How is Trait Anger Related to Adolescents’ Cyberbullying Perpetration? A Moderated Mediation Analysis

Abstract

Although trait anger has been shown to play an important role in cyberbullying perpetration, little is known about mediating and moderating mechanisms underlying this relationship. In the present study, we examined whether moral disengagement mediated the relationship between trait anger and cyberbullying perpetration, and whether this mediating process was moderated by empathy. Four hundred and fifty-five Chinese adolescents completed the measures of trait anger, moral disengagement, cyberbullying perpetration, and empathy. The results indicated that trait anger was significantly and positively associated with cyberbullying perpetration and this relationship was partially mediated by moral disengagement. Moderated mediation analysis further indicated that empathy moderated the relationship between moral disengagement and cyberbullying perpetration. This relationship became weaker for adolescents with higher levels of empathy. Results highlight the significance of identifying the mechanisms that moderate the mediated paths between trait anger and adolescents’ cyberbullying perpetration.

Keywords

trait anger moral disengagement cyberbullying perpetration empathy adolescents

Introduction

With the progress of science and technology, especially the development of mobile phones, people could engage in an army of online activities. While the population of China is about 1.4 billion, there are already more than 800 million Chinese mobile phone users (CNNIC, 2019). The development of internet has established a convenient interpersonal communication environment for adolescents and has a positive impact on their social and emotional development (Tokunaga, 2010). However, adolescents who use the internet often get into problems, such as cyberstalking (Seto, 2002), sexual predation (Dombrowski et al., 2004), and cyberbullying perpetration (Bhat, 2008). Among them, the probability of cyberbullying perpetration is very high (Fahy et al., 2016). For instance, cyberbullying perpetration among Chinese adolescents is relatively common with 34.84% having bullied someone (Zhou et al., 2013).

Prior research suggests that cyberbullying perpetration involvement, even witnessing, may be associated with future substance use in adolescence (Yoon et al., 2019). And a large number of cyberbullying perpetration incidents, coupled with the high severity of the incidents, has threatened the mental and physical health of adolescents, with victims experiencing harmful consequences such as psychosomatic symptoms (Patchin & Hinduja, 2006), antisocial behaviors (Low & Espelage, 2013), or even suicidal ideation and attempts (van Geel et al., 2014). Given the negative consequences, it is of theoretical and practical importance to explore those factors that may contribute to an increase in adolescents’ cyberbullying perpetration.

Nevertheless, to date, most researches on cyberbullying perpetration were from North America and Europe, little attention has been given in Asian (Chen et al., 2017). It is important to note that because of Chinese culture of suppressing emotional expression (Soto et al., 2011), Chinese adolescents may be more likely to vent their anger through cyberbullying perpetration. To fill these gaps, this study used Chinese adolescents as samples to examine the effect of trait anger on cyberbullying perpetration and extend previous research by investigating the mediating effect of moral disengagement and the moderating effect of empathy on this relationship.

Trait Anger and Cyberbullying Perpetration

Cyberbullying perpetration is considered as a type of bullying, since it follows the criteria of intentionality, repetition, and power imbalance (Olweus, 2013). It also refers to “an aggressive, intentional act carried out by a group or individual, using electronic forms of contact, repeatedly and over time against a victim who cannot easily defend him or herself” (Smith et al., 2008). Specificities of cyberbullying perpetration compared to traditional bullying, however, stem from social media’s affordances of connectivity, visibility, social feedback, persistence, and accessibility. These affordances imply that the negative effects of cyberbullying perpetration are more lasting, and there is no geographical limit to the negative effects of cyberbullying perpetration (Hinduja & Patchin, 2007). Therefore, cyberbullying perpetration may have a stronger psychosocial impact on those involved (Campbell et al., 2012).

Trait anger is defined as a tendency to react with anger across time and situations, where individuals become angry often in various situations (Tanrikulu & Campbell, 2015a). It is stable individual differences in the propensity to experience anger as an emotional state (Owen, 2011; Wilkowski & Robinson, 2008, 2010). Feelings of anger were more likely to foster participation in cyberbullying perpetration (Patchin & Hinduja, 2011). This effect can be explained by General Strain Theory (GST) which focused on negative emotions and affect (Agnew, 1985, 1989, 1992). Agnew (1992) defines three main sources of strain: (a) failure to achieve the goal valued by the individual; (b) elimination of positive stimuli, and (c) noxious situations or events, which cause negative emotions and ultimately lead to delinquency (Ackerman & Sacks, 2012). According to this theory, anger arises in reaction to these stimuli and increases the possibility of cyberbullying perpetration (Ak et al., 2015). Prior research suggests that anger is one of the main predictors of cyberbullying perpetration (Lonigro et al., 2015; Patchin & Hinduja, 2011). These findings highlight the value of decreasing anger in reducing cyberbullying perpetration.

It is important to note, however, that previous studies have focused primarily on the direct relationship between trait anger and cyberbullying perpetration. The mediating mechanism (i.e., how trait anger relates to cyberbullying perpetration?) and moderating mechanism (i.e., when the link is most potent?) underlying this relationship remain largely unknown. Answers to these questions are essential for a better understanding of the etiology of cyberbullying perpetration and the development of targeted intervention programs. Therefore, the current study utilized a sample of adolescents to examine a moderated mediation model in which, first, moral disengagement mediated the relationship between trait anger and cyberbullying perpetration; second, the direct and indirect relationships between trait anger and cyberbullying perpetration through moral disengagement was moderated by empathy.

Moral Disengagement as a Mediator

Bandura’s theory of moral agency (Bandura, 1999) is formulated to explain why people exhibit behaviors that contradict their own moral standards. Moral disengagement refers to the cognitive process individuals use to justify behaviors that they know are wrong, that is, their moral reasoning is adequate but is selectively disengaged from their behavior (Bandura et al., 1996). Previous research has supported moral disengagement theory that moral disengagement mechanisms can make individuals reconstruct aggression cognitively; thus, aggression is more likely to occur (Bandura et al., 1996). For instance, numerous cross-sectional studies have found that moral disengagement is positively associated with various forms of aggressive behavior such as physical aggression, verbal aggression, bullying, and cyberbullying perpetration (Bussey, Quinn, et al., 2015; Gao et al., 2017; Gini et al., 2014; Obermann, 2011; Wang et al., 2016).

For cyberbullying perpetration, moral disengagement can serve as a cognitive predictor of cyberbullying perpetration (Wang, Yang, et al., 2017). One explanation for this connection is that perpetrators’ inability to see the victims during and after the cyberbullying perpetration incidents could increase moral disengagement and the incidence of cyberbullying perpetration (Bauman, 2010; Perren & Gutzwiller-Helfenfinger, 2012). Specifically, compared to traditional bullying, cyberbullying perpetrators may feel less guilt, shame, or sympathy towards the victims since the distanced nature of mediated communication (Perren & Gutzwiller-Helfenfinger, 2012; Tanrikulu & Campbell, 2015b). Unable to witness negative experiences of the victims, perpetrators may be motivated to engage in more online harmful behaviors which may conflict with their moral beliefs (Tanrikulu & Campbell, 2015b). These viewpoints have been confirmed that perpetrators of cyberbullying lack remorse towards their victims (Slonje et al., 2012), and this may be the reason why cyberbullies may violate their moral values (Wachs, 2012). Some studies suggest that there is a significant correlationship between moral disengagement and cyberbullying perpetration (Wang, Yang, et al., 2017; Wang, Yang et al., 2019; Wang, Zhao, et al., 2019).

Previous research shows that individuals with higher levels of trait anger often have defects in self-regulation ability in addressing anger (Aricak & Ozbay, 2016). Hence, trait anger may create conditions for cognitive distortions beneficial to justify cyberbullying perpetration (Wang, Yang, et al., 2017). That is, high trait anger individuals are prone to experience and act upon feelings of revenge and bullying, and they are more likely to activate cognitive distortions, thereby avoiding self-blame, guilt, shame, and anticipatory punishment. Therefore, trait anger may increase adolescents’ moral disengagement. Some empirical studies have supported this view by showing that the sensation of anger can affect cognitive distortion and facilitate the activation of moral disengagement mechanisms (He & Harris, 2014; Tanrikulu & Campbell, 2015a).

General aggression model (GAM) suggests individual and environmental factors affect individuals’ internal cognitive process, subsequent evaluation, and decision-making process to further influence the occurrence of aggression (Montuoro & Mainhard, 2017). Based on GAM, trait anger (as an individual factor) may activate moral disengagement (internal cognitive process) to influence individual’s propensity to participate in cyberbullying perpetration. Consistent with this hypothesis, recent studies have found that moral disengagement can mediate the relationship between individual factors and cyberbullying perpetration, such as callous-unemotional traits and cyberbullying perpetration as well as trait anger and cyberbullying perpetration (Fang, et al., 2020; Wang, Yang, et al., 2017). More specifically, one study examined with 464 Chinese young adults who filled out questionnaires regarding trait anger, cyberbullying and moral disengagement found that moral disengagement can partially mediate the relationship between trait anger and cyberbullying perpetration after controlling gender and age (Wang, Yang, et al., 2017). It is important to note that adolescents usually have higher anger-related emotional styles and behaviors than young adults (Carstensen et al., 2000; English & Carstensen, 2014; Schieman, 1999). Therefore, it is reasonable to expect that adolescents who have high trait anger are more likely to develop high moral disengagement and in turn bully others online.

Empathy as a Moderator

Although trait anger may affect cyberbullying perpetration through the mediating effect of moral disengagement, not all adolescents prone to anger experience higher levels of moral disengagement (He & Harris, 2014) and display cyberbullying perpetration. Therefore, it is important to explore those factors that may buffer (i.e., moderate) the strength of the relationship between trait anger and cyberbullying perpetration as well as moral disengagement and cyberbullying perpetration. The present study hypothesized that empathy moderated the relationship between trait anger and cyberbullying perpetration as well as moral disengagement and cyberbullying perpetration.

Empathy refers to an ability to understand and share emotions of other individuals with whom we interact (Cohen & Strayer, 1996; Feshbach, 1997), and empathy is assumed to be initiated by the observation of another’s emotional state. As a consequence, empathy is positively associated with prosocial behavior (Juhl et al., 2020; Schoeps et al., 2020), and is negatively related to antisocial behavior (Álvarez-García et al., 2019). Furthermore, two meta-analyses show that individuals with high empathy had lower levels of cyberbullying perpetration (Kowalski et al., 2014; Zych et al., 2019), and the previous study shows that empathy is one of the important protective factors for cyberbullying perpetration (Lee & Shin, 2017). The risk-buffering model holds that protective factors can buffer or weaken the adverse effects of risk factors (Zimmerman et al., 1999). According to this model, the negative effect of trait anger on cyberbullying perpetration will be weakened under the influence of high empathy. Empirical studies have supported this hypothesis. For instance, empathy can moderate the relationship between family-of-origin aggression and electronic dating aggression, such that the positive link between family-of-origin aggression and electronic dating aggression is weaker at higher levels of empathy (Ramos et al., 2021). Similarly, empathy can moderate the relationship between moral disengagement and aggression, such that the positive link between moral disengagement and aggression is weaker at higher levels of empathy (Bussey, Quinn, et al., 2015). Moreover, empathy could moderate the direct and indirect effects of trait anger on aggressive behavior via hostile cognition (Jiang et al., 2019). To our knowledge, however, no previous study has examined whether empathy is a protective factor that buffers the adverse effects of trait anger and moral disengagement on adolescents’ cyberbullying perpetration.

The Present Study

Taken together, the aims of the present study were twofold. First, the present study tested whether moral disengagement would mediate the relationship between trait anger and cyberbullying perpetration. Second, the present study tested whether the direct and indirect relationships between trait anger and cyberbullying perpetration through moral disengagement would be moderated by empathy. These two research questions form a moderated mediation model, which can address both mediation (i.e., how does trait anger lead to cyberbullying perpetration?) and moderation (i.e., when the link is most potent?) mechanisms underlying the relationship between trait anger and cyberbullying perpetration. Based on the literature review, we proposed the following hypotheses:

Hypothesis 1. Moral disengagement would mediate the relationship between trait anger and cyberbullying perpetration.

Hypothesis 2. Empathy would moderate the relationship between trait anger and cyberbullying perpetration as well as moral disengagement and cyberbullying perpetration. Specifically, the relationship between trait anger and cyberbullying perpetration as well as moral disengagement and cyberbullying perpetration would be much weaker for adolescents with higher levels of empathy.

Method

Participants

A total of 455 middle school students (including 216 male students) participated in our survey. The participants were recruited from one middle school in Taiyuan, China. In this school, 10 classes were selected to participate in the present study. Data were collected during the school year from April to May 2017. The mean age of the participants was 13.53 years (SD = 0.92, range = 11–16 years). The reason for choosing this age group is that the rate of cyberbullying perpetration peaks in early adolescence (Kowalski et al., 2014).

Measures

Trait anger.

Trait anger was measured using the 10-item Trait Anger subscale of the State-Trait Anger Expression Inventory-II which assessed the experience and expression of anger (Spielberger, 1999). A representative item was: “I get angry easily.” Adolescents rated each item on a 4-point scale ranging from 1 (almost never) to 4 (almost always). Responses across the 10 items were averaged, with higher scores representing a greater tendency to experience anger in a wide range of situations. It has shown good validity and reliability in the Chinese population (Wang, Yang, et al., 2017). For the current study, its Cronbach’s α was .91.

Cyberbullying perpetration.

Cyberbullying perpetration was assessed by the Cyberbullying Scale developed by Wright (2014). Participants were asked how often they engaged in cyberbullying perpetration through information and verbal aggression such as social networking sites, text messages, and email on a scale of 1 (never) to 5 (all the time). A representative item was: “Do you often ignore peers online or via text messages?” Responses across the nine items were averaged, with higher scores indicating higher levels of cyberbullying perpetration. It has been used in Chinese adolescents and shows good validity and reliability (Wang, Zhao, et al., 2019). In the present research, its Cronbach’s α was .88.

Moral disengagement.

The Moral Disengagement Scale developed by Bandura et al. (1996) consists of 32 items, with four items measuring each of the eight moral disengagement mechanisms including moral justification, euphemistic language, advantageous comparison, displacement of responsibility, diffusion of responsibility, distorting consequences, attribution of blame, and dehumanization. A representative item was: “You can hit people who insult your family.” Adolescents rated each item on a 5-point scale ranging from 1(strongly disagree) to 5 (strongly agree). Responses across the 32 items were averaged, with higher scores representing higher levels of moral disengagement. The Chinese version of the Moral Disengagement Scale has been demonstrated to be a reliable and valid measurement in assessing moral disengagement (Wang, Lei, et al., 2017). For the current study, the measure also demonstrated good reliability (α = .93).

Empathy.

The Interpersonal Reactivity Index (IRI) was used to test participants’ empathy (Davis, 1983; Huang et al., 2011). The IRI is a 28-item self-report questionnaire comprised of four subscales (7 items each): perspective taking (PT), fantasy scale (FS), empathetic concern (EC), and personal distress (PD). Some researchers argue that PT and EC are representative of the empathetic response (Siu & Shek, 2005). Therefore, the present study following previous research used PT and EC to examine adolescents’ empathy (Cheng, 2014; Prot et al., 2014). Items are rated from 0 (Does not describe me well) to 4 (Describes me very well). Responses to these two subscales were summed to produce a composite score, with higher levels of empathy. Examples of items include: “Sometimes I envision how others see things to better understand my friends;” “I am easily moved by what I have experienced.” In this research, its Cronbach’s α was .77

Procedure

The study was approved by the Research Ethics Committee of the first author’s institution. Trained research assistants conducted the survey with standardized instructions in classrooms. Informed consent was obtained from the participants and their parents before data collection. Participants were informed that their participation was completely voluntary and they could terminate the participation anytime. We checked all questionnaires for completeness when adolescents finished.

Statistical Analyses

First, the descriptive information and correlationship matrix were calculated. Second, we followed the four-step procedure (Baron & Kenny, 1986) to establish a mediation effect. Third, we examined whether the mediation process was moderated by empathy. Moderated mediation is often applied to test whether the magnitude of a mediation effect is conditional on the value of a moderator (Muller et al., 2005). The analyses of moderated mediation were constructed using Hayes’s (2013) PROCESS macro (Model 15). All continuous variables were standardized and the interaction terms were computed from these standardized scores. Besides, the bootstrapping method was applied to examine the significance of all the effects to obtain robust standard errors for parameter estimation (Hayes, 2013). The bootstrapping method produced 95% bias-corrected confidence intervals of these effects from 1,000 resamples of the data. Confidence intervals did not include zero indicating the effect was significant.

Results

Preliminary Analyses

Means, standard deviations, and zero-correlationships for all study variables are presented in Table 1. As expected, for adolescents with a high of trait anger, they were more likely to have a high level of cyberbullying perpetration and moral disengagement. For adolescents with a high level of moral disengagement, they were more likely to bully others online. Empathy was negatively related to trait anger, moral disengagement, and cyberbullying perpetration.

Table 1.

Descriptive Statistics and Correlations Among Variables of Interest.

	M	SD	1	2	3	4	5	6
1. Gender	–	–	1
2. Age	13.53	0.92	–.14**	1
3. Trait anger	1.69	0.64	–.03	.03	1
4. Moral disengagement	1.84	0.59	–.20**	.12*	.28**	1
5. Empathy	3.52	0.63	.15**	.03	–.18**	–.21**	1
6. Cyberbullying perpetration	1.35	0.53	–.15**	.03	.32**	.38**	–.18**	1

Note. Gender was dummy coded such that 1 = Female and 0 = Male.

*p < .05. **p < .01. ***p < .001.

Table 2.

Testing the Mediation Effect of Trait Anger on Cyberbullying Perpetration.

Predictors	Model 1		Model 2		Model 3
	(Cyberbullying)		(Moral Disengagement)		(Cyberbullying)
	b	t	b	t	b	t
Gender	–.29	–3.24**	–.37	–4.14***	–.18	–2.08*
Age	–.00	–.08	.08	1.89	–.03	–.66
Trait anger	.32	7.28***	.28	6.26***	.24	5.46***
Moral disengagement					.29	6.49***
R²	.13		.13		.20
F	21.61***		21.52***		28.20***

Note. Each column is a regression model that predicts the criterion at the top of the column.

Gender was dummy coded such that 1 = Female and 0 = Male.

*p < .05. **p < .01. ***p < .001.

Testing for the Mediation Effect

In Hypothesis 1, the current study assumed that moral disengagement would mediate the link between trait anger and cyberbullying perpetration. To examine this hypothesis, this study followed the four-step procedure (Baron & Kenny, 1986) to establish the mediation effect, which requires (a) a significant relationship between trait anger and cyberbullying perpetration; (b) a significant association between trait anger and moral disengagement; (c) a significant association between cyberbullying perpetration and moral disengagement while controlling for trait anger; and (d) a significant coefficient for the indirect path between trait anger and cyberbullying perpetration via moral disengagement. The bias-corrected percentile bootstrap method determined whether the last condition was satisfied.

Multiple regression analysis showed that, in that first step, trait anger was significantly associated with cyberbullying perpetration, b = .32, p < .001 (see Model 1 of Table 2). In the second step, trait anger was significantly associated with moral disengagement, b = .28, p < .001 (see Model 2 of Table 2). In the third step, when controlling for trait anger, moral disengagement was associated with cyberbullying perpetration, b = .29, p < .001 (see Model 3 of Table 2). Finally, the bias-corrected percentile bootstrap method indicated that the indirect effect of trait anger on cyberbullying perpetration was .08, SE = .025, 95% CI = [.04, .13]. The mediation effect accounted for 25% of the total effect. Overall, the four criteria for establishing mediation effect were totally satisfied. Therefore, Hypothesis 1 was supported.

Testing for the Moderated Mediation

Hypothesis 2 assumed that empathy would buffer the relationships between trait anger and cyberbullying perpetration via moral disengagement. To test this moderated mediation hypothesis, we used the PROCESS macro (Model 15) developed by Hayes (2013) to examine for the moderated mediation. To be specific, we estimated parameters for two regression models. In Model 1, we examined the relationship between trait anger and moral disengagement. In Model 2, we estimated the moderating effect of empathy on the relationship between trait anger and cyberbullying perpetration as well as moral disengagement and cyberbullying perpetration. The specifications of the two models can be seen in Table 3. In each model, we controlled for gender and age.

Table 3.

Testing the Moderating Effects of Moral Disengagement and Empathy on the Relationship Between Trait Anger and Cyberbullying Perpetration.

Predictors	Model 1		Model 2
	(Moral Disengagement)		(Cyberbullying)
	b	t	b	t
Gender	–.37	–4.14***	–.17	–1.91
Age	.08	1.89	–.02	–.40
Trait anger	.28	6.26***	.23	5.11***
Empathy			–.07	–1.54
Trait anger × Empathy			.01	.30
Moral disengagement			.27	5.86***
Moral disengagement × Empathy			–.10	–2.29*
R²	.13		.21
F	21.52***		17.32***

Note. Each column is a regression model that predicts the criterion at the top of the column.

Gender was dummy coded such that 1 = Female and 0 = Male.

*p < .05. ***p < .001.

As Table 3 demonstrates, in Model 1 there was a main effect of trait anger on moral disengagement, b = .28, p < .001. Model 2 indicated that the effect of trait anger on cyberbullying perpetration was significant, b = .23, p < .001, and this effect was not moderated by the empathy, b = .01, p = .77. Finally, Model 2 also indicated that there was a significant main effect of moral disengagement on cyberbullying perpetration, b = .27, p < .001, and more importantly, this effect was buffered by empathy, b = –.10, p < .05. For descriptive purposes, this study plotted moral disengagement on cyberbullying perpetration, separately for low and high levels of empathy (1 SD below the mean and 1 SD above the mean, respectively; Figure 1). Simple slope tests demonstrated that for adolescents with low empathy, moral disengagement was significantly associated with cyberbullying perpetration, b = .37, p < .001. For adolescents with high empathy, this relationship was still significant but much weaker, b = .17, p < .05.

Figure 1.

Interaction between moral disengagement and empathy on cyberbullying perpetration.

The bias-corrected percentile bootstrap method further indicated that the indirect effect of trait anger on cyberbullying perpetration via moral disengagement was buffered by empathy. For adolescents with low levels of empathy, the indirect effect of trait anger on cyberbullying perpetration via moral disengagement was significant, b = .10, SE = .04, 95% CI = [.05, .17]. For adolescents with high levels of empathy, trait anger had weaker effect on cyberbullying perpetration through moral disengagement, b = .05, SE = .02, 95% CI = [.01, .10]. Therefore, Hypothesis 2 was partially supported.

Discussion

The effect of anger on cyberbullying perpetration has gained substantial empirical support (Ak et al., 2015; Kowalski et al., 2014; Lonigro et al., 2015; Patchin & Hinduja, 2011). However, questions regarding the mediating and moderating mechanisms underlying this relationship remain largely unanswered. We formulated a moderated mediation model to test whether trait anger would be indirectly related to cyberbullying perpetration via moral disengagement, and whether the direct and indirect relationships between trait anger and cyberbullying perpetration were moderated by empathy. Our findings indicated that the adverse effect of trait anger on cyberbullying perpetration was partially explained by moral disengagement. Furthermore, the relationship between moral disengagement and cyberbullying perpetration was moderated by empathy, such that the path from moral disengagement to cyberbullying perpetration was weakened in the context of higher empathy. The following sections discuss each of the hypotheses in light of this moderated mediation model of trait anger and cyberbullying perpetration.

The Mediating Role of Moral Disengagement

We first tested the association between trait anger and cyberbullying perpetration. Consistent with our hypothesis, moral disengagement mediates the relationship between trait anger and cyberbullying perpetration. This is consistent with the previous findings that moral disengagement is a crucial mediation mechanism of the associations of trait anger with cyberbullying perpetration (Wang, Yang, et al., 2017). Our finding argues for the important role of moral disengagement in helping to explain the relationship between trait anger and cyberbullying perpetration. The GAM states that trait anger, as an individual factor, may activate moral disengagement to influence individual’s propensity to participate in cyberbullying perpetration. That is, trait anger as a personality construct that refers to stable individual differences in the propensity to experience anger as an emotional state (Owen, 2011; Wilkowski & Robinson, 2008, 2010), according to GAM, can predict cyberbullying perpetration via the mechanism of moral disengagement, which can serve as a means to justify cyberbullying perpetration (Wang et al., 2016).

In addition to the overall mediation result, each of the separate links in our mediation model is noteworthy. For the first stage of the mediation process (i.e., trait anger ↓ moral disengagement), our results support the premise that trait anger can facilitate the activation of moral disengagement mechanisms. This finding is consistent with previous researches (He & Harris, 2014; Tanrikulu & Campbell, 2015a). Specifically, adolescents with higher trait anger are prone to experience anger, which may activate cognitive distortions and increase moral disengagement. This result may be explained by adolescents with higher levels of trait anger usually have defective self-regulatory capacities in resolving anger (Aricak & Ozbay, 2016). Consequently, trait anger sets the conditions for cognitive distortions conducive to justify cyberbullying perpetration. For the second stage of our mediation model (i.e., moral disengagement↓ cyberbullying perpetration), the present study found that there is a significant correlationship between moral disengagement and cyberbullying perpetration. This finding is consistent with Bandura’s moral disengagement theory (Bandura et al., 1996) and the previous studies suggest that individuals who have higher levels of moral disengagement are more likely to engage in cyberbullying perpetration (Bussey, Fitzpatrick, et al., 2015; Chen et al., 2017; Lazuras et al., 2013; Meter & Bauman, 2018; Orue & Calvete, 2019; Wang et al., 2016). That is, moral disengagement mechanisms can make individuals reconstruct cyberbullying perpetration cognitively.

The Moderating Role of Empathy

The second goal of the present study was to explore the moderating effect of empathy on the direct and indirect associations between trait anger and cyberbullying perpetration via moral disengagement. The indirect relationship between trait anger and cyberbullying perpetration via moral disengagement was moderated by empathy. However, empathy only moderated the second stage of the mediation process (i.e., the relationship between moral disengagement and cyberbullying perpetration). This is roughly consistent with the previous findings that the link between moral disengagement and aggression is moderated by empathy (Bussey, Quinn, et al., 2015). This finding can be explained by Bandura’s (1999) social cognitive theory. Based on this view (Bandura, 1999), individuals with high empathy can consider and appreciate the perspectives of other people (Davis, 1980) or experience emotions of concern, compassion, or sympathy toward a (potential) victim (Davis, 1994), then rethink their own thoughts and behaviors, consider their rationality, and reduce the occurrence of immoral behavior (Bandura, 1999). Thus, for adolescents with higher levels of empathy, the relationship between moral disengagement and cyberbullying perpetration becomes much weaker.

Contrary to our hypothesis, empathy does not buffer the direct relationship between trait anger and cyberbullying perpetration. One possible explanation for this result is that individuals with high trait anger have impaired cognitive resources and are prone to experience and act upon feelings of vengeance and bullying than to experience the feelings of others and feel guilty. Nonetheless, it is premature to discount the importance of empathy, as more research is needed before we can draw any definitive conclusions about empathy’s role in altering the relationship between trait anger and cyberbullying perpetration.

Overall, by incorporating empathy as a moderator into the model, the present study detected effects that would have been neglected without the moderation analysis. The present study indicated that the indirect effect of trait anger on cyberbullying perpetration via moral disengagement was significant for adolescents with low empathy. However, this indirect effect was non-significant for individuals with high empathy. This finding has particular meanings in Chinese culture. Chinese culture of suppressing emotional expression may lead adolescents to vent their anger through cyberbullying perpetration (Soto et al., 2011). Therefore, trait anger may be particularly damaging to adolescents’ cyberbullying perpetration in the Chinese context. Thus, researchers interested in the adverse effect of trait anger on cyberbullying perpetration should work on fostering empathy. The moderated mediation model in the current study is conceptually more nuanced and provides greater predictive power than the mediation model alone.

Limitations and Practical Implications

Several limitations should be considered when interpreting the findings of this study. First, this research was cross-sectional in design, so it cannot infer causality. Second, the data were collected only through self-report measures and it is particularly limited in assessing empathy with IRI, since individuals with low empathy may not be aware of those deficits. Future research can manage to collect date from multiple informants and would be helpful in decreasing this limitation. Third, all participants were middle school students. Future research could benefit from collecting data from different groups. Fourth, this study only investigated the moderating effects of general empathy. Future research can consider the role of cognitive empathy and affective empathy for the two components of empathy. Fifth, gender differences in cyberbullying perpetration are inconsistent (Barlett, & Coyne, 2014). Some studies have shown that boys cyberbullied more than girls (Hinduja & Patchin, 2013; Topcu & Erdur-Baker, 2012), whereas others concluded opposite (Görzig & Ólafsson, 2013; Pornari & Wood, 2010), and in other studies, no gender differences emerged (Perren, & Gutzwiller-Helfenfinger, 2012). Therefore, gender as a covariate was included in this study. Future research should focus on the impact of gender on cyberbullying perpetration to explore the mechanism underlain this association. Finally, the present study was based on Chinese adolescents. The generalizability of our findings should be further justified with samples from other culture countries. Although the current study believes that expression suppression may increase cyberbullying perpetration among Chinese adolescents, expression suppression may also have a positive effect in collectivist cultures. For instance, a cross-cultural study, which recruits 451 college students (205 Chinese and 246 European Americans), indicates that expression suppression is a suitable method to maintain interpersonal harmony in collectivist cultures (Wei et al., 2013). Given that, cultural influence should be considered when examining the adverse effect of trait anger on cyberbullying perpetration.

Despite these limitations, the present study has several practical contributions. Understanding the protective factors and risk factors for individuals who bully others is important to develop prevention and intervention plans to reduce cyberbullying perpetration. First, whether in reality or cyberspace, we should focus on controlling anger and emotional management to reduce the occurrence of cyberbullying perpetration. Second, given the indirect relationship between trait anger and cyberbullying perpetration via moral disengagement, interventions should develop strategies to reduce moral disengagement. Third, considering that the indirect effect of trait anger on cyberbullying perpetration becomes non-significant for high empathy individuals, it can be stated that these findings may help to design effective psychological interventions aimed at improving empathy in adolescents with higher levels of cyberbullying perpetration.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from the Program for the Innovative Talents of Higher Education Institutions of Shanxi and the Ministry of education of Humanities and Social Science project (16YJA190009).

ORCID iD

Xingchao Wang

Author Biographies

Jiping Yang, BA, is a professor in the School of Educational Science, Shanxi University, China. His research interests are in adolescents’ aggression, bullying, and moral disengagement.

Wenqing Li is a postgraduate student in the School of Educational Science, Shanxi University, China. His research interests are in adolescents’ cyberbullying perpetration.

Ling Gao, MA, is an associate professor in the School of Educational Science, Shanxi University, China. Her research interests are in adolescents’ aggression, bullying, and moral disengagement.

Xingchao Wang, PhD, is a professor in the School of Educational Science, Shanxi University, China. His research interests are in adolescents’ cyberbullying perpetration, aggression, bullying, moral disengagement, and parental phubbing.

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