicide attempts), and experiences of cyberbullying for the past 12 months by online questionnaires. Results The prevalence of cyberbullying for the past 12 months was 7.82% (633/8,098) among college students. Binary logistic regression analysis showed that sex (odds ratio, OR = 0.522, 95%CI = 0.433–0.629, p < 0.001), suicide attempts (OR = 2.164, 95%CI = 1.589–2.948, p < 0.001), depression (OR = 2.372, 95%CI = 1.602–3.512, p < 0.001), and anxiety (OR = 1.911, 95%CI = 1.305–2.800, p = 0.001) were independently associated with cyberbullying. Conclusion Cyberbullying is very common among college students in Hunan Province, China. Besides, being male, suicide attempts, depression and anxiety were independently associated with cyberbullying, which highlights the importance of paying attention to cyberbullying and addressing anxiety, depression, and suicidal behaviors among college students to better improve their mental health and prevent suicide.
Full-text available
The present study aimed to explore the link between intercultural sensitivity, the four dimensions of cyberbullying, i.e., aggression, victimization, cyber-defending, and passive bystander behavior), and religious education as a formal study discipline in schools. Our sample consisted of 241 high school students (M=18.54, SD=.49, 61% males). Our results suggested significant negative associations between intercultural sensitivity and cyber-perpetration, cyber-victimization, and cyber-bystander behavior. No significant gender differences were found concerning intercultural sensitivity. Our findings also suggested that the participants who studied religion as a formal discipline in high school reported higher intercultural sensitivity. Furthermore, we also found a significant interaction effect between intercultural sensitivity and religion as a formal school discipline, in the case of cyber-aggression and cyber-victimization dimensions of cyberbullying. Finally, we discuss our findings considering their practical implication, primarily in educational settings.
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Background/Objective: Cyberbullying is one of the social problems of most concern in educational spheres, especially in adolescence, where victimization experiences have been associated with episodes of anxiety and depression. The aim ofthis work was to analyze the relationship between cybervictimization, anxiety and depression in adolescence in a metaanalysisand identify the moderating variables that could help to explain the various correlations. Method: A search for crosssectionalstudies was conducted in the Web of Science, Scopus, and PsycINFO databases. Of the 156 studies identified, finally13 met inclusion criteria, with a total of 7,348 participants. Results: The results show statistically significant correlationsbetween cybervictimization and anxiety (r =.31) and cybervictimization and depression (r =.28), with moderate-to-largeeffect sizes. The meta-regression analysis showed that the percentage of women and continent are moderating variablesin the relationship between cybervictimization with depression and anxiety. Conclusions: In conclusion, misuse of thenew information and communication technologies can lead to psychological and social maladjustment of individuals, withnegative repercussions on their development © 2022 Colegio Oficial de la Psicología de Madrid. This is an open access article under the CC BY-NC-ND license (
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Online moral disengagement and cyberbullying can enhance fake news spreading. We explored the links between these variables and compulsive Internet use in a sample of 509 teenagers and adults aged 11 to 67. We investigated the effect of compulsive Internet use on cyberbullying through fake news creation and/or distribution, both direct and via moral disengagement, and the related differences between adults and teenagers. The indirect effect of compulsive Internet use on cyberbullying through moral disengagement was significant in adolescents, but not in adults. As assumed, teenagers scored significantly higher than adults on all the primary variables. Contrary to our expectations, no significant gender differences emerged, regardless of participants' age, in terms of compulsive Internet use, moral disengagement, nor cyberbullying. The results emphasize the importance of relevant online education programs designed to engage both teenagers and adults in critical thinking that might help in the fake news detection process, especially during the COVID-19 pandemic.
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The Internet is at the heart of our children’s and adolescents’ way of life. Although it opens up many positive perspectives in terms of access to information, knowledge, and communication, it also presents risks and potential negative experiences that can have severe consequences at the individual level. In this paper, we are interested in studying the link between cybervictimization, psychological well-being, and social competence. More specifically, we want to study how children and adolescents’ anxiety, impulsivity, self-esteem, and deviant behaviors may be related to cybervictimization. We collected data from 1019 children and young people in France aged 9–17 in the context of the EU Kids online survey. Sampling was performed building a random-probability nationally representative sample of households with children using the Internet. Participants completed a questionnaire online by computer-assisted self-interviewing (CASI). Structural equation model reveals that (1) cybervictimization is related to lower well-being, such as anxiety and low self-esteem, as well as lower social competence, such as impulsivity and deviant behaviors, and that (2) all dimensions of (non)well-being and social (in)competence are related to each other. Findings are discussed in the light of Agnew general strain theory and previous research findings on the consequences of cybervictimization.
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The present study aims to analyze the psychometric properties of the revised version of the Adolescent Cyber-Aggressor scale (CYB-AGS). This scale is composed of 18 items that measure direct and indirect cyberbullying. A cross-sectional study was conducted using two independent samples of adolescents. The first sample included 1318 adolescents (52.6% girls) from 12 to 16 years old (M = 13.89, SD = 1.32). The second sample included 1188 adolescents (48.5% boys) from 12 to 16 years old (M = 14.19, SD = 1.80). First, to study the psychometric properties of the CYB-AGS, exploratory factor analysis was performed on Sample 1. Results indicated a two-factor structure: direct cyber-aggression and indirect cyber-aggression. Second, to verify the structure of the CYB-AGS, we selected Sample 2 to conduct confirmatory factor analysis and test the scale’s convergent validity with theoretically-related measures. Results confirmed the reliability and validity of the two-dimensional model. Moreover, measurement invariance was established. Finally, regarding convergent validity, positive correlations were obtained between cyberbullying and aggressive behaviors in school, anger expression, negative attitudes towards school, and transgression of norms. Furthermore, negative correlations were found between cyberbullying and attitudes towards institutional authority.
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Cyberbullying perpetration (CP) and victimization (CV) are prevalent issues in adolescent development. However, previous meta-analyses focused only on cross-sectional findings. The present study aims to meta-analytically summarize 56 longitudinal studies on CP, CV, and related factors in children and adolescents. Forty meta-analyses on CP and CV as both predictors and outcomes of person-related, Internet activity-related, and contextual factors were performed. Additional moderator analyses took into account study design, sample population, and quality of the studies. Results highlight reciprocal longitudinal effects among CP, CV, and both traditional bullying and victimization: CP causes externalizing problem behaviors over time, whereas CV constitutes a risk factor of internalizing problems, such as depression and anxiety. Conversely, behavioral problems and increased Internet use predict involvement in CP, while depression, anxiety, and Internet use also predict CV over time. Further longitudinal research is needed to provide empirical evidence on understudied concepts.
Technical Report
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This report presents the findings from a survey of children aged 9–16 from 19 European countries. The data were collected between autumn 2017 and summer 2019 from 25,101 children by national teams from the EU Kids Online network. A theoretical model and a common methodology to guide this work was developed during four phases of the network’s work, and is discussed at the outset of this report. The main findings from the key topic areas are summarised, which correspond to the factors identified in the theoretical model: Access, Practices and skills, Risks and opportunities, and Social context.
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Little scientific attention has been paid to the problem of cyberbullying in the university environment, compared to similar studies conducted on adolescents. This study attempts to analyze the predictive capacity of certain emotional problems (anxiety, depression, and stress) and university adaptation with respect to cyberbullying in victims and aggressors. The European Cyberbullying Intervention Project Questionnaire, the Depression Anxiety Stress Scale-21 and the Student Adaptation to College Questionnaire were administered to a sample of 1282 university students (46.33% male) aged between 18 and 46. The results suggest that high levels of depression and stress increase the probability of being a cyberbullying victim, while high levels of depression increase the probability of being a cyberbullying aggressor. Similarly, the personal-emotional and social adaptation of students are found to be predictor variables of being a cyberbullying victim, in that high levels of personal-emotional and social adaptation decrease the probability of being a victim, while high levels of personal-emotional, academic and institutional adaptation decrease the probability of being a cyberbullying victim. The results of this study are of special relevance, since they indicate that intervention programs should consider the influence of emotional intelligence, as well as the relevance students' adaptation to university.
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Cyberbullying is a common social maladjustment that has negative repercussions on the wellbeing and development of adolescents, but numerous questions remain as to the relationship between cyberbullying and social anxiety in adolescence. This study analyzes cyberbullying profiles (screening of harassment among peers) and assesses whether these profiles vary with respect to the level of social anxiety (social anxiety scale for adolescents). The sample consisted of 1412 Spanish secondary education students aged 12 to 18 (M = 14.36, SD = 1.65). Latent class analysis and ANOVA were performed. Analyses revealed three profiles: high cyberbullying (high victimization, aggression, and aggression-victimization), low cyberbullying (moderate victimization, aggression, and aggression-victimization), and non-cyberbullying. The cyberbullying patterns varied significantly for all social anxiety subscales. Students with the high cyberbullying profile (bully–victims) presented high scores on social avoidance and distress in social situations in general with peers, whereas these students presented lower levels of fear of negative evaluation and distress and social avoidance in new situations as compared to the low cyberbullying (rarely victim/bully) and non-involved student profiles. Implications for psychologists and educational counselors and cyberbullying preventive interventions are discussed.
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In the current study, we tested the relations between cyberbullying roles and several psychological well-being outcomes, as well as the potential mediation effect of perceived social support from family, friends, and teachers in school. This was investigated in a cross-sectional sample of 1707 young adolescents (47.5% girls, aged 10–13 years, self-reporting via a web questionnaire) attending community and private schools in a mid-sized municipality in Sweden. We concluded from our results that the Cyberbully-victim group has the highest levels of depressive symptoms, and the lowest of subjective well-being and family support. We also observed higher levels of anxiety symptoms in both the Cyber-victims and the Cyberbully-victims. Moreover, we conclude that some types of social support seem protective in the way that it mediates the relationship between cyberbullying and psychological well-being. More specifically, perceived social support from family and from teachers reduce the probability of depressive and anxiety symptoms, and higher levels of social support from the family increase the probability of higher levels of subjective well-being among youths being a victim of cyberbullying (i.e., cyber-victim) and being both a perpetrator and a victim of cyber bullying (i.e., cyberbully-victim). Potential implications for prevention strategies are discussed.
The present study aimed to explore children’s perception of their happiness, as well as their parents’, and to investigate their potential associations with parenting styles. The sample included 73 children (age range 5 to 8 years old, M=6.57, SD=1.06) and one of their parents (age range 29-47 years old, M=36.45, SD=4.08, 85% mothers). Parents filled in a parenting styles and dimensions questionnaire. We used The Faces Scale to assess children’s attributions of happiness, while a focused interview obtained spontaneous verbal descriptions of what made both children and their parents happy. We used both qualitative and quantitative methods to explore our data. Most children considered their compliance with family rules as parents’ main source of happiness. Family relationships and friendship were found to be the primary sources for children’s happiness. Correlation analyses suggested significant associations between children’s self-reported happiness, parents’ perceived happiness, and some of the permissive (lack of follow-through) and authoritarian (directiveness) parenting styles’ dimensions. These findings may be useful for both the development and implementation of positive socio-emotional programs during childhood, as well as for the general parent-child internal dynamic.
The objective of this study is to analyze the predictive capacity of cybervictimization with regards to suicidal thinking and anxiety, depression and stress in university students. The European Cyberbullying Intervention Project Questionnaire, the Depression Anxiety Stress Scale-21 and the Suicidality Scale were administered to a sample of 1282 university students (594 men and 688 women) aged between 18 and 46 (M = 21.65; SD = 4.25). The results suggest that being a cybervictim increases the probability of suicidal thinking and presenting high levels of anxiety, depression and stress. This study highlights the high prevalence rates of cyberbullying in the university environment and how this issue is associated with emotional problems and suicidal thinking. The identification of these relationships may allow for the development of effective preventive intervention measures to respond to this problem.
School bullying is a complex social and relational phenomenon with severe consequences for those involved. Most children view bullying as wrong and recognize its harmful consequences; nevertheless, it continues to be a persistent problem within schools. Previous research has shown that children’s engagement in bullying perpetration can be influenced by multiple factors (e.g., different forms of cognitive distortions) and at different ecological levels (e.g., child, peer-group, school, and society). However, the complexity of school bullying warrants further investigation of the interplay between factors, at different levels. Grounded in social cognitive theory, which focuses on both cognitive factors and social processes, this study examined whether children’s bullying perpetration was associated with moral disengagement at the child level and with collective moral disengagement and prevalence of pro-bullying behavior at the classroom level. Cross-level interactions were also tested to examine the effects of classroom-level variables on the association between children’s tendency to morally disengage and bullying perpetration. The study’s analyses were based on cross-sectional self-report questionnaire data from 1,577 Swedish fifth-grade children from 105 classrooms (53.5% girls; M age = 11.3, SD = 0.3). Multilevel modeling techniques were used to analyze the data. The results showed that bullying perpetration was positively associated with moral disengagement at the child level and with collective moral disengagement and pro-bullying behavior at the classroom level. Furthermore, the effect of individual moral disengagement on bullying was stronger for children in classrooms with higher levels of pro-bullying behaviors. These findings further support the argument that both moral processes and behaviors within classrooms, such as collective moral disengagement and pro-bullying behavior, need to be addressed in schools’ preventive work against bullying.