Cyberbullying: relationship with developmental variables and cyber victimization^▪

The technology is gradually having an important impact on adolescents, as online communication becomes a significant part of their social life (1). At the same time, bullying, that is aggressive repetitive behaviors against a defenseless victim (2), has found a new medium, online environments. Cyberbullying is defined as “an aggressive, intentional act carried out by a group or individual, using electronic forms of contact, repeatedly and overtime against a victim who cannot easily defend him or herself” (3). In other words, cyberbullying is the act of bullying others while cyber victimization is being subjected to others’ bullying acts. Since it has adverse psychological consequences (4-7), academic outcomes (8-10), and increasing rates (11) more research is needed to understand the causal factors for cyberbullying.

One of the most critical psychosocial and developmental characteristics of adolescents is identity development. According to Erikson (12), identity brings in adolescents “purpose and direction” in life, and provides a sense of “inner sameness and continuity” over time and place. Although many researchers (13, 14) investigated this concept, the research recently has been focusing on the process by which identity develops. One of the process-oriented identity models was the three-dimensional identity model of identity formation (15). It focuses on three processes in ideological (i.e. education) and interpersonal (i.e. relationship with best friend) area. The first process, commitment, refers to making permanent choices in life and the sense of confidence in these choices. In-depth exploration, the second process, refers to the more detailed examination of choices adolescents made, questioning them, and striving for more in-depth information about the choices. The last process, which is the reconsideration of commitment, means that adolescents are not happy with their choices and look for alternatives. As a result of these processes, adolescents dynamically form their identity and discover who they are.

The identity formation process, which is intensive during the adolescence period, makes adolescents more vulnerable to online risks. Valkenburg and Peter (16) emphasized that adolescents could face cyberbullying and unwanted sexual demands. Intense interest in sexuality during this period could result in being subjected to sexting, a kind of cyberbullying (17). Finally, identity exploration in online environments was found to be related to cyberbullying (18). Especially adolescents with “identity fluidity”, i.e. assuming different online identities, had higher rates of cyberbullying. In short, the process of identity development confronts adolescents with higher online risks. On the other hand, a well-developed identity that is making commitments and exploring them protect them from risky behaviors (19-21). No study so far has investigated the protective effect of identity development on cyberbullying. On basis of the literature findings which revealed the protective role of a well-developed identity in different kinds of risky behaviors, it may be possible that adolescents with higher commitment and in-depth exploration would engage in less cyberbullying behaviors.

It is essential to find out the cause of cyberbullying. One of the theories of cyberbullying, general strain theory (GST), states that strain factors cause cyberbullying and there are three primary sources of strain in negative relationships with others (22). These are the prevention of someone from achieving positively valued goals, removing or threatening to remove positively valued stimuli, and present or threaten to present someone with dangerous or negatively valued stimuli. For example, adolescents who think that they cannot achieve the deserved success, who lost one of their friends in an accident or who have to move to another city, could experience strain. Anger and similar negative emotions, which result from a negative relationship with others, lead to aggressive behaviors in adolescents. In social media, being a cyber victim is also a source of strain. An adolescent who is excluded from a group in social media, threatened to post personal information online or denigrated experiences strains.

The strains cause negative emotions of which anger has particular importance for GST since it arouses revenge and activates the person. In a study in three different European countries, anger was found to be the most expressed emotion when the emotional effects of varying bullying behaviors were examined (23).

In the case of cyberbullying, GST identified many causes for cyberbullying behaviors. Traditional victimization, for example, was found to be an essential source of strain in terms of cyberbullying (24). Adolescents who were subjected to traditional victimization engaged in more cyberbullying behavior than those who were not, which meant that they acted out their anger online. This study also found that other sources of stress, such as parental stress (conflicts between parents and adolescents), studying for the university entrance exam, and financial burdens (insufficient pocket money) caused cyberbullying behaviors. Similarly, Lianos and McGrath (25) investigated the effects of being a cyber victim, perceived social support, academic stress, and financial stress. They found that participants, who experienced more of these strains, felt more anger and which in turn lead to more cyberbullying behaviors. Parental relationships, peer relationships, peer rejection, school, and homework stress were investigated as the causes of strains for adolescents in another study (26). The results revealed that these strain factors significantly predicted cyberbullying behaviors.

Peer relations are one of the strain factors proposed by GST. During the adolescence period, the importance of parents increasingly declines (27), while the time spent with peers shows a sharp increment (28). They strive for independence from the family and support from their friends (29). When the relationship between peer relations and cyberbullying examined, adolescents who perceived their friends as reliable, supportive, and caring were less likely to engage in cyberbullying behaviors (1). Besides, adolescents who had low social support from peers (30), who had a lesser attachment to their peers (31) and who perceived less help and support from them (32), were found to engage in more cyberbullying behaviors. The patterns of peer relationships, quality of friendship, and behavioral adjustment in real life predicted peer relations in online environments (33). Peer relations also have a buffering role in the victimization of cyberbullying (34).

Anger is an important motivator for many aggressive behaviors and cyberbullying. Yet not all adolescents who experience strains engage in cyberbullying. The reason why some better cope with their negative emotions could be related to emotion regulation strategies. Emotion regulation is an internal or external process that includes monitoring, evaluating, and changing the intensity, timing and emotional responses to reach a goal (35). It determines which emotions people will have, how will they experience and express them (36). There are mainly two types of emotion regulation strategies (37). In cognitive reappraisal, the person tries to reevaluate the emotional impact or meaning of the situation, which arouses the emotion. It is carried out during the production phase of emotions. In expressive suppression, the person actively and consciously tries to suppress or inhibit the behavioral expression of emotions. It is achieved after the production of emotion. The former is associated with positive well-being, more positive emotions, less negative emotions and better interpersonal relationships, whereas the latter is associated with depression, negative mood (38-40), less positive emotions and more negative emotions (36). In other words, while the cognitive reappraisal is accepted as a better strategy for emotion regulation, the expressive repression is recognized as a more negative strategy.

The research on the relationship between emotion regulation and cyberbullying is usually derived from the research on traditional bullying. It has been known that emotion regulation is related to aggressive behaviors and traditional bullying (41, 42). Both bullies and victims have deficiencies in their emotion regulation strategies (43). There are fewer studies on the relationship between cyberbullying and emotion regulation. It was reported that cyberbullies and cyberbully/cyber victims were not successful at expressing their emotions and they experience their negative emotions more intensively when compared to those who were unrelated to bullying or who were cyber victims (44). Moreover, adolescents who had deficiencies in positive emotion regulation strategies like cognitive reappraisal did more cyberbullying (45). Emotion regulation strategies influence not only cyberbullying but also cyber victimization behaviors. Adolescents with non-adaptive emotion regulation strategies, such as self-blame, other-blame, rumination and catastrophizing, were found to engage in more cyberbullying behaviors longitudinally than those with adaptive emotion regulation strategies (46). Also, cyber victims who use positive emotion regulation strategies (i.e. such as putting into perspective, positive refocusing, positive reappraisal, acceptance and refocusing on planning) improved better than those using negative ones (47). Eventually, emotion regulation strategies, particularly negative ones like expressive repression, are expected to be related to positively with cyberbullying.

To sum up, based on the literature, peer relations are expected to be related to cyberbullying behaviors. In the presence of poor relationships with peers and expressive repression, one of the negative emotion regulation strategies, adolescents would have difficulty in managing negative emotions and are expected to engage in more cyberbullying. In this context, identity development in the interpersonal relationship area is a broader concept influencing peer relations, emotion regulation strategies and cyberbullying. Figure 1 depicts the proposed model about the relationship between these variables.

FIGURE 1.

Based on the research on aggressive behaviors, exposure to aggressive behaviors is associated with performing similar acts later (48). Most of the theories which help to the understanding of cyberbullying, concentrate on the importance of exposure to cyberbullying behaviors. General aggression theory, based on social learning and social cognitive theories, was proposed to explain the relationship between aggressive behaviors and violence in media (49). When applied to cyberbully, exposure to cyberbullying is accepted as one of the factors for the emergence of similar behaviors (50). Similarly, the Barlett and Gentile cyberbullying model (51) explain how cyberbullies continue to be cyberbullies. The theory emphasizes the importance of learning in the maintenance of these behaviors. Cyberbullying experiences lead to the beliefs of anonymity. The cyberbully eventually learns that the harmful act can be done anonymously and develop a positive attitude. The theory is thought to be incomplete in the sense that it did not take into account that the same learning is likely for cyber victims. In other words, cyber victims just as cyberbullies, could learn that the act of cyberbullying often goes undetected. Hence, they are more likely to engage in similar cyberbullying behaviors.

The relationship between cyberbullying and cyber victimization is clearly demonstrated in many cross-sectional studies (52-57). Some studies reported the co-occurrence of cyberbullying and cyber victimization as high as 80% (58, 59), whereas others did not report such a relationship (60). Li (61) founded that the best predictor of cyber victimization was cyberbullying behavior. Besides, the transition between being a cyberbully and the cyber victim is thought to be easy due to the nature of the online environment (62). The longitudinal relationship has been investigated in fewer studies. Barlett and Gentile (51) investigated the cross-lagged relationship between two variables with two months interval. They reported that there was a strong relationship between two variables, both cross-sectionally and longitudinally. Another study also said that being a cyber victim was significantly associated with being a cyberbully six months later yet it did not significantly predict the cyberbullying behaviors (63). Still, another study tested if cyber victims turns out to be cyberbullies (57). The results revealed that cyberbullying behaviors were not significantly predicted from three months earlier cyber victimization, despite the significant correlation between them. Similar results were obtained in a study with a one-year interval (64). In short, the cyber victimization and cyberbullying were longitudinally associated with each other despite the lack of any causal evidence.

The ambiguity regarding the causal relationship between cyber victimization and cyberbullying involvement can be overcome with cross-lagged panel models that allow describing reciprocal relationships between variables (65-68). In these models, measurement of the same variables has taken at two or more points in time. Both the directional influences of variables (cross-lags) and the stability of each variable over time can be estimated. Thus, identification of cross-lagged effects between cyberbullying and cyber victimization will elucidate the relationship between these variables. Also, it will reveal whether cyber victims learn to cyberbully through exposure.

Thus, the present study has two aims. First, it aims to investigate the relationship between peer relations, emotion regulation and cyberbullying cross-sectionally, and to examine the role of identity development on cyberbullying and other variables. A cross-sectional model (Figure 1) will test the relationship between expressive repression, peer relations and cyberbullying. The direct relationship between identity development and cyberbullying, in addition to the indirect relationship through peer relations and expressive repression will also be revealed in this model. Second, the study aims to explain the causal relationship between cyberbullying and cyber victimization. A cross-lagged panel model will be applied to reveal the causal precedence of them, in addition to the stability of them across two waves. The cross-lagged relationship from Time 1 (T1) cyber victimization to Time 2 (T2) cyberbullying would be larger than the cross-lagged relationship from T1 cyberbullying to T2 cyber victimization.

The proposed model was analyzed by the structural equation modeling (SEM) in LISREL 8.71. Before the analysis, the data were examined for the assumptions of SEM. The two-stage approach in which the measurement and the structural models are tested separately was preferred in SEM (76). Sample size, missing values, outliers, multicollinearity, linearity and homoscedasticity assumptions were met. Since the data did not meet the assumptions of normality, robust maximum likelihood with asymptotic covariance matrices was preferred as suggested by Jöreskog, Olsson and Wallentin, (77). Model-data fit were evaluated by using Satorra-Bentler χ²/df, root mean square error of approximation (RMSEA), standardized root mean square residual (SRMSR), comparative fit index (CFI) and Tucker Lewis index (TLI). The acceptable fit values are less than 5 for Satorra-Bentler χ²/df, less than 0.08 for RMSEA, less than 0.05 for SRMSR, greater than 0.90 for CFI and TLI (78).

To compute the standard coefficients of the relationships in the cross-lagged panel model, two hierarchic regression analyses were employed (SPSS 24.0). Before the analysis, data were checked for the assumptions of the regression analysis. In each regression analysis, time one measures of predicted variables were controlled by being entered in the first block of analysis.

The study aimed to reveal the cross-sectional relationship between the developmental variables and cyberbullying, in addition to finding out the cross-lagged relationship between cyberbullying and cyber victimization. The results showed that having good peer relations were related to less cyberbullying behavior. Expressive repression, as a negative emotion regulation strategy, is positively associated with peer relations. In other words, adolescents who repressed their emotions more had better relationships with their peers, and those with better peer relations did less cyberbullying. Surprisingly, adolescents with higher identity commitment (successful identity) and adolescents with higher reconsidering their commitment (unsuccessful identity) did more cyberbullying. Thus contrary to expectations, a successful identity process did not protect adolescents from engaging cyberbullying behaviors. Another aim was to look at the causal relationship between cyberbullying and cyber victimization. The results supported that cyber victims turned out to cyberbullies with time by showing that being a cyber victim was related to cyberbullying four months later.

One of the aims of the study was to test the relationship between peer relations, expressive repression and cyberbullying. Peer relations were found to have a negative relationship with cyberbullying. This finding is consistent with the expectation of GST, which accepts peer relationships as a source of strain. Peer relations, by itself, were seen as a reason for cyberbullying (80). Moreover, patterns of a face-to-face relationship with peers were repeated in online environments (33). The finding that adolescents who were excluded by their friends were more likely to engage in externalizing behaviors (81), also explains that those with better friendship involved in less cyberbullying.

Since expressive repression is a negative emotion regulation strategy, it was expected to correlate with cyberbullying positively. The results showed that it has an indirect effect on cyberbullying through peer relationships. Once again, it stressed the importance of peer relations. In spite of using negative emotion regulation, they had good relationships with peers that, in turn, protected them from misbehaving in online environments. Expressive repression was found to be correlated with peer relations positively, contrary to the literature. Actually, this strategy was connected to problems in interpersonal relations (82). But the finding differed according to culture. In Asian cultures, repressing emotions were not perceived as unfavorable as in European cultures. Turkish culture might be more alike in Asian cultures in terms of emotional expression. Especially in terms of negative emotions, repression rather than the expression of emotion seemed preferable for a better interpersonal relationship.

Another aim was to explore the relationship between the dimensions of identity development and cyberbullying. As expected, the reconsideration of commitment had a weak positive correlation with cyberbullying. This dimension of identity means that the adolescent is unhappy with the present relations and in a search process. It is associated with more psychosocial problems (83, 84). Therefore, they can experience issues with their friends in online environments. Due to the cross-sectional design of this model, it could also be possible that the adolescent who engages in online cyberbullying activities would be more likely to reconsider their current relationships and search for new friends.

On the contrary to expectations, the findings revealed a weak positive relationship between the commitment dimension of identity development and cyberbullying. It was stated no study so far seemed to investigate this relationship in the literature. However, a well-developed identity was expected to protect adolescents from cyberbullying, a kind of risky behavior (19). Adolescents tended to hide their real names, ages, or gender in online environments (85). The nature of the cyber environment does not allow the individuals to detect the identity of the bully and usually, cyberbullying is unpunished (86, 87). As a result, adolescents would calculate fewer risks online, threatening someone or spread rumors or visual materials about a friend. Thus, the protective effects of identity may not work in cyber environments. Another explanation for this finding would be related to the possibilities which the online environment presented to adolescents. The cyber environment is a place where they can communicate with others, socialize, express themselves and test different identities (17). Sexual exploration, one of the subjects attract their attention, is more accessible and perceived as less risky in online environments (16). Also, social media provide them with feedback about their identity trials (88). More engagement in online environments for identity search could result in more developed identity, i.e. more commitment and more cyberbullying behaviors.

Results indicated that T1 cyber victimization predicted T2 cyberbullying, whereas T1 cyberbullying did not predict T2 cyber victimization. Consequently, it appears that being a cyber victim precedes being a cyberbully in time. In other words, cyber victims learn to cyberbully through exposure. The finding is important in terms of explaining cyberbullying behaviors. Both General Aggression Theory and Barlett and Gentile’s Cyberbullying Model posit that exposure to cyberbullying is vital in the emergence of cyberbullying behaviors, although the two theories explain the mechanism differently. The former relies on social learning principles, whereas the latter stresses the importance of anonymity beliefs. The current results provided support for both theories. However, the mechanisms through which cyber victims become cyberbullies are still vague.

In addition to cross-lagged relationships between cyber victimization and cyberbullying, the lagged relationships, as shown by significant autoregressive correlations revealed that both variables were stable over time. This finding is consistent with previous studies that reported significant longitudinal associations (51, 63). It is seen that bullying or being victimized in the cyber environment is not a one-time event; it persists if not intervened. This result uncovers the need for prevention.

The prior longitudinal studies have provided additional support for the causal relationship between T1 cyber victimization and T2 cyberbullying, with different time intervals changing from three months to one year (57, 63, 64). These studies did not differ from the current research in terms of the sample characteristics. They reported significant correlations similar to the present study. However, in none of these studies, cyberbullying was significantly predicted from prior cyber victimization.

The results correspond to those of Den Hamer and Konjin (46), who investigated the effects of emotion regulation strategies on cyber victimization and cyberbullying relationships longitudinally. They reported that cyber victims turn into cyberbullies, especially if they are not good at regulating their emotions. The results are inconsistent with those reported by Barlett and Gentile (51), who similarly investigated cross-lagged correlations between cyberbullying and cyber victimization. They found both cross-lagged relationships significant; even the relationship from T1 cyberbullying to T2 cyber victimization was higher than the vice versa. The difference might be due to the sample, which consisted of university students. Also, the shorter time interval between waves (two months) in that study might be another factor for the difference. Unfortunately, both studies had two waves. As Kearney (67) suggested, the lag between measurements should be enough to observe the effects of variables. Thus, it would be better to include more than two waves to see the effects. The findings also revealed that both cyber victimization and cyberbullying are stable over time. The result is also consistent with prior research.

Making causal inferences as a result of cross-lagged panel analysis is a disputable subject in the literature. Some researchers argue that they cannot be accepted as causal models, but they are still powerful for starting a discussion on the causal effect of one variable on another (65). It is challenging to reveal cause-effect relationships through experimental designs in developmental researches. Tyagi and Singh (66) claim that these models can give a clue about the cause-effect relationship between the variable in cases where it is impossible to use real experimental designs. In either case, this study presents important findings on the temporal relations between cyberbullying and cyber victimization.

Given the increasing importance of cyber environments for identity search during adolescence, the present research will contribute to filling the gap in the literature on the relationship between identity development and cyberbullying. Future research could explore a causal relationship with longitudinal models because the cross-sectional nature of the present study does not allow to make an inference about whether a well-developed identity caused more cyberbullying behaviors or not. Additionally, more research is needed, which unveils why and how cyber victims do more cyberbullying through the inclusion of possible emotions such as anger or revenge, as stated by GST.

Overall, this study demonstrated the importance of peer relations and cyber victimization for cyberbullying. Adolescents with difficulty in peer relationships are more vulnerable to engage in cyberbullying, thus being a clear target for prevention programs in educational settings. Moreover, the finding that children and adolescents who experienced cyber victimization are more likely to cyberbully in the future has also implications for prevention. Preventive efforts should focus on increasing awareness on how to respond to cyber victimization. Alternative responses to cyberbullying would help them to fight against cyberbullying. The research and practice should more focus on interventions for cyber victims who are prone to be cyberbullied after some time.