Social advantages and disadvantages associated with cyber aggression-victimization: A latent class analysis

Highlights

• Evolutionary functions apply to cyber aggression and victimization.

• Empirical analyses show groups involved in both cyber aggression and victimization.

• Cyber aggressive-victim groups differ in frequency of reactive aggression.

• Cyber aggression-victimization is associated with social advantages.

• Highly reactive cyber aggression-victimization is linked to social disadvantages.

Abstract

This study examines cyber aggression and cyber victimization from an evolutionary perspective, extending the literature by: (1) employing Latent Class Analysis to identify cyber aggression-victimization status groups using proactive and reactive cyber aggression, and cyber victimization, as indicators; and (2) examining whether cyber aggression-victimization status groups experience social advantages and disadvantages similar to those in traditional aggression research. In this study, a three-class model best described adolescents’ cyber aggression and victimization; in the sample of 400 adolescents ages 12–18, 79.4% were uninvolved, 13.1% were mixed cyber aggressor-victims (moderate proactive and reactive cyber aggression, and cyber victimization), and 7.4% were highly reactive cyber aggressor-victims (moderate proactive cyber aggression and cyber victimization, but high reactive cyber aggression). These groups contrast with those found in empirical traditional aggression research as pure cyber aggressors and cyber victims were not identified. Consistent with evolutionary theory and aggression research that suggest it has adaptive functions, mixed cyber aggressor-victims reported more social dominance and dating partners, and highly reactive cyber aggressor-victims reported more sexual partners, when compared to uninvolved peers. However, highly reactive cyber aggressor-victims also reported more friendship anxiety and less implicit social power than the mixed and uninvolved group, consistent with traditional research suggesting that reactive aggression is more strongly linked to social disadvantages and less strongly linked to social advantages, than is proactive aggression. Although cyber aggression is a relatively new form of aggression, an evolutionary perspective can illuminate why it continues to be a social problem despite intervention efforts.

Introduction

With increased use of electronic communication technologies in recent years, cyber aggression has become quite prevalent and problematic (see Kowalski, Giumetti, Schroeder, & Lattanner, 2014). Cyber aggression can be defined as ‘intentional behavior aimed at harming another person … through computers, cell phones, and other electronic devices, and perceived as aversive by the victim’ (Schoffstall & Cohen, 2011, p. 588). Cyber aggression subsumes the more specific form called cyberbullying, which is defined more strictly by requiring that the perpetrator has a power advantage over the victim (Schoffstall & Cohen, 2011; Volk, Dane, & Marini, 2014). While much research has focused on cyberbullying, cyber aggression has been found to be more prevalent (Wolak, Mitchell, & Finkelhor, 2007); approximately 1 in 6 adolescents report involvement in cyberbullying (Modecki, Minchin, Harbaugh, Guerra, & Runions, 2014), whereas roughly 1 in 3 adolescents perpetrate cyber aggression (Pabian, De Backer, & Vandebosch, 2015; Ybarra & Mitchell, 2007). Furthermore, cyber aggression tends to co-occur with cyber victimization (Ybarra & Mitchell, 2007), which adds to the problematic nature of these experiences.

Both cyber aggression and cyber victimization have been associated with depression, anxiety, loneliness, suicidal ideation, and low life satisfaction and self-esteem (Bonanno & Hymel, 2013; Kowalski, Guimetti, Schroeder, & Lattaner, 2014). However, Kowalski et al. (2014) found that internalizing problems are more strongly related to cyber victimization than to cyberbullying. Moreover, adolescents involved in both cyberbullying and victimization (i.e., cyberbully-victims) have reported levels of suicidal ideation roughly two times greater than cyberbullies or cyber victims (Bonanno & Hymel, 2013).

Although aggression and bullying have been linked to a variety of social disadvantages, including the negative correlates previously discussed, evolutionary psychologists have posited that aggression has provided solutions to various problems in humans’ evolutionary history, including procuring resources, obtaining/maintaining status and power, and competing with intrasexual rivals (Buss & Shackelford, 1997). Thus, aggression and bullying can be utilized as tools to facilitate and maintain access to evolutionarily relevant social advantages in the domains of resource control, reputation, and reproduction (see Volk, Camilleri, Dane, & Marini, 2012). Consistent with the evolutionary psychological perspective, traditional aggression and bullying have been found to serve adaptive functions, insofar as bullying has been linked with social advantages such as social dominance and status (Juvonen, Graham, & Schuster, 2004; Pellegrini, Bartini, & Brooks, 1999; Reijntjes et al., 2013b; Vaillancourt, Hymel, & McDougall, 2003), as well as perceived popularity (Cillessen & Mayeux, 2004; de Bruyn, Cillessen, & Wissink, 2010; Juvonen, Wang, & Espinoza, 2013; Thunfors & Cornell, 2008; Reijntjes et al., 2013a). Moreover, bullies also engage in dating and sexual behavior earlier and more often than uninvolved peers (Arnocky & Vaillancourt, 2012; Connolly, Pepler, Craig, & Taradash, 2000; Vaillancourt, 2013; Volk, Dane, Marini, & Valliancourt, 2015). This research suggests that traditional aggression and bullying occurs in the context of intrasexual competition for social resources.

Because cyber aggression is a relatively new form of aggression, evolutionary research is sparse in this area. However, preliminary research suggests that cyber aggression has been used to derogate evolutionarily preferred traits in same-sex peers, particularly physical appearance and sexual fidelity in females, and sexual orientation, achievements, and physical ability in males (Hoff & Mitchell, 2009; Wyckoff, Buss, & Markman, 2018), and thus may be a vehicle for intrasexual competition strategies similar to those perpetrated with traditional verbal and relational aggression. Cyber aggression also predicts increases in perceived popularity (for females only: Badaly, Kelly, Schwartz, & Dabney-Lieras, 2013; both sexes: Wegge, Vandebosch, Eggermont, & Pabian, 2016), and has been cross-sectionally linked with more dating and sex partners for adolescents involved in both cyber aggression and victimization (Lapierre & Dane, 2019). This evidence suggests that evolutionary theory may be applicable to this relatively new form of aggression.

Evolutionary perspectives also argue that antisocial strategies such as aggression have cost-benefit trade-offs (see Volk et al., 2012). In this vein, resource control theory (Hawley, 2007) states that antisocial or coercive strategies incur social costs, especially hindering cooperative relationships, that offset the benefit of gaining resources, reputational benefits, and opportunities for reproduction. These trade-offs are evident in research showing that while bullies and aggressors tend to have high perceived popularity (e.g., Juvonen et al., 2013; Wegge et al., 2016; Wright, 2014) and social dominance/status amongst peers (e.g., Juvonen et al., 2004; Vaillancourt et al., 2003), they also tend to experience social disadvantages such as being disliked by peers (Cillessen & Mayeux, 2004; de Bruyn et al., 2010; Reijntjes et al., 2013a; Rodkin & Berger, 2008; Wright, 2014), and being less able to form alliances than youth using prosocial strategies (Farrell & Dane, 2019). Moreover, although bullies and aggressors report more involvement in dating and sex (Arnocky & Vaillancourt, 2012; Volk, Dane, Marini, & Vaillancourt, 2015), they also report more peer conflict (Rose, Swenson, & Carlson, 2004), insecure attachment to peers (Wright et al., 2015) and romantic partners (Wright, 2015), as well as more aggression, and less affection, intimacy, commitment, and equity in dating relationships (Connolly et al., 2000).

However, it is important to note that the costs or social disadvantages associated with aggression may be buffered when aggression is utilized alongside prosocial strategies of resource control (Hawley, 2015). For example, in the case of bistrategic controllers, individuals who use both aggressive and prosocial resource control strategies in a planful and controlled way, some research suggests that their strategic use of prosocial resource control strategies, such as cooperation and reciprocation, can offset the costs/disadvantages of strategic aggression by minimizing the loss of affection or esteem from peers (e.g., Hawley, 2003). However, there is also evidence to the contrary, suggesting that bistrategic controllers experience social disadvantages/costs, as evidenced by low social preference (Reijntjes et al., 2017). In general, this research suggests that more planful approaches to resource control might minimize the social costs/disadvantages relative to impulsive or reactive approaches.

Given that adolescence marks the age when bullying and aggression typically peak (see Volk et al., 2012) and intrasexual competition for social resources becomes prevalent (Polo, Fernandez, Munoz-Reyes, Dufey, & Buunk, 2018), it is important to examine how adolescents’ use of cyber aggression is related to both social advantages and disadvantages. Identifying the social advantages linked to cyber aggression can illuminate why cyber aggression continues to be a problem amongst adolescents despite the risk of incurring social disadvantages and the implementation of school-based anti-cyberbullying interventions intended to reduce this behavior (Gaffney, Ttofi, & Farrington, 2019).

Previous person-oriented research has shown different costs and benefits to be associated with traditional bullying-victimization status groups, including bullies, victims, and bully-victims (both a bully and a victim). In comparison to uninvolved peers, bullies report more externalizing problems, while victims report more internalizing problems (Lovegrove & Cornell, 2014). Bully-victims, on the other hand, report more externalizing and internalizing problems than bullies, victims, and uninvolved peers. Moreover, victims and bully-victims report more peer disadvantages than do bullies and uninvolved peers (Marini, Dane, Bosacki, & YLC-CURA, 2006). These results generally support the contention that bully-victims are the most psychosocially maladjusted group (see Schwartz, Proctor, & Chein, 2001; Volk et al., 2012).

In contrast, several studies have found evidence of social advantages linked to bully-victim status. According to cross-sectional research, female relational bully-victims and physical aggressor-victims of both sexes report more dating behaviors than uninvolved peers (Dane, Marini, Volk, & Vaillancourt, 2017; Gallup, O'Brien, & Wilson, 2011). Similarly, adolescents had more dating and sexual partners when their involvement in cyber aggression and victimization was high (Lapierre & Dane, 2019). A possible explanation is that adolescents who have procured adaptive benefits are viewed as intrasexual rivals (i.e., competitor effect; Dane et al., 2017; Lapierre & Dane, 2019). In line with this contention, traditional victimization is more likely to be experienced by adolescents involved in dating or sexual behavior (Gallup, O’Brien, White, & Wilson, 2009; Leenaars, Dane, & Marini, 2008; McComb & Dane, 2019) and by females who are physically attractive or provocatively dressed (Leenaars et al., 2008; Vaillancourt & Sharma, 2011). Furthermore, both cyber aggression and cyber victimization have been linked to adolescent girls' frequency of taking sexualized selfies, but not to their frequency of taking selfies overall (Stuart & Kurek, 2019). These behaviors and traits may be indicators that mark intrasexual rivals (e.g., Fink, Klappauf, Brewer, & Shackleford, 2014), which could elicit jealousy and trigger victimization (Vaillancourt & Sharma, 2011). Within the context of intrasexual competition, adolescents would likely victimize rivals to reduce their status over time (Arnocky, Sunderani, Miller, & Vaillancourt, 2012; Arnocky; Vaillancourt, 2012; Dane et al., 2017), rather than victimize vulnerable peers who are uninvolved and ineffective in intrasexual competition.

Empirical person-oriented research has shown that cyberbullying-victimization status groups are different from those identified in traditional aggression research, in that adolescents were either uninvolved or involved in both cyber aggression and victimization to varying degrees (i.e., cyberbully-victims; Festl, Vogelgesang, Scharkow, & Quandt, 2017; Schultze-Krumbholz et al., 2015). These findings are consistent with research suggesting that cyber aggression and victimization are more highly correlated that their traditional counterparts (Bauman, Toomey, & Walker, 2013; Varjas, Heinrich, & Myers, 2009), possibly because cyberspace affords anonymity and reduces the salience of power balances between perpetrators and victims (Kowalski et al., 2014), which makes cyber aggression and victimization more likely to occur as a reciprocal cycle rather than as pure cyber aggression or cyber victimization. Thus, “pure” cyberbully and cyber victim categories have not yet been found with empirical methods of assessment, albeit in research that has used only frequency and form of cyber aggression as indicators.

There are theoretical and empirical grounds for suggesting that person-oriented analyses using measures of aggressive (proactive versus reactive) function may reveal different groups of cyber aggressor-victims than analyses that focused only on frequency and form of cyber aggression. Proactive aggression is defined as goal-directed and unprovoked, whereas reactive aggression is an impulsive and defensive response to a perceived threat or frustration (Hubbard, McAuliffe, Morrow, & Romano, 2010). Consistent with the goal-directedness of bullying (see Volk et al., 2014), proactive aggression has been related more strongly and consistently to being a traditional bully (Camodeca & Goossens, 2005; Salmivalli & Nieminen, 2002; Sijtsema, Veenstra, Lindenburg, & Salmivalli, 2009) and a cyberbully (Ang, Huan, & Florell, 2014; Calvete, Orue, Estevez, Villardon, & Padilla, 2010) than has reactive aggression. In contrast, reactive aggression has been more consistently related to being a bully-victim (Salmivalli & Nieminen, 2002), and bully-victims exhibit more reactive aggression than do bullies (Runions, Salmivalli, Shaw, Burns, & Cross, 2018; Salmivalli & Nieminen, 2002). However, other research suggests that both bullies and bully-victims engage in proactive and reactive aggression (e.g., Camodeca, Goossens, Terwogt, & Schuengel, 2002). According to person-oriented research, traditional aggressors tend to engage in both proactive and reactive aggression; some individuals use both to similar degrees, while others are more highly involved in reactive than proactive aggression (Smeets et al., 2017; Thomson & Centifanti, 2018). Likewise, other research suggests that adolescents are motivated to engage in cyber aggression for both proactive and reactive reasons (Law, Shapka, Domene, & Gagne, 2012; Runions, Bak, & Shaw, 2017; Shapka & Law, 2013).

Therefore, in the current study, we investigated whether including proactive and reactive functions of cyber aggression as indicators in an empirical person-centered analysis would distinguish cyber aggressive-victims involved in both functions of cyber aggression to similar degrees (i.e., mixed cyber aggressor-victims) from those who are more reactively cyber aggressive (i.e., highly reactive cyber aggressive-victims). This distinction may be important because these groups likely experience different social advantages and disadvantages.

Based on theory and empirical evidence in traditional aggression research, we expected that highly reactive cyber aggressive-victims would be likely to experience more social disadvantages and fewer social advantages than mixed cyber aggressive-victims. In comparison to reactive aggression, proactive aggression is more effective for attaining goals because it is strategic, goal-directed, and linked to greater self-efficacy and the expectation of positive outcomes (Hubbard et al., 2010). Accordingly, proactive aggression has been associated with higher levels of, and increases in perceived popularity (van den Berg, Burk, & Cillessen, 2019; Prinstein & Cillessen, 2003), and bullying has been linked to social dominance (Reijntjes et al., 2013a). While social advantages may mark adolescents as intrasexual rivals (e.g., Fink, Klappauf, Brewer, & Shackelford, 2014; Vaillancourt & Sharma, 2011), research suggests that victimization is less likely to reduce powerful adolescents’ social advantages or harm their cooperative relationships (Hunter, Boyle, & Warden, 2007; Vaillancourt & Hymel, 2006; Ybarra, Espelage, & Mitchell, 2014).

In contrast, reactive aggression is associated with distrust and a tendency to aggress in response to real or perceived provocation (Hubbard et al., 2010). As a result, it is associated with emotional dysregulation and social disadvantages that impair cooperative relationships, including the formation of more conflictual and less supportive and satisfying friendships amongst boys (Poulin & Boivin, 1999). Reactive aggression has also been linked to low implicit social power, which refers to the ability to obtain social resources and positive perceptions freely conferred by peers, including positive attention, admiration, liking, and support from allies (Farrell & Dane, 2019; Vaillancourt & Hymel, 2006). For example, reactive aggression has been linked to peer rejection and low social preference (Card & Little, 2006; van den Berg et al., 2019), as well as teacher ratings of uncooperativeness (Price & Dodge, 1989). Furthermore, in comparison to proactive aggression, reactive aggression has been more strongly linked to victimization (Card & Little, 2006), which is associated with low alliance formation ability (Farrell & Dane, 2019). Social disadvantages are likely both antecedents and consequences of reactive aggression, making highly reactive adolescents provocative and vulnerable to a cycle of victimization and retaliation, as well as ineffective in achieving social benefits (see Hubbard et al., 2010).

This study aimed to (1) use proactive and reactive cyber aggression, and cyber victimization, as indicators to empirically identify cyber aggressive-victimization status groups, and (2) assess how cyber aggression-victimization status groups are differentially linked to evolutionarily relevant social advantages and disadvantages in the domains of resource control (i.e., social dominance), reputation (i.e., implicit social power), and reproduction (i.e., number of dating and sexual partners, and friendship and relationship attachment anxiety and avoidance). Based on previous empirical, person-oriented research on cyber aggression-victimization (Festl et al., 2017; Schultze-Krumbholz et al., 2015) and traditional proactive and reactive aggression (Smeets et al., 2017; Thomson & Centifanti, 2018), we expected to identify three different groups of adolescents: (1) a group not involved in either proactive or reactive cyber aggression, nor cyber victimization; (2) a group of mixed cyber aggressor-victims who use proactive and reactive cyber aggression to similar degrees and experience cyber victimization in the context of intrasexual competition; and (3) a group of highly reactive cyber aggressor-victims who predominately engage in reactive cyber aggression in response to cyber victimization.

Because proactive aggressors have achieved more social advantages than reactive aggressors and non-aggressors in past research (Farrell & Dane, 2019; Reijntjes et al., 2013b), we predicted that mixed cyber aggressor-victims would report more social dominance and dating and sexual partners than would highly reactive cyber aggressor-victims and uninvolved peers. Furthermore, given that aggressive strategies involve a trade-off between social benefits and social costs, we expected both cyber aggressor-victim groups to report more social disadvantages, including less implicit social power and more friendship and relationship attachment anxiety and avoidance, when compared to that of uninvolved peers. However, because social disadvantages have been linked more strongly with reactive than proactive aggression (Card & Little, 2006; Hubbard et al., 2010), we predicted that highly reactive cyber aggressor-victims would report more social disadvantages than mixed cyber aggressor-victims.