Abstract

Bullying victimization in adolescence is a significant risk factor for developing reactive aggressive behavior. One such behavior, bullying perpetration, has penetrated cyberspace in recent years, with continuity and overlap between cyberbullying and bullying. Despite a large body of research on the topic more specific data is needed to explain how adolescent cyberbullying and bullying victims are at a distinct risk of becoming aggressive perpetrators. Also lacking is an understanding of how personal characteristics such as perceived popularity and self-esteem serve as resilience or risk factors in the relationship between exposure to cyberbullying and bullying as victims and then as perpetrators. The current survey was conducted among 427 public high school students in 10^th to 12^th grade (53% females) in Israel using a self-administrated questionnaire. In line with the study hypothesis the results reveal that students with negative perceived popularity and low self-esteem are more exposed to cyberbullying and bullying. The findings also showed that high school students who were victims of cyberbullying and bullying tended to respond by bullying perpetration. Furthermore, negative perceived popularity and low self-esteem, together with higher rates of exposure to cyberbullying or bullying, contributed to increased bullying perpetration among bully-victim youth. Limitations of the study and implications of the results are discussed.

Keywords: Bullying; Cyberbullying; Self-Esteem; Popularity

Literature Review

Bullying among children is a significant worldwide public health problem (Craig, et al. [1,2]). Bullying is usually defined as repeated, intentional aggression perpetrated by a more powerful individual or group against another person perceived to be physically or psychologically weaker, i.e., who have difficulty defending themselves (Olweus, et al. [3-5]). Bullying can take on many forms, including physical, e.g., punching or kicking, seizing or damaging other people’s belongings; verbal, e.g., ridiculing, insulting, repeatedly mocking someone, making racist remarks, name-calling, threatening; relational, i.e., leaving one or more peers out of aggregation groups; and indirect, i.e., spreading rumors or gossip about another person (Nansel, et al. [6,3]). While communication technology developments present many advantages for adolescents (Mishna, et al. [7-9]), along with the widespread use of smartphones and internet access, bullying has penetrated cyberspace, conceptualized as cyberbullying (e.g., Aizenkot, et al. [10-17]). Cyberbullying is an emerging form of bullying and is defined as harm inflicted through threatening, harassing, taunting, and/or intimidating a peer, using an electronic medium, such as a computer, cell phone, and other electronic devices (Hinduja, et al. [18,19,16]).

Similar to definitions of traditional bullying, cyberbullying definitions include aggressive perpetration with the intent to harm (Kiriakidis, et al. [19]). Cyberbullying uses online media to send cruel, threatening, embarrassing, vicious messages in private or group chats. It also includes creating websites with pictures or jokes about victims and inviting other classmates to participate in ridiculing victims online, and tricking victims into revealing sensitive information through instant messaging and then forwarding it to others (Kiriakidis, et al. [19]). Cyberbullying is manifested in
(a) Verbal violence (mockery, curses, insults, derogatory names, threats);
(b) Group violence (opening a group against someone, group shunning or group selectivity - opening a group without a person against their will, preventing entry into a group, forced removal from a group); and,
(c) Visual violence (using photos or videos offensively) (Aizenkot, et al. [10,20,21]).

Unlike traditional bullying, cyberbullies do not see the distress of their victims (Kiriakidis, et al. [19]), and cyberbullying quickly reaches a wide audience (Hinduja, et al. [18]), and is hard to erase (Pieschl, et al. [22]). Bullying and cyberbullying have several characteristics in common, among them the imbalance of power between the aggressor and the victim and the intentionality and replication of the violent perpetration (Navarro, et al. [23,15]). Bullying and cyberbullying mainly consist of relational aggression, including social exclusion or injuring the victim’s reputation, gossiping, slandering and sabotage (Hinduja, et al. [18,24,25]). Bullying and cyberbullying most often occur in spaces with little adult supervision, and since they are difficult to detect or trace (Kiriakidis, et al. [19]). bullies are less wary of being identified. Accordingly, off- and on-line bullying actions usually take place in front of bystanders (Cantone, et al. [26]). These similarities led some researchers to consider cyberbullying a modality of traditional bullying (Erdur Baker, et al. [27-29]). For school students cyberbullying is a particularly insidious form of bullying, as it can occur at school and at home (Hinduja, et al. [18]). In fact, numerous studies have found continuity between school bullying and cyberbullying (Aizenkot, et al. [14,20,30-34]). Thus, for example, Hinduja and Patchin [18]. showed that over 60% of adolescents were involved in both forms of bullying. Therefore, it is common for aggressors emerging in the classroom to continue their perpetration outside the school, through the smartphone and on the internet (Aizenkot, et al. [20]).

Perceived Popularity and Self-Esteem of Bullying Victims

Popularity is generally conceptualized as a shared recognition among peers that a particular person has achieved prestige, visibility or high social standing (Adler, et al. [35]). Popularity can be assessed either by sociometric or perceived popularity. These constructs are distinct, as sociometric popularity is a measure of how well liked (vs. disliked) a child is by peers, whereas perceived popularity reflects a child`s popularity (vs. unpopularity) and dominance within the social hierarchy (Parkhurst, et al. [36]). Perceived popularity is considered as more predictive of adjustment in adolescence than sociometric popularity (Litwack, et al. [37]), as growing empirical and qualitative evidence indicates that perceived popularity is highly valued in adolescence (de Bruyn, et al. [38-40], and prized above achievement, friendship and romantic relationships (LaFontana, et al. [41]). Sullivan [42]) theorized that group-level acceptance is important for development. More specifically, attaining high popularity may contribute to a notable sense of accomplishment and satisfaction and bolster self-esteem (De Bruyn, et al. [37,38,41]), which is defined as the individual’s subjective evaluation of his or her worth as a person (e.g., Gjerde, et al. [43-46]). Self-esteem was found to be highly responsive to social evaluation and external feedback (Crocker, et al. [47,48]). Litwack et al. [37] found that perceived popularity uniquely contributed to adolescent adaptation and well-being, predicting less depressive affect and higher self-esteem. This may be explained by the fact that high social status affords adolescents peer reinforcement in which they are sought out as friends, provide support, admired, and emulated (Sandstrom, et al. [49]).

In general, bullying victims have low self-esteem, low social status, and experience greater social marginalization and feelings of social rejection and isolation (Brown, et al. [50-56]). Most often, adolescents who are not socially accepted tend to be socially incompetent (Shetgiri [2]) and may be characterized by high levels of aggression (Pouwels, et al. [57]). In a recent meta-analysis which evaluated 40 independent studies that examined the association between bullying perpetration and self-esteem, Tsaousis [58] reported a significant, negative association between the two constructs. Youth characterized by high perceived popularity usually behave pro-socially (LaFontana, et al. [41]) and have welldeveloped social skills, although they may sometimes use bullying to gain or maintain dominance in their peer group. The bully usually aims to undermine the victim’s social status and their sense of personal security, while at the same time raising their own selfesteem and social status (Barker, et al. [59,25]). In Research indicates that conventional bullying is positively associated with perceived popularity but negatively associated with social preference of the bully (Berger, et al. [60-63]). Bullying has been described as a dynamic process involving reciprocity between perpetration and victimization (Rose, et al. [64]). Research has demonstrated that not all students involved in the bullying cycle are either bullies or victims, as some of the victims fight back against the bullies or bully other targets, thus adopting the role conceptualized as bullyvictim (Kozasa, et al. [65-67]), also known as reactive bullies or provocative/aggressive victims (Smokowski, et al. [25]).

These may be impulsively aggressive children who respond with aggression to being bullied, or victims who transition from victimization to bullying perpetration over a period of time (Barker, et al. [59]). There is less information about bully-victims compared to the other groups (Shetgiri [2]). The victims’ reprisals may be aroused when their negative victimization experiences accumulate to a critical point, and when they cannot receive effective assistance from others to improve their situation (Sung, et al. [67]). Victims may fight back against their bullies or bully other peers to satisfy their needs, such as enhancement of self-esteem (Kozasa, et al. [65,68]), security, emotional ventilation (Lam, et al. [69]), and prevention of further bullying (Sekol, et al. [70]). Rose, et al. [71] found that students with low self-esteem who experienced bullying victimization engaged in higher rates of bullying perpetration when compared with low self-esteem youth who did not experience victimization. The social information processing model (Crick, et al. [72-74]) may provide an explanation of how the victim becomes a bully-victim and is based on a five-step process. First, victims notice the social situation in which bullies continually attack them. Second, based on previous experience, the victims may think that they will remain victims if they do not find a way to deal with the situation. Third, the victims may think that imitating bullies by attacking others may be a useful way to achieve their goal. Fourth, the victims evaluate the feasibility of executing their plan, for example of attacking more vulnerable targets. Fifth, the victims may decide to follow through with attacks on these vulnerable targets – thus becoming bully-victims. A recent qualitative study (Sung, et al. [67]) provided empirical evidence supporting this model.

The Present Study

The main goal of the present study was to explore the conditions under which exposure to bullying and cyberbullying as a victim is connected to use of violence as a bullying perpetrator. It was assumed that self-esteem and perceived popularity are positively associated with and serve as moderators in the relationship between exposure to bullying as a victim and bullying perpetration. The study also empirically examined the associations between bullying in the physical space and bullying in the virtual space, cyberbullying, among adolescents. Although bullying and cyberbullying have been widely studied in recent decades, many knowledge gaps remain regarding individual and contextual factors that could potentially be the cause or consequence of this aggressive perpetration (Zych, et al. [75]). To the best of our knowledge no study to date has examined the relationship between the variables among adolescents. The importance of the research lies in the fact that both off- and on-line, bullies and victims alike have a significantly amplified risk of anxiety, depressive symptoms, drug use and suicidal ideation compared to children who are not bullied or bullies (e.g., Ortega-Barón, et al. [76-78,12,29]). The findings of this study may contribute to the debate about bullying and cyberbullying and may have implications for the development of intervention programs in the school setting.

Hypothesis

a) Hypothesis 1: Students who were bullying/cyberbullying victims are more likely to be bullying/cyberbullying perpetrators.
b) Hypothesis 2: There is a strong positive linear relationship between bullying victimization and bullying perpetration in the physical space and the virtual space.
c) Hypothesis 3: Students with negative perceived popularity and low self-esteem are more likely to be bullying/cyberbullying perpetrators.
d) Hypothesis 4: Negative perceived popularity is negatively correlated with self-esteem.
e) Hypothesis 5: Perceived popularity and self-esteem will moderate the relationship between bullying victimization and bullying perpetration.

Method

Participants and Procedure

Data were collected from 427 students (53% females) from 39 classes in 16 public high schools (average of 11 students from each class) in 10th (50%), 11th (36%) and 12th (14%) grade. All schools are located in lower to middle socio-economic status neighborhoods. The study was based on data collected for an extensive follow-up evaluation survey conducted by the Ministry of Education in Israel and overseen by a regional Ministry supervisor which aimed to measure the effectiveness of a largescale preventive intervention program. The intervention goal was to reduce WhatsApp cyberbullying and develop optimal online communication between students. Data used for this study were taken from the first measurement (Time 1) and were collected before the intervention began. Intervention effects are not reported in the current article. Identifying details except for gender were not collected about the students at the individual level. However, identifying details at the class and school levels were used, among them school name, grade, and class number. It should be noted that the data collected were not sent to the schools, which only received overall information about the school and its students. Students filled the questionnaires voluntarily, there were no mandatory questions and penalties were not imposed on students who chose not to complete the questionnaire or not to participate at all. A teacher was present in the classroom to maintain order while the students filled the questionnaire. Despite the teacher‘s presence, student privacy was strictly observed since the teacher was not permitted to walk among the students while they completed the survey questionnaires and was specifically requested to respect the privacy of the information they provided. Students completed the survey online at school and had the option of completing it at home.

Measures

Bullying and Cyberbullying Behaviors Between Students

The questionnaire was comprised of 12 items representing bullying and cyberbullying behaviors which may appear between classmates in the school space and between students on social media. It was based on previous questionnaires that examined bullying and cyberbullying (Aizenkot, et al. [20,10,79,80,21]) and was used and validated in previous studies of Israeli children and adolescents (Aizenko, et al. [79,10,20]). The 12 items were divided into four dimensions: The first dimension refers to the space where the bullying occurred: 6 items measured bullying in the physical school space and 6 items measured cyberbullying between students in the virtual space. The second dimension addressed the role of the student in the bullying event, as a bully or a bullyvictim. This was performed using a response scale as follows: for every bullying and cyberbullying behavior the student was asked whether they had been the victim of bullying/cyberbullying and whether they had bullied others. It should be emphasized that for each item the student could simultaneously state that they had been bullied and had bullied others. Sample item: “Did a student in your class verbally attack another student on social media this year?” The responses were scored as follows: “I experienced this once” (1 Point); “I experienced this more than once” (2 Points); “I did this to another student” (1 Point); “It didn’t happen this year” (0 Points). Four bullying scores were calculated:
(1) Score for cyberbullying victims;
(2) Score for bullying victims in the physical space;
(3) Score for cyberbullying perpetrators; and
(4) Score for bullying perpetrators in the physical space.

The possible scores for the victims ranged from 0 to 12, with a higher score indicating a higher frequency of bullying victimization, and the possible scores for the bullying perpetrators ranged from 0 to 6, with a higher score indicating a higher rate of bullying perpetration.

Popularity in Class

The Piers-Harris 2 Children’s Self-Concept Scale Popularity Subscale (Piers, et al. [81]) was originally developed to provide a brief, self-report instrument for assessing self-concept in children and adolescents. Self-concept refers to a relatively stable set of attitudes reflecting both description and evaluation of one’s own perpetration and attributes. Since its introduction the Piers-Harris Scale has enjoyed widespread acceptance among clinicians and researchers. The subscale was translated into Hebrew for the present study using the back translation method. The original popularity subscale included 12 items, 9 of which were selected for the current study as they were found to be specifically suitable for examining perceived popularity in the classroom. Moreover, the subscale items were adapted for the present study in order to specifically examine the respondent’s sense of social acceptability in the classroom. Items that refer to the student’s perceived social competence, for example “I am shy, were omitted”. The items were rated on a 5-point Likert scale from 1 (not true at all) to 5 (very true). Principal component factor analysis with varimax rotation indicated the distribution of items into two factors, one included positive perceived popularity in the classroom (4 items, eigenvalue =1.71) and the other negative perceived popularity in the classroom (5 items, eigenvalue = 3.85) with a total of 62% explained variance (Table 1). Negative and positive popularity scales were mean scored such that a higher score indicates greater agreement with the content of each scale (Table 1).

Self-Esteem Scale

The Rosenberg Self-Esteem Scale (Rosenberg [82]) assesses normative feelings of self-worth. The scale includes 10 items, for example, “On the whole, I am satisfied with myself”, rated from 1 (strongly disagree) to 5 (strongly agree). The scale was translated into Hebrew by Zak [83]. (The scale presented high ratings in reliability areas; internal consistency was 0.77 and minimum coefficient of reproducibility was at least 0.90 (Hobfoll, et al. [84,82]). A varied selection of independent studies, each using samples such as – parents, men over 60, high school students and civil servants – showed alpha coefficients ranging from 0.72 to 0.87. Internal reliability in the present study was .86. Test-retest reliability for the 2-week interval was calculated at 0.85, and 0.63 for the 7-month interval (Silber, et al. [85,86]). Principal component factor analysis with varimax rotation indicated the convergence of items into one factor with a total of 79% explained variance. The self-esteem scale was mean scored, so that a higher score represents more positive self-esteem.

Statistical Analysis

Initial SPSS descriptive statistics, correlations and multiple hierarchical regression analysis were used to examine the distribution of study variables in the study sample and to confirm the direct relationship between bullying victimization and bullying perpetration (Hypothesis 1-2) and between perceived popularity and self-esteem (Hypothesis 3-4). Also used was regression analysis with PROCESS (Hayes [87]), a macro for SPSS to examine multivariate models such as mediation, moderation, and moderated mediation using robust estimation based on bootstrapping techniques. We also used PROCESS following the instructions in Hayes and Montoya [88], to test the slope differences and for probing and plotting the interaction effects involving multicategory moderators. The Hayes Process (Hayes [87]), model 2 was used to test the proposed model in Figure 1 (Hypothesis 5), which predicts that perceived popularity and self-esteem will moderate the relationship between bullying victimization and bullying perpetration. Student grade level and gender were controlled due to previous findings showing significantly reduced bullying during adolescence (Pepler, et al. [89]) and gender differences showing a higher probability that boys will be bullies compared to girls (Juvonen, et al. [53]) but higher relational bullying among girls compared to boys (Lamb, et al. [24]).

Results

Descriptive Analysis and Correlations

The means, standard deviations and correlations of the variables are summarized in Table 2. The results reveal a significant, positive, and moderate to strong intensity correlation between bullying victimization and bullying perpetration, supporting the first two study hypotheses. In accordance with the third study hypothesis, the dependent variables of bullying and cyberbullying perpetration were positively and significantly associated with negative perceived popularity, meaning that the more negative the student’s perceived popularity the more they perpetrated bullying and cyberbullying and vice versa. In line with the fourth research hypothesis, self-esteem was significantly, negatively, and weakly to moderately intensively correlated to negative perceived popularity. Furthermore, self-esteem was found to have a negative, although weak, correlation with bullying and cyberbullying victimization, but not with bullying and cyberbullying perpetration. The correlations also indicated convergence in relation to bullying in both spaces, with relatively strong links between on- and off-line bullying victimization and on- and off-line bullying perpetration.

The controlled variables of gender and grade were found to have a significant, weak and positive association with bullying victimization and bullying perpetration. Descriptive analysis results showed that participants of the current study reported a high level of self-esteem and relatively low negative perceived popularity. The bullying victimization and bullying perpetration rates were not high. Calculating the percentage of bullying victims and bullying perpetrators showed that 26% of the students reported being victims of bullying and 25% of cyberbullying. Also, 15% of the students reported being bullying perpetrators and 13% cyberbullying perpetrators. These percentages express the proportion of students who were bullying victims or bullying perpetrators at least once. Furthermore, 60% of the students who reported being cyberbullying victims also reported being off-line bullying victims. Similarly, 61% of the students who stated that they were bullying perpetrators in the virtual space also reported bullying in the physical space. As shown in Figure 1 below, about one-third of the students who reported cyberbullying perpetration reported simultaneously being victims of bullying in the physical and / or the virtual space. By comparison, nearly half the students reported bullying perpetration simultaneous with bullying victimization in the physical space i.e., responded in kind (Table 2) (Figure 1).

Regression Models

Two 2-step hierarchical linear regression models were constructed to predict bullying perpetration among high school students, one for bullying and one for cyberbullying. The need to separate the statistical analyses for each space was due to the strong correlations obtained between the bullying indices in both spaces. Concerning the threat of multicollinearity within each model, no variance inflation factor was greater than 1.40, indicating that this is not a concern (Tabachnick, et al. [90]). Final Models 1 & 2 regression analyses for predicting student cyberbullying and bullying perpetration were significant, F_(5,421) = 39.48, p < .001, R² = 0.32, p < .000; , F_(5,421) = 39.66, p < .001, R2 = 0.31, p < .000, respectively. Hypothesis 1 stated that students who were bullying or cyberbullying victims were more likely to perpetrate bullying and cyberbullying. Results from Models 1 & 2 support Hypothesis 1, showing that bullying and cyberbullying perpetrations are positively related to bullying and cyberbullying victimization, b = .21, SE = .02, β = .50, t = 11.05, p < .001; b = .22, SE = .02, β = .54, t = 11.52, p < .001, respectively. Hypothesis 3 stated that students with negative perceived popularity will be positively correlated with bullying and cyberbullying perpetration. The results received from Models 1 & 2 support Hypothesis 3 in the virtual space, but not in the physical space, b = .11, SE = .05, β = .10, t = 2.27, p = .024; b = .01, SE = .05, β = .00, t = 0.09, p = .926, respectively. This shows that bullying perpetration in the virtual space is positively related to student’s perceived popularity in the classroom. The more they perceived their popularity to be negative, the more likely they were to perpetrate cyberbullying. (Table 3) below shows the regression results obtained (Table 3).

Process

Process analysis aimed to examine the moderating role of perceived popularity and low self-esteem in the relationship between bullying victimization and bullying perpetration, while controlling for gender and student grade level. Two models were tested, the first model for cyberbullying and the second model for bullying. The findings for Model 1 (Table 4) reveal a significant general model for cyberbullying perpetration, F_{(7, 419)} = 38.43, p < .001, R2 = 0.39. The regression coefficients indicate a direct positive significant main effect of cyberbullying victimization (b = 0.22; SE = 0.07; p = .001; 95% CL 0.35 to 0.08), and a negative significant main effect of self-esteem (b = -0.11; SE = 0.04; p = .015; 95% CL -0.19 to -0.22). Furthermore, in line with research hypothesis 5, two significant interactions were found between negative perceived popularity and cyberbullying victimization (b = 0.09; SE = 0.01; p < .001; 95% CL 0.06 to 0.12), and between self-esteem and cyberbullying victimization (b = 0.05; SE = 0.01; p < .001; 95% CL 0.02 to 0.07) on cyberbullying perpetration. Figures 2 & 3 show that when bullying victimization increases in the virtual space then cyberbullying perpetration also increases, across perceived popularity and self-esteem. However, it appears that when perceived popularity is more negative and self-esteem is lower, the tendency to cyberbullying perpetration increases.

Nonetheless, among students who were never cyberbullying victims, as self-esteem declines cyberbullying perpetration significantly increases to some extent. The findings for Model 2 (Table 4) reveal a significant general model for bullying perpetration, F_{(7, 419)} = 35.79, p < .001, R² = 0.37. The regression coefficients indicate direct positive significant main effects of bullying victimization (b = 0.17; SE = 0.07; p = .010; 95% CL 0.04 to 0.30) and of negative perceived popularity (b = 0.15; SE = 0.06; p = .010; 95% CL 0.04 to 0.25). Furthermore, two significant interactions were found between negative perceived popularity and bullying victimization (b = 0.06; SE = 0.01; p < .001; 95% CL 0.04 to 0.09) and between self-esteem and bullying victimization (b = 0.06; SE = 0.01; p < .001; 95% CL 0.03 to 0.08) on bullying perpetration. Figures 4 & 5 show that high exposure to bullying increases bullying perpetration, both in the virtual and the physical space, beyond perceived popularity and self-esteem. An examination of the moderating role of perceived popularity in relation to bullying victimization and bullying perpetration showed that students affected by bullying who perceive their popularity as negative are more likely to use bullying perpetration relative to students affected by bullying but whose perception of their popularity is less negative. This phenomenon is similarly observed in both the virtual and the physical space. Furthermore, among students who were not affected by bullying, and their perceived popularity was relatively positive, their tendency to bullying perpetration in the physical space was higher than among students with greater negative perceived popularity.

By comparison, in the virtual space students who were not victims of cyberbullying tended to less cyberbullying perpetration regardless of their perceived popularity. Examining the moderating role of self-esteem in relation to bullying victimization and bullying perpetration revealed a slightly different picture of bullying in the virtual space and in the physical space. The study found that in the virtual space, among students exposed to cyberbullying, self-esteem was not found to moderate cyberbullying perpetration. In other words, cyberbullying perpetration in this group is higher relative to the group of students who were not victims of cyberbullying. In relation to bullying in the physical space, bullying perpetration among bullying victimization students was found to be higher among students with positive self-esteem compared to students with low self-esteem. By comparison, among students who were not bullying victims, when self-esteem is lower their tendency to bullying perpetration relative to students with more positive selfesteem increases in both spaces (Table 4) (Figures 2-5).

Discussion

Findings of the present study may contribute to a better understanding of the relationship between bullying perpetration as a response to bullying victimization, perceived popularity and self-esteem. The research hypotheses were mostly confirmed. In accordance with the first research hypothesis the study found that students who were victims of bullying and cyberbullying were more likely to use bullying and cyberbullying perpetration. The study findings provide empirical support for the idea of bullying perpetration as an aggressive reaction to bullying victimization (Kozasa, et al. [65-67,25]) and the conceptualized role of the bully-victim. As such, bullying perpetration may be an impulsive aggressive reaction to being bullied, or of victims who made a transition from victimization to bullying perpetration over a period of time (Barker, et al. [59,67]). Thus, the study findings support the notion of a dynamic process that involves reciprocity between victimization and perpetration (Rose, et al. [64]).

This fight-back strategy may stem from the need to improve their self-esteem (Kozasa, et al. [65,68]). or their social status (Crick, et al. [72-74,67]), restore their security and enable emotional ventilation (Lam, et al. [69]) and prevent further bullying (Crick, et al. [72-74,70,67]). Cyberbullying and bullying, and the link between them, have very damaging consequences. While studies on the topic have increased, knowledge gaps remain regarding factors that could protect children from becoming cyberbully perpetrators or victims (Zych, et al. [91]). According to the current study findings as well as other studies, not all students who were involved in bullying as victims responded in kind (O’Moore, et al. [66]). The study findings contribute to our understanding of the relationship between on- and off- line bullying victimization and bullying perpetration, and of how self-esteem and perceived popularity serve as risk or protective factors with respect to bullying victimization and perpetration in both the physical and the virtual space. The negative correlations found in the current study between perceived popularity and bullying victimization reinforce the view of bullying as relational aggression (Hinduja, et al. [18,24,25]).

Bullying and cyberbullying mainly consists of a power imbalance between aggressor and victim reflecting social status differences (e.g., Crick, et al. [72-75,92,67]). Bullying victims are more anxious and less popular than bullies, have poorer social skills and fewer means of preventing or effectively coping with bullying, and may thus feel powerless (Barker, et al. [59,25]). The study results show a strong relationship between bullying in the virtual space and the physical space. More than half the students reported that they were simultaneously involved in cyberbullying and bullying. These findings are similar to those reported in previous studies which showed that over 60% of adolescents were involved in both forms of bullying (Hinduja, et al. [18,19]). Involvement in cyberbullying can, however, indicate involvement in other types of bullying perpetration and victimization (Wang, et al. [93,94]) and continuity between school bullying and cyberbullying (Aizenkot, et al. [20,30-34,14]).

These findings reinforce the argument of an overlap between bullying behavior in the physical space and in the virtual space and similarities in the behavioral characteristics of bullying in both spaces. The behavior similarities in both spaces are reflected in the intentionality of the behavior and in the imbalance of power between the aggressor and the victim (Navarro, et al. [23,15,9]). This commonality between the spaces reinforces the claim that cyberbullying is a modality of traditional bullying (Erdur-Baker, et al. [27-29]). The present study findings offer empirical support for possible explanations of the connection between bullying victimization and bullying perpetration, however these findings should be treated with caution in light of several methodological weaknesses. First, the fact that the findings do not offer causal explanations as they are based on subjective self-report questionnaires and not on objective measurements. This data collection technique may be biased and, moreover, when it comes to data collection of offensive behavior it may suffer from missing reporting.

Furthermore, the study respondents may have other behavioral problems, organic or personality characteristics, such as attention problems or low empathy. These factors were found in a meta-analytical review of 25 studies related to cyberbullying perpetration (Zych, et al. [91]). These factors were not taken into consideration in the current study, but could interact with the relationships between the study variables. To complete the picture it is important to examine the study findings in light of other characteristics and background variables and in additional groups of students. Finally, the present study findings do not provide an indepth explanation of why bullying victims also tend to perpetrate bullying. Possible explanations should be considered in further studies. The importance of the present study is borne out by the fact that these theoretical constructs are critical to adolescent emotional development and mental well-being. It is also found in the negative impact of bullying victimization and perpetration on student well-being (Machimbarrena, et al. [77,29]), self-esteem (Extremera, et al. [95-97]) and perceived popularity (Cook, et al. [51,61]), especially in adolescence. The results have important implications for policy and practice and may be very useful in designing specifically tailored programs to prevent cyberbullying and bullying [98].

References

1. Craig W, Harel Fisch Y, Fogel-Grinvald H, Dostaler S, Hetland J, et al. (2009) A cross-national profile of bullying and victimization among adolescents in 40 countries. International Journal of Public Health 54(2): 216-224.
2. Shetgiri R (2013) Bullying and Victimization Among Children. Advances in pediatrics 60(1): 33-51.
3. Olweus D (1993) Bullying at school: What we know and what we can do. Blackwell, Cambridge, MA, Oxford, UK.
4. Olweus D, Limber SP (2010) Bullying in school: evaluation and dissemination of the Olweus Bullying Prevention Program. American journal of Orthopsychiatry 80(1): 124-134.
5. Smith PK, Brain P (2000) Bullying in schools: Lessons from two decades of research. Aggressive Behavior: Official Journal of the International Society for Research on Aggression 26(1): 1-9.‏
6. Nansel TR, Overpeck M, Pill RS, Ruan J, Simons-Morton B, et al. (2001) Bullying perpetrations among US youth: prevalence and association with psychosocial adjustment. JAMA 285(16): 2094-2100.
7. Mishna F, Saini M, Solomon S (2009) Ongoing and online: Children and youth's perceptions of cyber bullying. Children and Youth Services Review 31(12): 1222-1228.‏
8. O’Keeffe GS, Clarke-Pearson K (2011) On communications and media. Clinical report-the impact of social media on children, adolescents, and families. Journal of the American Academy of Pediatrics 127: 800-804.
9. Yubero S, Larrañaga E, Villora B, Navarro R (2017) Negative peer relationships on piracy perpetration: A cross-sectional study of the associations between cyberbullying involvement and digital piracy. International Journal of Environmental Research and Public Health 14(10): 1180-1192.
10. Aizenkot D, Kashy-Rosenbaum G (2019) Cyberbullying victimization in WhatsApp classmate groups among Israeli elementary, middle, and high school students. Journal of Interpersonal Violence 36(15-16): NP8498-NP8519.
11. Hinduja S, Patchin JW (2008) Cyberbullying: An exploratory analysis of factors related to offending and victimization. Deviant Perpetration 29(2): 129-156.
12. Mitchell KJ, Jones LM (2015) Cyberbullying and bullying must be studied within a broader peer victimization framework. The Journal of Adolescent Health: Official Publication of The Society for Adolescent Medicine 56(5): 473-474.
13. Moreno Ruiz D, Martínez–Ferrer B, García–Bacete F (2019) Parenting styles, cyberaggression, and cybervictimization among adolescents. Computers in Human Perpetration 93: 252-259.
14. Tokunaga RS (2010) Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Perpetration 26(3): 277-287.
15. Waasdorp TE, Bradshaw CP (2015) The overlap between cyberbullying and traditional bullying. Journal of Adolescent Health 56(5): 483-488.
16. Wang J, Iannotti RJ, Nansel TR (2009) School bullying among adolescents in the United States: Physical, verbal, relational, and cyber. Journal of Adolescent health 45(4): 368-375.
17. Ybarra ML, Boyd D, Korchmaros JD, Oppenheim JK (2012) Defining and measuring cyberbullying within the larger context of bullying victimization. Journal of Adolescent Health 51(1): 53-58.
18. Hinduja S, Patchin JW (2010) Bullying, cyberbullying, and suicide. Archives of Suicide Research 14(3): 206-221.
19. Kiriakidis SP, Kavoura A (2010) Cyberbullying: a review of the literature on harassment through the Internet and other electronic means. Fam Community Health 33(2): 82-93.
20. Aizenkot D (2017) WhatsApp cyberbullying among children and adolescents in Israel: A pilot research. Educational Counseling 20: 363-389.
21. Willard NE (2007) Cyberbullying and cyberthreats: Responding to the challenge of online social aggression, threats, and distress. Champaign, IL: Research Press.
22. Pieschl S, Porsch T, Kahl T, Klockenbusch R (2013) Relevant dimensions of cyberbullying-Results from two experimental studies. Journal of Applied Developmental Psychology 34(5): 241-252.
23. Navarro R, Yubero S, Larrañaga E (2015) Psychosocial risk factors for involvement in bullying perpetrations: Empirical comparison between cyberbullying and social bullying victims and bullies. School Mental Health 7(4): 235-248.
24. Lamb J, Pepler DJ, Craig W (2009) Approach to bullying and victimization. Canadian Family Physician 55(4): 356-360.
25. Smokowski PR, Kopasz KH (2005) Bullying in school: An overview of types, effects, family characteristics, and intervention strategies. Children & Schools 27(2): 101-110.
26. Cantone E, Piras AP, Vellante M, Preti A, Daníelsdóttir S, et al. (2015) Interventions on bullying and cyberbullying in schools: A systematic review. Clinical Practice and Epidemiology in Mental Health 11(Suppl M4): 58-76.
27. Erdur Baker Ö (2010) Cyberbullying and its correlation to traditional bullying, gender and frequent and risky usage of internet-mediated communication tools. New Media and Society 12(1): 109-125.
28. Li Q (2007) Bullying in the new playground: Research into cyberbullying and cyber victimization. Australasian Journal of Educational Technology 23(4): 435-454.
29. Slonje R, Smith PK, Frisén A (2017) Perceived reasons for the negative impact of cyberbullying and traditional bullying. European Journal of Developmental Psychology 14(3): 295-310.
30. Kowalski RM, Morgan CA, Limber SP (2012) Traditional bullying as a potential warning sign of cyberbullying. School Psychology International 33(5): 505-519.
31. Lazuras L, Barkoukis V, Tsorbatzoudis H (2017) Face-to-face bullying and cyberbullying in adolescents: Trans-contextual effects and role overlap. Technology in Society 48: 97-101.
32. Martínez-Ferrer B, Moreno D, Musitu G (2018) Are adolescents engaged in the problematic use of social networking sites more involved in peer aggression and victimization? Frontiers in Psychology 9: 801.
33. Olweus D (2013) School bullying: development and some important challenges. Annual Review of Clinical Psychology 9: 751-780.
34. Twyman K, Saylor C, Taylor LA, Comeaux C (2010) Comparing children and adolescents engaged in cyberbullying to matched peers. Cyberpsychology, Perpetration, and Social Networking 13(2): 195-199.
35. Adler PA, Kless SJ, Adler P (1992) Socialization to gender roles: Popularity among elementary school boys and girls. Sociology of Education 65(3): 169-187.
36. Parkhurst JT, Hopmeyer A (1998) Sociometric popularity and peer-perceived popularity: Two distinct dimensions of peer status. Journal of Early Adolescence 18(2): 125-144.
37. Litwack SD, Aikins JW, Cillessen AHN (2012) The distinct roles of sociometric and perceived popularity in friendship: Implications for adolescent depressive affect and self-esteem. Journal of Early Adolescence 32(2): 226-251.
38. De Bruyn EH, Van den Boom DC (2005) Interpersonal perpetration, peer popularity and self-esteem in early adolescence. Social Development 14(4): 555-573.
39. Eder D (1985) The Cycle of Popularity: Interpersonal relations among female adolescents. Sociology of Education 58(3): 154-165.
40. Pouwels JL, Lansu TAM, Cillessen AHN (2018) A developmental perspective on popularity and the group process of bullying. Aggression and Violent Perpetration 43: 64-70.
41. LaFontana KM, Cillessen AHN (2010) Developmental changes in the priority of perceived status in childhood and adolescence. Social Development 19(1): 130-147.
42. Sullivan HS (1953) The interpersonal theory of psychiatry. Norton, New York.
43. Gjerde PF, Westenberg PM (1998) Dysphoric adolescents as young adults: A prospective study of the psychological sequelae of depressed mood in adolescence. Journal of Research on Adolescence 8(3): 377-402.
44. Marsh HW, O’Mara A (2008) Reciprocal effects between academic self-concept, self-esteem, achievement, and attainment over seven adolescent years: unidimensional and multidimensional perspectives of self-concept. Personality & Social Psychology Bulletin 34(4): 542-552.
45. Stice E, Ragan J, Randall P (2004) Prospective relations between social support and depression: Differential direction of effects for parent and peer support? Journal of Abnormal Psychology 113(1): 155-159.
46. Trzesniewski KH, Donnellan MB, Moffitt TE, Robins RW, Poulton R, et al. (2006) Low self-esteem during adolescence predicts poor health, criminal perpetration, and limited economic prospects during adulthood. Developmental Psychology 42(2): 381-390.
47. Crocker JW, Connie T (2001) Contingencies of self-worth. Psychological Review 108(3): 593-623.
48. Hank P, Baltes Götz B (2019) The stability of self-esteem variability: A real-time assessment. Journal of Research in Personality 79: 143-150.
49. Sandstrom MJ, Cillessen AHN (2006) Likeable versus popular: Distinct implications for adolescent adjustment. International Journal of Perpetrational Development 30(4): 305-314.
50. Brown SL, Birch DA, Kancherla V (2005) Bullying perspectives: experiences, attitudes, and recommendations of 9- to 13-year-olds attending health education centres in the United States. Journal of School Health 75: 384-392.
51. Cook CR, Williams KR, Guerra NG, Kim T, Sadek S (2010) Predictors of bullying and victimization in childhood and adolescence: A meta-analytic investigation. School Psychology Quarterly 25(2): 65- 83.
52. Espelage DL, Swearer SM (2003) Research on school bullying and victimization: what have we learned and where do we go from here? School Psychology Review 32(3): 365-383.
53. Juvonen J, Graham S, Schuster MA (2003) Bullying among young adolescents: The strong, the weak, and the troubled. Pediatrics 112(6): 1231-1237.
54. Olweus D (1994) Bullying at school: Basic facts and effects of a school-based intervention program. Journal of Child Psychology and Psychiatry 35(7): 1171-1190.
55. Ttofi MM, Farrington DP, Lösel, F, Loeber R (2011) Do the victims of school bullies tend to become depressed later in life? A systematic review and meta-analysis of longitudinal studies. Journal of Aggression, Conflict, and Peace Research 3(2): 63-73.
56. Aizenkot D, Kashy Rosenbaum G (2020) The effectiveness of anti-cyberbullying intervention program in reducing bullying on- and off- line and improving perceived popularity and self-esteem. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 14(3).
57. Pouwels JL, Lansu TAM, Cillessen AHN (2016) Participant roles of bullying in adolescence: Status characteristics, social perpetration, and assignment criteria. Aggressive Perpetration 42(3): 239-253.
58. Tsaousis I (2016) The relationship of self-esteem to bully perpetration and peer victimization among schoolchildren and adolescents: A meta-analytic review. Aggression and Violent Perpetration 31: 186-199.
59. Barker ED, Arseneault L, Brendgen M, Fontaine N, Maughan B (2008) Joint development of bullying and victimization in adolescence: Relations to delinquency and self-harm. Journal of the American Academy of Child & Adolescent Psychiatry 47(9): 1030-1038.‏
60. Berger C, Caravita SC (2016) Why do early adolescents bully? Exploring the influence of prestige norms on social and psychological motives to bully. Journal of Adolescence 46: 45-56.‏
61. De Bruyn EH, Cillessen AHN, Wissink IB (2010) Associations of peer acceptance and perceived popularity with bullying and victimization in early adolescence. Journal of Early Adolescence 30(4): 543-566.
62. Sijtsema JJ, Veenstra R, Lindenberg S, Salmivalli C (2009) Empirical test of bullies’ status goals: Assessing direct goals, aggression, and prestige. Aggressive Behavior 35(1): 57-67.
63. Witvliet M, Olthof T, Hoeksma JB, Goossens FA, Smits MS, (2010) Peer group affiliation of children: The role of perceived popularity, likeability, and behavioral similarity in bullying. Social Development 19(2): 285-303.
64. Rose CA, Simpson CG, Moss A (2015) The bullying dynamic: Prevalence of involvement among a large‐scale sample of middle and high school youth with and without disabilities. Psychology in the Schools 52(5): 515-531.‏
65. Kozasa S, Oiji A, Kiyota A, Sawa T, Kim SY (2017) Relationship between the experience of being a bully/victim and mental health in preadolescence and adolescence: a cross-sectional study. Annals of general psychiatry 16: 37.
66. O’Moore M, Kirkham C (2001) Self-esteem and its relationship to bullying perpetration. Aggressive Perpetration 27(4): 269-283.
67. Sung YH, Chen LM, Yen CF, Valcke M (2018) Double trouble: The developmental process of school bully-victims. Children and Youth Services Review 91: 279-288.‏
68. Pollastri AR, Cardemil EV, O’Donnell EH (2010) Self-esteem in pure bullies and bully/victims: A longitudinal analysis. Journal of interpersonal violence 25(8): 1489-1502.‏
69. Lam DO, Liu AW (2007) The path through bullying - a process model from the inside story of bullies in Hong Kong secondary schools. Child and Adolescent Social Work Journal 24(1): 53-75.‏
70. Sekol I, Farrington DP (2010) The overlap between bullying and victimization in adolescent residential care: Are bully/victims a special category? Children and Youth Services Review 32(12): 1758-1769.‏
71. Rose CA, Simpson CG, Preast JL (2016) Exploring psychosocial predictors of bullying involvement for students with disabilities. Remedial and Special Education 37(5): 308-317.
72. Crick NR, Dodge KA (1994) A review and reformulation of social information-processing mechanisms in children's social adjustment. Psychological bulletin 115(1): 74.‏
73. Crick NR, Dodge KA (1996) Social information-processing mechanisms in reactive and proactive aggression. Child Development 67(3): 993-1002.
74. Van Reemst L, Fischer T, Zwirs B (2016) Social information processing mechanisms and victimization: A literature review. Trauma, violence & abuse 17(1): 3-25.
75. Zych I, Farrington DP, Ttofi MM (2019) Protective factors against bullying and cyberbullying: A systematic review of meta-analyses. Aggression and Violent Behavior 45: 4-19.‏
76. Ortega Barón J, Buelga S, Cava MJ, Torralba E (2017) School violence and attitude toward authority of students' perpetrators of cyberbullying. Revista de Psicodidáctica 22: 1-83.
77. Machimbarrena JM, Calvete E, Fernández-González L, Álvarez-Bardón A, Álvarez-Fernández L, et al. (2018) Internet risks: An overview of victimization in cyberbullying, cyber dating abuse, sexting, online grooming and problematic internet use. International Journal of Environmental Research and Public Health 15(11): 2471.
78. Ttofi MM, Farrington DP, Lösel F, Crago RV, Theodorakis N (2016) School bullying and drug use later in life: A meta-analytic investigation. School psychology quarterly 31(1): 8-27.‏
79. Aizenko D, Kashy Rosenbaum G (2018) Cyberbullying in WhatsApp classmates` groups: Evaluation of a prevention program implemented in Israeli elementary and middle school classrooms. New Media and Society 20(12): 4709-4727.
80. Heiman T, Olenik Shemesh D (2015) Cyberbullying experience and gender differences among adolescents in different educational settings. Journal of Learning Disabilities 48(2): 146-155.
81. Piers EV, Harris DB, Herzberg DS (2002) Manual for the Piers-Harris 2: Children’s self-concept scale (2^nd)., Western Psychological Services, Los Angeles, CA.
82. Rosenberg M (1965) Society and the adolescent self-image. Princeton University Press, Princeton, Nj.
83. Zak I (1976) Structure of ethnic identity of Arab-Israeli students. Psychological Reports 38(1): 239-246.‏
84. Hobfoll SE, Walfisch S (1984) Coping with a threat to life: A longitudinal study of self-concept, social support, and psychological distress. American Journal of Community Psychology 12(1): 87-100.
85. Silber E, Tippett JS (1965) Self-esteem: Clinical assessment and measurement validation. Psychological Reports 16(3): 1017-1071.
86. Shorkey CT, Whiteman VL (1978) Correlations between standard English and dialectical Spanish versions of five personality scales. Psychological Reports 43(3, Pt 1): 910.
87. Hayes AF (2017) Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2^nd)., The Guilford Press, New York, USA.
88. Hayes AF, Montoya AK (2017) A tutorial on testing, visualizing, and probing an interaction involving a multicategorical variable in linear regression analysis. Communication Methods and Measures 11(1): 1-30.
89. Pepler D, Jiang D, Craig W, Connolly J (2008) Developmental trajectories of bullying and associated factors. Child Development 79(2): 325-338.
90. Tabachnick BG, Fidell LS (2001) Using multivariate statistics. Allyn & Bacon, Boston, MA.
91. Zych I, Baldry AC, Farrington DP, Llorent VJ (2019) Are children involved in cyberbullying low on empathy? A systematic review and meta-analysis of research on empathy versus different cyberbullying roles. Aggression and Violent Perpetration 45: 83-97.
92. Slonje R, Smith PK (2008) Cyberbullying: Another main type of bullying? Scandinavian Journal of Psychology 49: 147-154.
93. Wang J, Iannotti RJ, Luk JW, Nansel TR (2010) Co-occurrence of victimization from five subtypes of bullying: physical, verbal, social exclusion, spreading rumors, and cyber. Journal of Pediatric Psychology 35(10): 1103-1112.
94. Wang J, Iannotti RJ, Luk JW (2012) Patterns of adolescent bullying perpetrations: physical, verbal, exclusion, rumor, and cyber. Journal School Psychology 50(4): 521-534.
95. Extremera N, Quintana-Orts C, Mérida-López S, Rey L (2018) Cyberbullying victimization, self-esteem, and suicidal ideation in adolescence: Does emotional intelligence play a buffering role? Frontiers in Psychology 9(367): 1-9.
96. Kowalski RM, Limber SP (2013) Psychological, physical, and academic correlates of cyberbullying and traditional bullying. Journal of Adolescent Health 53: S13-S20.
97. Patchin JW, Hinduja S (2010) Cyberbullying and self-esteem. Journal of School Health 80(12): 614-621.
98. Kiefer SM, Ryan AM (2008) Striving for social dominance over peers: The implications for academic adjustment during early adolescence. Journal of Educational Psychology 100(2): 417-428.

ABSTRACT

Bullying victimization in adolescence is a significant risk factor for developing reactive aggressive behavior. One such behavior, bullying perpetration, has penetrated cyberspace in recent years, with continuity and overlap between cyberbullying and bullying. Despite a large body of research on the topic more specific data is needed to explain how adolescent cyberbullying and bullying victims are at a distinct risk of becoming aggressive perpetrators. Also lacking is an understanding of how personal characteristics such as perceived popularity and self-esteem serve as resilience or risk factors in the relationship between exposure to cyberbullying and bullying as victims and then as perpetrators. The current survey was conducted among 427 public high school students in 10^th to 12^th grade (53% females) in Israel using a self-administrated questionnaire. In line with the study hypothesis the results reveal that students with negative perceived popularity and low self-esteem are more exposed to cyberbullying and bullying. The findings also showed that high school students who were victims of cyberbullying and bullying tended to respond by bullying perpetration. Furthermore, negative perceived popularity and low self-esteem, together with higher rates of exposure to cyberbullying or bullying, contributed to increased bullying perpetration among bully-victim youth. Limitations of the study and implications of the results are discussed.

Keywords: Bullying; Cyberbullying; Self-Esteem; Popularity