The relationship between alexithymia, hostile attribution bias, and aggression
Introduction
Aggression includes any behavior that involves intentional infliction of harm to others (Anderson & Bushman, 2002), such as robbery, assault, and hurting or bullying others. The rate of aggression among college students remains high, despite increasing efforts to curtail these behaviors (Leonard, Quigley & Collins, 2002; Tremblay, Graham & Wells, 2008). Recent studies have indicated that individuals who initiated attacks and those who reported being the target are more prone to mental health problems and behavioral disorders (Ming et al., 2011; Yang et al., 2012). Therefore, it is a crucial step to identify and address factors associated with aggression to develop effective preventive strategies.
Alexithymia may be an important emotional personality predictor of aggression. Alexithymia represents a dimensional emotion-processing deficit comprised of three factors: difficulty identifying feelings (DIF), difficulty describing feelings (DDF), and externally oriented thinking (EOT) (Bagby, Taylor & Parker, 1994). DIF refers to deficits associated with recognizing, interpreting and distinguishing internal signals. DDF refers to a reduction in the ability to communicate feelings, and EOT refers to a thinking style with a preference for external stimuli rather than internal experiences. Corresponding to the three primary characteristics of alexithymia, the 20-item Toronto Alexithymia Scale (TAS-20; Bagby et al., 1994), which is a widely used measure of alexithymia (Taylor, 2000), contains these three dimensions. Although difficulty in processing emotional signals of others’ is not part of the definition, alexithymic individuals appear to be characterized by limited abilities to read others’ emotions, intentions, and desires (e.g., Lyvers, Kohlsdorf, Edwards & Thorberg, 2017). These deficits in emotion-processing may increase the likelihood of an individual engaging in aggressive responses. For instance, researchers suggested that deficits in emotion perception could be an important component for the development of antisocial behavior (Bowen & Dixon, 2010). This point was reiterated by Roberton, Daffern and Bucks (2015), who suggested that the deficits in attending to, and communicating, negative emotions are responsible for the increased risk of aggression in adult criminal offenders, rather than the negative emotions alone. Cohn, Seibert, and Zeichner (2009) suggested that to express and terminate internal distress, men may resort to destructive externalizing behaviors if they have difficulty expressing, sharing, or displaying their emotions in masculine-relevant threatening situations. A direct association between alexithymia and aggression has also been demonstrated among different populations, spanning from community samples, to clinical populations (e.g., Velotti et al., 2016).
Despite the findings mentioned, further studies are needed to improve our general understanding about the correlation between alexithymia and aggression. The reasons are as follows.
Alexithymia is regarded as a heterogeneous and dimensional structure (e.g., Kajanoja, Scheinin, Karlsson, Karlsson & Karukivi, 2017). The three dimensions of alexithymia showed several important distinctions. To begin with, EOT is conceptually distinct from DIF and DDF. Specifically, EOT may be linked to emotional deficits but is not defined as a deficit per se, whereas DIF and DDF are conceptualized as deficit-based components (Bagby et al., 1994). Meanwhile, DIF and DDF tend to show stronger associations (as compared to EOT) with a wide range of relational and emotional difficulties (e.g., Paivio & McCulloch, 2004; Shishido, Gaher & Simons, 2013; Spitzer, Siebel-Jürges, Barnow, Grabe & Freyberger, 2005). Therefore, an increasing number of researchers encourage the analysis of alexithymia total scores as well as individual subscales scores (e.g., Kajanoja et al., 2017).
Individual facets of alexithymia may differentially relate to the various subtypes of aggression. Based on the motivations and functions, aggression is divided into two categories: reactive aggression (RA) and proactive aggression (PA) (Dodge & Coie, 1987). RA occurs as a defensive response to perceived threat, provocation, or frustration, while PA is considered to be an offensive, instrumental behavior conducted in anticipation of some benefits (Dodge & Coie, 1987). On one hand, DIF has been suggested to be a strong predictor of impulse control problems, such as problem gambling and compulsive buying, while DDF and EOT were not (Mitrovic & Brown, 2009; Rose, 2012). Therefore, it could be speculated that among alexithymia factors, DIF may be the strongest correlate of reactive aggression, a construct that can also be defined as impulsive aggression (Stanford et al., 2003). On the other hand, in contrast to DIF and DDF, EOT is uniquely related to certain traits characterized by callousness (i.e., lack of empathy or guilt) and fear insensitivity (Essau, Sasagawa & Frick, 2006; Karpman, 1941). While callousness and insensitivity (e.g., underestimate the probability of being punished) have been suggested as predictors of proactive aggression, they were not predictors of reactive aggression (Marsee & Frick, 2007). Therefore, among alexithymia factors, EOT may be the strongest correlate of proactive aggression.
In sum, the three alexithymia factors may not show equally strong associations with reactive and proactive aggression. However, previous research has consistently demonstrated that alexithymia was positively associated with impulsive or reactive aggression (Edwards & Wupperman, 2017, Fossati et al., 2009, Teten et al., 2008). Few studies had examined the association between alexithymia and proactive aggression, even fewer the associations between alexithymia factors and aggression subtypes. Therefore, studies adopting a sub-dimensional approach are needed.
There is an increasing emphasis on exploring the interactive effects of risk factors contributing to aggression (Anderson and Bushman, 2002; Konrath, Novin & Li, 2012). In addition to alexithymia, HAB is an important individual factor related to aggression (De Castro, Veerman, Koops, Bosch & Monshouwer, 2002). HAB refers to the tendency to interpret the actions of the provocateur as intentionally hostile, even in ambiguous situations (Dodge & Somberg, 1987). According to the Social Information Processing (SIP) model (Crick & Dodge, 1994), information processing is comprised of six stages: (1) information encoding (i.e. ‘what happened’, (2) interpreting (i.e. ‘why it happened’, (3) possible goals selection (e.g., maintain relationship or terminate intrusion), (4) response selection, (5) evaluation of possible responses, and (6) selecting the most positively evaluated response. Deficits or biases occurring in any of these stages can contribute to aggression. HAB could reflect a deficit in the second stage where the information is being interpreted. A recent meta-analysis showed that HAB, a widely studied construct in the SIP model, was positively associated with aggressive behaviors (De Castro et al., 2002).
In contrast to alexithymia, as an emotional personality variable, HAB is an important cognitive personality variable that has been linked to aggression. Based on the SIP model, Lmerise and Arsenio (2000) proposed a revised model that integrated temperament and emotional factors into the previous cognitive model, to expand the model's explanatory power. According to this amended model, cognitive and affective factors may interact and culminate in aggression (Lemerise & Arsenio, 2000). Although in the integrated model, it is not well articulated how different factors interact. Researchers have demonstrated that HAB is an important moderator for aggression socialization (Molano, Jones, Brown & Aber, 2013). Meanwhile, Konrath and colleagues (2012) investigated how alexithymia interacts with partner characteristics (in-group vs. out-group) in predicting aggression. Results showed that the effect of alexithymia on aggression was only found after interacting with out-group (i.e., different religious or political backgrounds) members. One possible reason is that high-level alexithymic individuals might be elicited higher levels of threat perceptions in the out-group condition than low-level alexithymic individuals. No such differences emerged in the in-group condition (Konrath et al., 2012). As such, perceptions of threat may strengthen the association between alexithymia and aggression. Therefore, we supposed that HAB, which represents an individual's tendency to perceive threat, betrayal, and hurt in interpersonal situations (Coccaro, Noblett & Mccloskey, 2009), may serve as a moderator. We specifically expected that the link between alexithymia and aggression would be stronger for individuals with relatively higher rather than lower levels of HAB.
The present study aimed to obtain more precise information about the correlation between alexithymia and aggression. On one hand, this study adopted a sub-dimensional approach to explore the unique relationship between different dimensions of alexithymia and subtypes of aggression. It was hypothesized that the three alexithymia factors would not show equally strong associations with reactive aggression and proactive aggression (hypothesis 1). Specifically, DIF would show a stronger association with reactive aggression than DDF or EOT, while EOT would show a stronger association with proactive aggression than DIF or DDF. On the other hand, the present study investigated how alexithymia and HAB interact, contributing to an increase in aggression. It was hypothesized that HAB would moderate the relationship between alexithymia and aggression (hypothesis 2). Given the limited empirical research on the moderating role of HAB in the relationship between alexithymia dimensions and aggression subtypes, no specific hypothesis was formulated. We tested these hypotheses among college students, a sample who is experiencing transitional periods with a high risk for aggression (Leonard et al., 2002; Tremblay et al., 2008).
Section snippets
Participants and procedure
The study sample included 485 college students (275 females, 56.70%) with a mean age of 20.39 (standard deviation (SD) = 1.67, range from 17 to 27 years). The university's institutional review board provided ethics approval for this study. All participants provided written informed consent and participation was completely voluntary. Every participant in the present study completed the following psychological instruments, including the Chinese version (Zhu et al., 2007) of TAS-20, the Social
Descriptive statistics and correlations
All study variables were checked for outliers (± 3 SDs). Data from six participants were then excluded, resulting in a total of 479 participants (mean ± SD age, 20.38 ± 1.66) whose data remained for further analyses. T-tests showed that males reported higher levels of EOT [t (1, 477) = 1.93, p = 0.054], HAB [t (1, 477) = 2.63, p = 0.009], reactive aggression [t (1, 477) = 2.76, p = 0.006], proactive aggression [t (1, 477) = 5.79, p < 0.001], and total aggression [t (1, 477) = 5.02, p < 0.001]
Discussion
The present study aimed to further clarify the correlation between alexithymia and aggression. Consistent with prior research, results showed a positive association between alexithymia and aggression. However, in line with our hypotheses, different alexithymia factors did not show equally strong associations with aggression subtypes. Specifically, DIF was the only alexithymia factor that showed a positive correlation with reactive aggression, while EOT (in contrast to DIF and DDF) was the
Ethical statement
We confirm that all study participants provided informed consent, and the study design was approved by the Institutional Review Board at Shanghai Normal University, China.
We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.
CRediT authorship contribution statement
Xu Li: Methodology, Writing - original draft. Bingbing Li: Data curation, Formal analysis. Jiamei Lu: Conceptualization. Li Jin: Writing - review & editing. Juan Xue: Writing - review & editing. Xianwei Che: Writing - review & editing.
Declaration of Competing Interest
none.
Acknowledgments
This Project was granted financial support from China Postdoctoral Science Foundation (2018M642053; 2019M651544).
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