Psychology of Intimate Relationships Week 7
The Link Between Narcissism and Aggression: A Meta-Analytic Review
Sophie L. Kjærvik and Brad J. Bushman School of Communication, The Ohio State University
This meta-analytic review examines the link between narcissism and aggression, and whether the link is stronger under provocation conditions. A total of 437 independent studies were located, which included 123,043 partici- pants. Narcissism was related to both aggression (r = .26, [.24, .28]) and violence (r = .23, [.18, .27]). As expected, the narcissism-aggression link was stronger under provocation conditions (r = .29, [.23, .36]) than under no provocation conditions (r = .12, [.05, .18]), but was even significant in the absence of provocation. Both “normal” and “pathological” narcissism were related to aggression. All three dimensions of narcissism (i.e., entitlement, grandiose narcissism, vulnerable narcissism) were related to aggression. Narcissism was related to all forms of aggression (i.e., indirect, direct, displaced, physical, verbal, bullying), and to both functions of aggres- sion (i.e., reactive, proactive). The relation between narcissism and aggression was significant for males and females, for people of all ages, for students and nonstudents, and for people from individualistic and collectivistic countries. Significant results were obtained in experimental, cross-sectional, and longitudinal studies, in published and unpublished studies, and in studies that assessed aggression using different types of measures (i.e., self-report, other-report, observation). Overall results were robust to publication bias and the presence of outliers. Theoretically, these results indicate that provocation is a key moderator of the link between narcissism and aggression. Individuals high in narcissism have “thin skins” and are prone to aggression when they are provoked. Practically, these results suggest that narcissism is an important risk factor for aggression and violence.
Public Significance Statement This meta-analytic review found that individuals with high levels of narcissism are prone to aggres- sive and violent behavior, especially when they are provoked. There was a triangulation of results across different research methodologies. The relationship was robust for different forms and func- tions of aggression, different types and dimensions of narcissism, and for males and females of dif- ferent ages from different countries.
Keywords: narcissism, aggression, violence, ego-threat, meta-analysis
Supplemental materials: https://doi.org/10.1037/bul0000323.supp
When science discovers the center of the universe, a lot of people will be disappointed to find they are not it.—Bernard Baily, American comic book artist
This quote seems to accurately describe people with high levels of narcissism. The personality trait narcissism was named after the mythological Greek figure Narcissus, who was a handsome, self- absorbed, vain young man who fell in love with his own image reflected in still water. “I burn with love for—me!” Narcissus exclaimed.
In this meta-analytic review, narcissism is defined as “entitled self-importance” (Krizan & Herlache, 2018, p. 6). People with high levels of narcissism think they are special people who deserve special treatment. They have an exaggerated and inflated sense of their own importance. Indeed, narcissism was initially la- beled the “God-complex” (Jones, 1913).
Narcissism Is Not a Dichotomy
Overwhelming empirical evidence suggests that narcissism is continuous variable rather than a dichotomy (for a review see Kri- zan & Herlache, 2018). Thus, we will not refer to individuals with high levels of narcissism as “narcissists.” Calling someone a nar- cissist implies that narcissism is a dichotomous variable, which it
This article was published Online First May 24, 2021. Brad J. Bushman https://orcid.org/0000-0002-1266-5101 We thank Alexandra Blouin, Cecily Exline, David Fuller, Jessica
Kaplan, Claire Teets, and Tess Wells for their help coding studies. We thank Eddie Brummelman, Josh Miller, Aaron Pincus, Sander Thomaes, and Aiden Wright for their helpful feedback on a draft of this article. We thank Sven Kepes for his help conducting the sensitivity analyses, Gertrudes Velasquez and Betsy Becker for their help conducting the analyses for correlated effects, and Matthew Sweitzer for his help with the violin plot. Finally, we would like to thank Golnoosh Behrouzian for her help with Table SM1, the references, and computing intercoder reliability. The data for this meta-analytic review are available on Open Science Framework (OSF) via this link: https://osf.io/m6xek/. Correspondence concerning this article should be addressed to Brad J.
Bushman, School of Communication, The Ohio State University, 3016 Derby Hall, 154 North Oval Mall, Columbus, OH 43210, United States. Email: bushman.20@osu.edu
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© 2021 American Psychological Association 2021, Vol. 147, No. 5, 477–503 ISSN: 0033-2909 https://doi.org/10.1037/bul0000323
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is not. Even the latent structure of narcissistic personality disorder (NPD) is continuous (Aslinger et al., 2018). Because narcissism is a continuous variable, it has a distribu-
tion. However, the distribution of narcissism differs for children and adults. In children ages 7–17, narcissism tends to have a nor- mal, bell-shaped distribution (Thomaes & Brummelman, 2016). In adults 18 and older, narcissism tends to have a positively skewed distribution with a long right tail (Krizan & Herlache, 2018). In other words, most adults have relatively low levels of narcissism, some adults have moderate levels, and a few adults have extremely high levels.
Narcissism Is Not a Unitary Construct
There is growing consensus that narcissism is not a unitary con- struct. Rather, narcissism has important dimensions, although not all researchers agree on what those dimensions are. Two independ- ent groups of scholars recently suggested that the narcissism spec- trum can best be represented using three correlated factors (Wright & Edershile, 2018). One group proposed the Narcissism Spectrum Model (Krizan & Herlache, 2018) to describe these three compo- nents, whereas the other group proposed the Trifurcated model of Narcissism (Weiss et al., 2019). Both groups identified an essential core of narcissism, as well as two peripheral components. One group called the core component entitlement (Krizan & Herlache, 2018), whereas the other group called it antagonistic (Miller et al., 2017). In terms of the two peripheral components, one group called them grandiosity and vulnerability (Krizan & Herlache, 2018), whereas the other group called them extraverted and neu- rotic (Miller et al., 2017). Data show that a three-factor model fits the data better than a
single-factor or two-factor model (Krizan & Herlache, 2018). In this meta-analytic review, we focus on these three components, and we use the terms entitlement, grandiose narcissism, and vul- nerable narcissism. Individuals high in grandiose narcissism tend to have high levels of self-esteem, whereas those high in vulnera- ble narcissism tend to have low levels of self-esteem (Wink, 1991). The grandiose dimension of narcissism is characterized by self-assuredness, imposingness, attention seeking, entitlement, exhibitionism, self-indulgence, and disrespect for the needs of others (Bushman et al., 2009; Wink, 1991). An individual high in grandiose narcissism is often referred to as “hard-headed, aggres- sive, and a show-off” (Wink, 1991, p. 569). The vulnerable dimen- sion is characterized by hypersensitivity to evaluations from others, defensiveness, bitterness, anxiousness, self-indulgence, conceitedness, arrogance, and an insistence on having one’s own way (Wink, 1991). An individual high in vulnerable narcissism is often referred to as “unpredictable and prone to act out unexpect- edly” (Greene, 1991, p. 283). In the past, more emphasis has been given to the grandiose component of narcissism than to the vulner- able component (Cain et al., 2008; Miller et al., 2011; Wright & Edershile, 2018), both in the clinical (i.e., NPD) and subclinical domains. Clinically, the American Psychiatric Association’s (APA) Diag-
nostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM–5; APA, 2013) has consistently emphasized grandiose fea- tures of narcissism. Likewise, the most popular self-report meas- ures of subclinical narcissism, such as the Narcissistic Personality Inventory (NPI; Raskin & Terry, 1988), have emphasized the
grandiose features of narcissism. Unfortunately, this has led to an unbalanced and incomplete picture of narcissism (Wright & Eder- shile, 2018). More recently, researchers have begun developing and measuring the vulnerable features of narcissism. This meta- analytic review will examine the relation between these three fac- tors of narcissism (i.e., entitlement, grandiose narcissism, vulnera- ble narcissism) and aggression.
Pathological Levels of Narcissism
Some scholars have suggested that narcissism has both nor- mal and pathological expressions (e.g., Pincus & Lukowitsky, 2010). Normal narcissism is sometimes called “subclinical nar- cissism” (e.g., Wallace & Baumeister, 2002). Pathological lev- els of narcissism are associated with clinically relevant mental health problems such as depression, suicidal ideation, self- harm, pathological gambling, homicidal ideation, stalking behavior, aggression, and violence (Schoenleber et al., 2015). Those with pathological levels of narcissism have significant regulatory deficits and maladaptive strategies to cope with self- image threats. Thus, individuals with pathological narcissism might be especially prone to lash out at others in an aggressive manner when they are threatened.
In clinical and psychiatric research, pathological expressions of narcissism are typically operationalized using the APA’s DSM–5 (APA, 2013) as NPD, which is defined as a “pervasive pattern of grandiosity (in fantasy or behavior), a constant need for admira- tion, and lack of empathy” (p. 669). Although the latent structure of NPD is continuous (Aslinger et al., 2018), NPD is a dichoto- mous categorization made by mental health professionals typically following clinical interviews. Researchers have also developed a self-report measure of pathological narcissism called the Patholog- ical Narcissism Inventory (PNI; Pincus, 2013; Pincus et al. 2009). The PNI measures two dimensions of narcissism—grandiosity and vulnerability. The grandiosity and vulnerability subscales of the PNI are highly correlated, and individuals high in “pathological narcissism” are thought to have problems with both grandiosity and vulnerability (e.g., Pincus, 2013), although this is an area in need of further research (e.g., Gore & Widiger, 2016; Hyatt et al., 2018). Other self-report measures of narcissism capture so-called “normal narcissism.”
Other scholars disagree that the distinction between normal and pathological narcissism is a meaningful one (e.g., Miller et al. 2017). They argue that whether narcissism is pathological depends on how extreme, inflexible, and pervasive it is, and on whether it causes distress and impairment to the self and to others. These scholars also point out that so-called “normal” measures of narcis- sism, such as the NPI (Raskin & Terry, 1988), are highly corre- lated with clinical symptoms of NPD and ratings of psychopathy (Krusemark et al., 2018; Miller et al., 2009) and generate empiri- cal profiles consistent with expert ratings (Miller et al., 2014, 2016). In addition, so-called normal narcissism is often correlated with maladaptive behaviors, such as aggression and violence (e.g., Bushman & Baumeister, 2002).
This meta-analytic review examines the link between both nor- mal and pathological levels of narcissism and aggression. We will explore whether the link between pathological narcissism (i.e., with high PNI scores, NPD) and aggression is stronger than the link between normal narcissism and aggression.
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Aggression and Violence
The main outcome variable in this meta-analytic review is aggres- sion, which is defined as “any form of behavior directed toward the goal of harming or injuring another living being who is motivated to avoid such treatment” (Baron & Richardson, 1994, p. 7). Aggression can take different forms (Bushman & Huesmann, 2010). For example, physical aggression involves harming others physically (e.g., hitting, kicking, stabbing, or shooting), whereas verbal aggression involves harming others with spoken or written words (e.g., yelling, screaming, swearing, or name calling). Aggression can be expressed directly when the victim is present, or indirectly when the victim is absent (e. g., spreading gossip or rumors behind someone’s back). Aggression can also be displaced onto an innocent target. Bullying involves repeated acts of aggression, which can occur offline or online (called cyberbullying). Offline, the bully is generally large, strong, and intimi- dating so they can “push other people around.” Online, the bully does not need to possess these characteristics. Because there has been some debate about whether there is a meaningful distinction between bully- ing and cyberbullying (e.g., Olweus & Limber, 2018), we coded whether the bullying occurred offline or online. We also coded trolling, which involves intentionally provoking others online. In this meta-ana- lytic review, we coded the form of aggression for exploratory purposes. Aggression can also serve different functions. Researchers have
distinguished between reactive and proactive aggression (Bush- man & Anderson, 2001). Reactive aggression (also called hostile, emotional, affective, and impulsive aggression) is “hot tempered” annoyance-based aggression that is an “end in itself.” Proactive aggression (also called instrumental and premeditated aggression) is “cold-blooded” incentive-based aggression that is a “means to some other end” (e.g., money, status, power, reputation, revenge, prestige). In this meta-analytic review, we also coded the function of aggression. Because individuals high in narcissism are hyper- sensitive to provocation, we expect narcissism to be positively relate to reactive aggression. But narcissism might also be posi- tively related to proactive aggression, especially when it comes to obtaining status (Grapsas et al., 2020). Some scholars have also suggested that the distinction between reactive and proactive aggression is not particularly useful because aggression can be both annoyance-based and incentive-based, and because the two types of aggression tend to be very highly correlated (see Bush- man & Anderson, 2001). Thus, narcissism should be related to both reactive and proactive aggression. We also examined the link between narcissism and violence,
which is defined as any aggressive behavior intended to cause extreme physical harm, such as injury or death (Bushman & Hues- mann, 2010). All violent behaviors are aggressive, but only behav- iors intended to cause extreme physical harm are violent. For example, hitting someone is violent, but calling someone an insult- ing name is not violent, although it is aggressive. We expected narcissism to be more strongly related to aggression than to vio- lence, because rare and extreme behaviors have a restricted range and are more difficult to predict.
Narcissism and Aggression
There is a large body of research examining the link between narcissism and aggression. Individuals with high levels of
narcissism have several characteristics that predispose them to behave in an aggressive manner. Some aspects of narcissism are directly related to aggression, such as being antagonistic and dis- agreeable (Krizan & Herlache, 2018; Vize et al., 2019), and lack- ing empathy for others (Czarna et al., 2015; Hepper et al., 2014; Jones, 1913).
How people view themselves can also influence how they treat others, including whether they treat them in an aggressive manner. People with high levels of narcissism view themselves as superior beings. Viewing oneself as superior implies viewing others as in- ferior (Brummelman et al., 2018; Grapsas et al., 2020). Of course, it is easier to aggress against others if one considers them to be in- ferior beings.
This meta-analytic review integrates this body of research and examines possible moderator variables. Theoretically, the most important moderator variable is provocation.
Provocation
Some theoretical models predict high levels of aggression among individuals high in narcissism in certain contexts and situa- tions. According to the threatened egotism model (Baumeister et al., 1996), individuals high in narcissism levels are especially prone to aggress against others who evaluate them negatively, such as by shaming, humiliating, embarrassing, or criticizing them. Although negative evaluations can be unpleasant for every- one, they are especially unpleasant and threatening for individuals high in narcissism due to their inflated egos and their “thin skins.” The model also predicts that individuals high in narcissism are likely to reject negative evaluations from others, which allows them to maintain their inflated self-views. Finally, the model pre- dicts that individuals high in narcissism will be more likely to retaliate against those who evaluate them negatively by aggressing against them.
According to the Status Pursuit in Narcissism (SPIN) model (Grapsas et al., 2020), individuals high in narcissism are also prone to aggress against others in their attempts to obtain status. For example, narcissistic youth, especially boys, are prone to bully others to obtain dominance or status in their peer group (Reijntjes et al., 2016). Most models of narcissism, including the threatened ego model, propose that the main motive of people high in narcis- sism is the desire to create and maintain an overly positive, grandi- ose self-image, which is an intrapersonal motive. In contrast, the SPIN model proposes that this desire to have a grandiose self- image serves a higher-order social motive—to obtain social status, which is an interpersonal motive. From an evolutionary perspec- tive, this makes good sense. A grandiose self-image helps people accrue higher status and social benefits by convincing others of their superior skills and abilities.
The recent literature seems to suggest that narcissistic aggres- sion stems from provocation more generally (e.g., Rasmussen, 2016), although some studies find that narcissistic aggression can also occur in the absence of provocation (e.g., Reidy et al., 2010). In this meta-analytic review, we code provocation as a key moder- ator variable. We predict the link between narcissism and aggres- sion to be stronger when participants are provoked than when they are not provoked. If narcissism is related to aggression in nonpro- voking contexts, it would have interesting theoretical implications. Perhaps seeing others as inferior beings is sufficient to ignite
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aggression in individuals high in narcissism, even in the absence of external provocation. We also code whether the provocation is related to status (e.g.,
respect, prominence, or reputation) or affiliation (e.g., belonging, liking, or closeness). The SPIN model (Grapsas et al., 2020) would predict higher levels of narcissistic aggression for status-related provocations than for affiliation-related provocations.
Exploratory Moderator Variables
In addition to theoretical moderators described above, this meta- analytic review also considered several additional characteristics that might moderate the relation between narcissism and aggres- sion, including source, participant, and design characteristics.
Source Characteristics
As one measure of publication bias, we coded whether each study was published in a peer reviewed journal or not. In addition, we used more formal methods for assessing the impact of publica- tion bias by conducting a comprehensive battery of sensitivity analyses. We also coded the year the data were collected. We explore
whether the relation between narcissism and aggression is stable over time.
Participant Characteristics
Previous research has reported that males have higher levels of narcissism than females (Grijalva et al., 2015). When it comes to gender differences in aggression, males exhibit higher levels of physical aggression than females do, whereas females exhibit higher levels of indirect aggression than males do (Björkqvist, 2018). This meta-analytic review explores whether there are gen- der differences in the relation between narcissism and aggression. Consistent with evolutionary theory, several scholars have sug-
gested that narcissism levels reach a developmental high in adoles- cence (e.g., Bleiberg, 1994), and decrease across the life span (Foster, Campbell, & Twenge, 2003, Trzesniewski & Donnellan, 2010), until they reach a developmental low in older age (Carter & Douglass, 2018; Robins et al., 2002). This meta-analytic review explores whether age moderates the relation between narcissism and aggression. Researchers in psychology and related fields have questioned
whether the results obtained from studies that use samples of stu- dents from universities and colleges generalize to other popula- tions (e.g., Ashraf & Merunka, 2017; Briones & Benham, 2017; Espinosa & Ortinau, 2016; Flere & Lavri�c, 2008; Hanel & Vione, 2016; James & Sonner, 2001; Landers & Behrend, 2015; Sears, 1986). Some studies find differences between student and nonstu- dent samples, whereas other studies find no differences. This meta-analytic review explores whether the relation between narcis- sism and aggression differs for students and nonstudents. Higher narcissism levels have been found in people from indi-
vidualistic countries than in people from collectivistic countries (Foster, Campbell, & Twenge, 2003; Foster, Shrira, & Campbell, 2003; Twenge & Campbell, 2009). This meta-analytic review explores whether the relation between narcissism and aggression differs for people from individualistic and collectivistic countries.
Design Characteristics
This meta-analytic review explores the relation between narcis- sism and aggression in experimental, cross-sectional, and longitu- dinal studies. For experimental studies, we also coded whether the experiment was conducted in a laboratory, online, or field setting. There has been some debate about whether online and offline experiments produce similar results (e.g., Horton et al., 2011; Reips, 2000). Finally, we explore whether similar results are obtained when aggression is assessed via self-report, other-report (e.g., parent, teacher, or peer), and behavioral observation.
Previous Meta-Analytic Reviews
Although other meta-analytic reviews have examined the link between narcissism and aggression (Bettencourt et al., 2006; Geel et al., 2017; Hyatt et al., 2019; Lambe et al., 2018; Moor & Ander- son, 2019; Muris et al., 2017; Rasmussen, 2016), this meta-ana- lytic review is far more comprehensive than past meta-analytic reviews. For example, it includes many more studies, it includes unpublished studies, it examines normal and pathological narcis- sism, it examines different dimensions of narcissism, it examines different forms and functions of aggression, it includes provoca- tion as a key moderator variable, and it includes several other ex- ploratory moderator variables. It controls for correlated effects. It also includes a comprehensive battery of sensitivity analyses to examine the effects of publication bias and outliers on the obtained results.
Method
Literature Search
Five computer databases were used to locate relevant studies published through November 15, 2020: Medline, PsycINFO, Edu- cational Resources Information Center (ERIC), PubMed, and Pro- Quest. We searched for unpublished studies in ProQuest to address potential publication bias (i.e., the file drawer problem; Rosenthal, 1979). The terms used for the literature search were (“dark core” OR “dark personality traits” OR “dark traits” OR “dark tetrad” OR “dark triad” OR ego* OR entitlement OR gran- dios* OR narcissis* OR NPD) AND (aggress* OR agonistic OR “antisocial behavior” OR “antisocial behaviour” OR “anti-social behavior” OR “anti-social behaviour” OR assault* OR attack* OR bullie* OR bully* OR conflict* OR coerc* OR cruel* OR der- ogate* OR dominant* OR “externalising behaviour”* OR “exter- nalizing behavior”* OR “externalising problems”* OR “externalizing problems”* OR fight* OR harass* OR hostil* OR “negative reciprocity” OR rape* OR reveng* OR retaliat* OR sadis* OR troll* OR venge* OR victim* OR violen*). The asterisk allows terms to have all possible endings (e.g., the term aggress* will retrieve studies that used the terms aggress, aggressed, aggressor, aggressive, and aggression).
Most of the aggression terms are the ones used in the journal Aggressive Behavior, which is the flagship journal of the Interna- tional Society for Research on Aggression. We also used search terms from previous meta-analytic reviews of narcissism and aggression. In addition, we added search terms based on a
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thesaurus search and our reading of the literature. The search terms were limited to be in the Title and/or Abstract. We also were going to include the terms “conduct problems,”
“oppositional behavior,” and “oppositional behaviour” as aggres- sion terms, but such measures often lump aggressive behavior in with other antisocial behaviors (e.g., stealing, lying, cheating). We excluded these terms because this meta-analytic review focuses specifically on aggression. To obtain studies that we might have been missed, two addi-
tional steps were taken. First, we searched the reference sections of previous meta-analytic reviews (Bettencourt et al., 2006; Geel et al., 2017; Hyatt et al., 2019; Lambe et al., 2018; Moor & Ander- son, 2019; Muris et al., 2017; Rasmussen, 2016). Second, we searched the reference sections of all retrieved studies.
Inclusion Criteria
Four inclusion criteria were used. First, the study had to include a measure of narcissism. Second, the study needed to examine nar- cissism at the individual level rather than at the group or collective level (e.g., de Zavala, 2011; de Zavala et al., 2019). Third, the study had to include a measure of aggression and/or violence. Fourth, participants had to be at least 7 years old. One cannot accurately measure narcissism in children under about age 7. Young children typically hold inflated views of themselves and their competencies. One reason is that they are not yet well able to compare their own competencies with those of others, or to incor- porate such self-other comparisons into their self-views (Ruble & Frey, 1991). Moreover, young children find it difficult to distin- guish their ideal self (the person they want to be) from their actual
self (the person they really are; Harter, 2012). From about age 7, however, children develop more realistic self-views, and it is from this age that individual differences in narcissism can be meaning- fully assessed (Thomaes & Brummelman, 2016).
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Flowchart
The literature search produced 11,862 research reports, but not all of them were relevant to this meta-analytic review. To deter- mine whether research reports were relevant, we read their titles and abstracts. As shown in the PRISMA flowchart in Figure 1, the final sample included 320 research reports (each marked with an asterisk in the References section), which included 437 independ- ent studies involving 123,043 participants.
Theoretical Moderator Variables
Normal Versus Pathological Narcissism
Pathological narcissism can be determined using the classifica- tion of NPD or the PNI (Pincus, 2013; Pincus et al. 2009; includ- ing the brief PNI; Schoenleber et al. 2015).
Narcissism Dimensions
We examined three dimensions of narcissism: (1) entitlement, (2) grandiose narcissism, and (3) vulnerable narcissism. We also examined pathological narcissism, which includes elevated levels of both grandi- osity and vulnerability. To code these different aspects of narcissism, we used classifications provided by other researchers based on several different narcissism scales (e.g., Crowe et al., in press; Krizan & Herl-
Figure 1 PRISMA Flowchart of Literature Search
Research reports identified through
PsycINFO, Medline, ERIC, PubMed,
ProQuest (n = 11,862)
Additional research reports identified through reference sections of other reviews (n = 129)
Research reports excluded after reading title/abstract or more
(n = 9,965)
Research reports excluded due to
duplication (n = 1,672)
Total number of research reports
identified (n = 11,991)
Research reports were excluded due to insufficient data
(n = 34)
Research reports included in the final
review (n = 320)
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ache, 2018; Weiss et al. 2019; Wright & Edershile, 2018; see Table SM1 in online supplementary materials). Because we were interested in dimensions of narcissism that are
often formed using different subscales, we asked 83 authors to send us correlations for different narcissism subscales and aggres- sion if they were not included in the original research report. Of these 83 authors, 43 (52%) responded to our requests and provided the missing subscale data, 28 (34%) did not respond to our initial or follow-up e-mail, seven (8%) said the data were inaccessible (e.g., due to coronavirus disease 2019 [COVID-19], data stored on an old computer), and five (6%) could not be contacted (e.g., were deceased, no forwarding e-mail). Thus, the analyses based on sub- scales should be interpreted with some caution.
Aggression and Violence
This meta-analytic review examined the relation between nar- cissism and both aggression and violence. In laboratory experi- ments, the most widely used behavioral measure of aggression is the competitive reaction time (RT) task (Warburton & Bushman, 2019), where participants deliver unpleasant noise blasts through headphones to an ostensible opponent each time they beat them on a RT task. Displaced aggression can also be measured using this task, but the target is an innocent person rather than the provoca- teur (e.g., Bushman & Baumeister, 1998; Twenge & Campbell, 2003). The most common self-report measure of aggression is the Aggression Questionnaire (AQ; Buss & Perry, 1992), which meas- ures both physical aggression (e.g., “If somebody hits me, I hit back”) and verbal aggression (e.g., “I can't help getting into argu- ments when people disagree with me”). We coded the form of aggression (i.e., indirect, direct, displaced, physical, verbal, trol- ling, bullying). For bullying, we coded whether it occurred offline or online (i.e., cyberbullying). We also coded the function of aggression (i.e., reactive, proac-
tive). One common self-report measure of reactive, and proactive aggression is the Reactive-Proactive Aggression Questionnaire (Raine et al., 2006), which contains 11 items to measure reactive aggression (e.g., “Gotten angry or mad or hit others when teased”) and 12 items to measure proactive aggression (e.g., “Had fights with others to show who was on top”). Violence is often measured using convictions for violent crimes
(e.g., Fisher & Hall, 2011; Westhead & Egan, 2015). One common self-report measure of intimate partner violence is the Conflict Tac- tics Scale (Straus, 1979; e.g., “Kicked, bit, or punched partner”).
Provocation
We coded whether participants were provoked or not. If participants were provoked, we coded whether the provocation was status-related (e.g., respect, prominence, or reputation), or affiliation- related (e.g., belonging, liking, or closeness). A common status-related provocation consists of giving participants bogus negative feedback about an essay they wrote (e.g., Bushman & Baumeister, 1998); or bogus negative results on an intelligence test (e.g., Smalley & Stake, 1996). A common affiliation-related provocation consists of telling participants that nobody has chosen them as a partner for an upcoming group task (e.g., Twenge & Campbell, 2003), or excluding them from a ball-toss game called cyberball (e.g., Chester & DeWall, 2016). It is important to note that provocation is confounded with the
function of aggression. Specifically, studies that involved provoca- tion measured reactive aggression.
Exploratory Moderator Variables
Source Characteristics
Publication Status. Publication status (i.e., peer reviewed or not peer reviewed) was analyzed as a one test of publication bias, although more formal procedures were also used (see Sensitivity Analyses portion of Results section).
Year. We coded the year the data were collected. If the authors did not report the year the data were collected, we coded the year the article was published.
Participant Characteristics
Gender. If studies reported separate results for males and females, we coded them separately. If studies did not report sepa- rate results for males and females, we contacted authors and asked for the separate results.
Age. We coded the mean age of participants. Some studies that used students as participants did not report their mean age. Thus, the mean age of the available student samples in this meta- analytic review was computed (M = 20.69) and imputed for miss- ing values.
Student Sample. We coded whether participants were stu- dents from a university or college or not.
Country. We coded whether participants were from an indi- vidualistic or collectivistic country.
Design Characteristics
Type of Design. We coded the type of design researchers used (i.e., experimental, cross-sectional, or longitudinal). Wave 1 of a longitudinal study was coded as a cross-sectional study. If a longitudinal study included more than two waves of data, waves after wave 1 were averaged.
Type of Setting. For experiments, we coded whether it was conducted online, in a laboratory setting, or in a naturalistic field setting.
Type of Report. We coded whether aggression was assessed via self-report, other-report (e.g., parent, teacher, peer, or signifi- cant other), or behavioral observation.
Intercoder Reliability
All studies were coded by two independent raters (the lead author and trained undergraduate research assistants), called “dou- ble coding” (Cooper, 2016). To assess intercoder reliability, the intraclass coefficient was used for continuous characteristics and the kappa coefficient was used for categorical characteristics (Orwin & Vevea, 2009). The median reliability coefficient was .69. The median percent agreement on the coded study characteris- tics was 81%. Any coding disagreements were resolved via discus- sion between the two authors.
Analysis Strategy
In this meta-analytic review, both narcissism and aggression were conceptualized as continuous variables. Thus, the correlation coefficient was used as the effect-size index. Because the distribu- tion of the correlation coefficient is not normally distributed unless the population correlation coefficient equals zero, Fisher’s z-
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transformation was applied to each correlation coefficient before pooling them. Each z-transformed value was weighted by the inverse of its variance (i.e., N-3). Thus, larger studies received more weight when effect-size estimates were combined. Data were analyzed using Comprehensive Meta-Analysis
(CMA) software (Version 3; Borenstein et al., 2011) and R (R Core Team, 2020). Random-effects models were used, which assume that effect sizes differ from population means by both sub- ject-level sampling error and study-level variability (Borenstein et al., 2011). Although random-effects models are more conservative than fixed-effects models, they require fewer statistical assump- tions and allow for generalizations to a broader set of studies than only the ones included in the meta-analytic review (Borenstein et al., 2011). Conventional meta-analytic methods rely on the assumption
that effect size point estimates are independent (Hedges et al., 2010). In this meta-analytic review, the independence assumption was often violated because many studies provided more than one correlation, resulting in clusters of correlations from these respec- tive studies. For example, we examined the relation between three factors of narcissism (i.e., entitlement, grandiose narcissism, vul- nerable narcissism) and aggression. Some studies measured more than one factor of narcissism using the same sample of partici- pants, which violates the independence assumption. In addition. some studies measured both aggression and violence, both func- tions of aggression (i.e., reactive and proactive aggression), or multiple forms of aggression (e.g., physical and verbal aggression) using the same sample of participants. Other examples include experiments used within-subjects designs, longitudinal studies that reported both cross-sectional and longitudinal correlations, and studies that used both self-report and other-report measures of aggression. There were 1,048 correlations from the 437 studies. Thus, we calculated robust variance estimates to adjust standard errors of dependent effect size point estimates and confidence intervals (CIs; Hedges et al., 2010; Tipton 2013, 2015) with the metafor v. 2.4-0 (Viechtbauer, 2010) and robumeta v. 2.0 (Fisher et al., 2017) packages in R (R Core Team, 2020). For distributions with fewer than 10 effect sizes, we only pro-
vide descriptive statistics. Most meta-analysts urge caution when interpreting results from distributions with fewer than 10 effect sizes (e.g., Kepes et al., 2012; Sterne et al., 2011). We also conducted comprehensive battery of sensitivity analy-
ses to determine whether the obtained results were robust to publi- cation bias and outliers. The sensitivity analyses are summarized after the main results.
Results
Study Characteristics
This meta-analytic review included 437 independent studies involving 123,043 participants. Of these 437 studies, 360 were published in peer-reviewed journals and 77 were unpublished. The studies were conducted between 1985 and 2020. The average age of participants ranged from 8.3 to 61.7 years. Of the 437 studies, 183 used student samples from colleges or universities, and 254 used nonstudent samples. About 88% of studies were conducted in individualistic countries.
Overall Results
The average correlation for the 437 studies was .25 with a 95% CI ranging from .24 to .27, which excludes the value zero. The 25th, 50th, and 75th percentiles were .14, .24, and .33, respec- tively. As can be seen in the violin plot (see Figure 2), the distribu- tion is symmetric (i.e., the median and mean are almost identical, the median cuts the box in half, the whiskers are about the same length, and the mild outliers are symmetrically distributed in the two tails of the distribution). The correlations varied widely, rang- ing from �.39 to .76, suggesting that the study results were hetero- geneous. Nearly all correlations (94%) were positive.
Although random effects models were used for theoretical rea- sons, there were also good empirical reasons for using them. The observed effects were heterogeneous, Q(436) = 3484.31, p , .0001. The I2 statistic indicated that 87% of the heterogeneity in effects was due to between-study differences. According to the Cochrane Collaboration (Higgins & Green, 2011), an I2 greater than 75% suggests considerable heterogeneity. The coded charac- teristics for the individual studies are included in Table SM2 in online supplemental materials.
The Link Between Narcissism and Aggression and Violence
The correlation between narcissism and violence, defined as aggression intended to cause extreme physical harm such as injury or death (Bushman & Anderson, 2001).was .23 [.18 to .27], k = 65. The correlation between narcissism and less extreme acts of aggression was .26 [.24, .27], k = 376. The two correlations did not significantly differ in size, Q(1)= 1.46, p = .23.
Normal Versus Pathological Narcissism
The average correlation between normal narcissism and aggres- sion was .25 [.23, .27], k = 386. The average correlation between pathological narcissism and aggression was .29 [.20, .37] for the 21 studies that used NPD and was .28 [.22, .33] for the 30 studies that used the PNI. The correlations based on the NPD and PNI were combined (r = .28, [.23, .33], k = 51) because they did not differ, Q(1)= 0.053, p = . 82. Likewise, normal and pathological narcissism (i.e., NPD studies plus PNI studies) did not differ in their relation to aggression, Q(1)= 1.63, p = .20.
Narcissism Dimensions
We examined the relation between three dimensions of narcis- sism and aggression. The correlation between entitlement, which is the core of narcissism, and aggression was .26 [.23, .29], k = 100. The correlation between grandiose narcissism and aggression was .24 [.22, .26], k = 358. The correlation between vulnerable narcissism and aggression was .26 [.22, .30], k = 89. The magni- tude of the correlations did not significantly differ, Q(2) = 1.60, p = .45.
Forms of Aggression
Narcissism was related to indirect aggression (r = .24, [.18, .29], k = 59), direct aggression (r = .22, [.20, .25], k = 205), and
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displaced aggression (r = .18, [.05, .31], k = 12), and the correla- tions did not significantly differ in size, Q(2) = 2.52, p = .28. Narcissism was related to both physical aggression (r = .24,
[.21, .26], k = 175) and verbal aggression (r = .21, [.18, .25], k = 69), and the correlations did not significantly differ in size, Q(1) = 1.03, p = .31. Narcissism was more strongly related to offline bullying (r =
.29, [.21, .37], k = 21) than to online bullying (i.e., cyberbullying; r = .20, [.17, .24], k = 18), Q(1) = 4.37, p = .04. However, both CIs excluded zero. Thus, there was a significant positive relation between narcissism and bullying both offline and online. Only nine studies measured the link between narcissism and
trolling. Descriptively, these nine studies found a significant posi- tive correlation between narcissism and trolling, r = .19 [.14, .24].
Functions of Aggression
The average correlation between narcissism and proactive aggression (r = .34, [.30, .38], k = 59) was stronger than the aver- age correlation between narcissism and reactive aggression (r = .26, [.24, .29]), k = 179, Q(1) = 10.99, p = .001. However, both CIs excluded zero. Thus, there was a significant positive relation between narcissism and both cold-blooded and hot-headed aggression.
To more directly examine this moderator, we also analyzed the 32 studies that measured both reactive and proactive aggression using the same sample of participants via the Reactive-Proactive Aggression Questionnaire (Raine et al., 2006). This analysis found that the relationship between narcissism and proactive aggression (r = .30, [.26, .34]) did not differ from the relationship between
Figure 2 Violin Plot
Note. The density of the distribution at a given correlation is denoted by its width. The mean correlation is denoted by a solid line, and the 95% confidence interval (CI) bounds are denoted by dashed lines. The center of the violin plot contains a boxplot. Mild outliers are denoted by solid black circles. There were no extreme outliers. See the online article for the color version of this figure.
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narcissism and reactive aggression (r = .29, [.24, .34]), Q(1) = 0.13, p = .72.
Provocation
A total of 38 studies included both a provocation condition and a no provocation condition. As expected, narcissism was more strongly related to aggression under provocation condi- tions (r = .29, [.23, .36]) than under no provocation conditions (r = .12, [.05, .18]), Q(1) = 9.84, p = .002. However, both CIs excluded the value zero. Thus, there was a significant positive relation between narcissism and aggression even in the ab- sence of provocation. An additional 20 studies included only a provocation condition.
Of the 58 studies that included some form of provocation, 55 could be coded status-related (e.g., respect, prominence, or reputa- tion) or affiliation-related (e.g., belonging, liking, or closeness). Contrary to the SPIN model (Grapsas et al., 2020), narcissism was more strongly related to aggression when the provocation was affiliation-related (r = .39, [.28, .48], k = 20) than when the provo- cation was status-related (r = .22, [.17, .27], k = 35), Q(1) = 7.56, p = .006. However, both CIs excluded zero. Thus, there was a sig- nificant positive relation between narcissism and aggression regardless of whether the provocation was affiliation-related or status-related.
Source Characteristics
Year
The year the data were collected did not significantly influ- ence the magnitude of the relation between narcissism and aggression, b = �.0005, [�.0033, .0022], k = 437. Likewise, the year the data were collected from student samples did not significantly influence the magnitude of the relation between narcissism and aggression, b = �.0003, [�.0034, .0028], k = 183. Thus, the association between narcissism and aggression was stable over the years examined (1985 to 2020) for all sam- ples and for student samples.
Publication Status
The average correlation did not differ for published (r = .26, [.24, .27], k = 360) and unpublished (r = .24, [.20, .27], k = 77) studies, Q(1) = 0.95, p = .33. Thus, publication bias did not contaminate the meta-analytic results using this measure (for other measures see Sensitivity Analyses portion of Results section).
Participants Characteristics
Gender
The relation between narcissism and aggression did not signifi- cantly differ for males (r = .24, [.20, .27], k = 108) and females (r = .21, [.16, .26], k = 51), Q(1) = 0.58, p = .45.
Age
Participant age did not significantly influence the magnitude of the relationship between narcissism and aggression, b �.0004 [.0010, �.0024], k = 427. Thus, the link between narcissism and aggression was stable across the ages studied (mean ages ranged from 8.3 to 61.7 years). The remaining 10 studies did not report mean age of participants.
University Students
The link between narcissism and aggression was slightly but significantly larger for nonstudent samples (r = .27, [.25, .29], k = 254) than for student samples (r = .23, [.21, .25], k = 183), Q(1) = 5.15, p = .02. However, both CIs excluded zero. Thus, there was a significant positive relation between narcissism and aggression for both students and nonstudents.
Country
The average correlation between narcissism and aggression did not significantly differ for participants from individualistic coun- tries (r = .25, [.23, .27], k = 384) and those from collectivistic countries (r = .26, [.21, .31], k = 50), Q(1) = 0.14, p = .71.
Design Characteristics
Type of Design
Narcissism was positively related to aggression in cross-sec- tional studies (r = .26, [.24, .28], k = 358), experimental studies (r = .22, [.18, .26], k = 76), and longitudinal studies (r = .19, [.11, .27], k = 13). The between-groups test was significant, Q(2) = 7.21, p = .03. However, all three CIs excluded zero. Thus, there was a significant positive relation between narcissism and aggres- sion regardless of the type of design researchers used.
Type of Setting
For experimental studies, we coded whether the setting was online, in a laboratory, or in the field. However, there were no field experiments, and only seven online experiments, which had an av- erage correlation of .29 [.23, .34]. The 69 lab experiments had an average correlation of .20 [.16, .24].
Type of Report
We coded whether aggression was assessed via self-report, other- report (e.g., parent, teacher, peer, or significant other), or behavioral ob- servation. The correlation was largest for other-report measures (r = .30, [.22, .35], k = 48), followed by self-report measures (r = .26, [.24, .27], k = 312), followed by behavioral measures (r = .21, [.17, .25], k = 93). The between-groups test was significant, Q(2) = 6.28, p = .04. However, all three CIs excluded the value zero. Thus, there was a significant posi- tive relation between narcissism and aggression regardless of the type of report used to measure aggression.
Sensitivity Analyses
We conducted sensitivity analyses to assess whether publication bias, outliers, or both affected our results. Both publication bias and outliers can adversely affect meta-analytic results and associ- ated conclusions (Kepes et al., 2013). In fact, publication bias has
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been referred to as the potentially greatest threat to the validity of meta-analytic results (Rothstein et al., 2005). We performed a comprehensive battery of sensitivity analyses to determine the degree to which our obtained results were affected by publication bias, outliers, or both (e.g., Kepes et al., 2017). All sensitivity analyses were conducted using Comprehensive
Meta-Analysis (Borenstein et al., 2011) and R syntax (Kepes & McDaniel, 2015; Viechtbauer, 2017). First, we calculated the na- ïve observed meta-analysis mean estimate (�roÞ for each distribu- tion as well as the associated statistics (e.g., 95% CI, 90% prediction interval [PI], weighted sum of squared deviations from the mean, ratio of true heterogeneity to total variation). By “na- ïve,” we mean the meta-analytic results without any “adjustment” for potential biases (Copas & Shi, 2000). Next, we conducted a one sample removed analyses to examine the influence of each individual effect size on the obtained meta-analytic results. Then, we assessed the potential for publication bias in each distribution. We used several methods, including trim-and-fill (fixed effects and random effect), cumulative meta-analysis (Kepes et al., 2017), selection models (Vevea & Woods, 2005), PET-PEESE, and influ- ence diagnostics to identify potential outliers. All identified outlier(s) were excluded, and we reran all publication bias meth- ods. Thus, when outliers were identified we performed all publica- tion bias methods twice: (1) once on the original distribution, and (2) once on the distribution without identified outlier(s). Then, the results were averaged before making any conclusions. Specifi- cally, when determining whether a particular naïve mean estimate was robust to the presence of publication bias and/or outliers, we calculated the average and the median estimates of all five publica- tion bias methods with and without outliers. We used the median as well as the average because the median minimizes the potential undue influence of an estimate from any individual method on the overall results and conclusions. To estimate the severity of poten- tial publication bias, we used guidelines suggested by other schol- ars (Kepes et al., 2012; Kepes & McDaniel, 2015). Specifically, we calculated the difference between the naïve estimate and the average estimates of all five publication bias methods with and without outliers, as well as the corresponding percent change dif- ference. Any change of more than 20% was considered “moder- ate” and any change of more than 40% was considered “severe.” In addition to the cumulative meta-analysis by precision (Kepes
et al., 2012), we reported the cumulative meta-analytic mean of the most precise effect sizes. For the selection models, a prior models with p value cut-points were used to model moderate and severe instances of publication bias (Vevea & Woods, 2005). Pub- lication bias assessment methods were not used on distributions containing 10 or fewer effect sizes because all methods become less stable with small samples (Kepes et al., 2012). The results from the sensitivity analyses are displayed in Table
1. Columns 1–3 display the distribution analyzed, the number of samples (k), and the number of participants (N). Columns 4–10 report the naïve meta-analytic results, including the random effects (RE) meta-analytic mean (�roÞ, the 95% CI, the 90% PI, Cochran’s Q statistics, I2, tau (s), and the one-sample removed statistics (me- dian mean, minimum, or maximum). Column 11–18 display the results from the trim-and-fill analyses; for the fixed effects (FE) as well as the RE model. For each model, the table includes the side of the funnel plot on which the imputed samples are located (FPS), the number of imputed samples (ik), the trim-and-fill
adjusted mean effect size (t&fFE �ro, t&fRE�roÞ, and the respective 95% CI. Column 19 contains the cumulative mean for the five most precise samples (pr5�roÞ. Columns 20 and 21 contain the results from the moderate (smm�roÞ and severe (sms�roÞ selection models. Column 22 contains the result of the PET-PEESE (pp�ro) analysis. Figures SM1 to SM36 in online supplemental materials contain forest plots that display the cumulative meta-analyses and funnel plots that display the magnitude of the effect size by preci- sion, with trim-and-fill imputations (for interpretation guidelines, see Kepes et al., 2012). CIs and Q-tests for correlated effects are based on robust variance estimates.
Neither publication bias nor outliers appear to influence the overall effect size. It could be overestimated by an average of .02 (7%). As can be seen in the violin plot (see Figure 2), there were no extreme outliers in the data set. The mild outliers were evenly distributed in the positive and negative distribution tails. Removing these 12 mild out- liers did not change the naïve mean correlation or the CI limits.
Many other distributions were not affected by publication bias or outliers. Most of the aggression distributions were unaffected by publi- cation bias or outliers, including the distributions for aggression, nearly all forms of aggression (i.e., indirect aggression, displaced aggression, physical aggression, verbal aggression, bullying, cyberbullying), both functions of aggression (i.e., reactive aggression, proactive aggression), and provoked aggression regardless of whether the provocation was affiliation-related or status-related. None of the narcissism distributions were affected by publication bias or outliers (i.e., normal narcissism, pathological narcissism, entitlement, grandiose narcissism, vulnerable narcissism). The distributions for both published and unpublished stud- ies were unaffected by publication bias or outliers. Many distributions for participant characteristics were unaffected by publication bias, including the distributions for males, students, nonstudents, and partici- pants from both individualistic and collectivistic countries. The distri- butions for all three types of research designs (i.e., experimental, cross- sectional, longitudinal) were unaffected by publication bias or outliers. Finally, the distribution for self-report measures of aggression was unaffected by publication bias or outliers.
However, some distributions were affected by publication bias and/or outliers. After deletion of identified outliers and removal of publication bias, the naïve mean correlation for violence (r = .23) might be overestimated by .04 to .16 (20–70%)
1
and the naïve mean correlation for unprovoked aggression (r = .12) might be overestimated by .05 to .07 (50–62%). Other distributions were affected mainly by publication bias. After removal of publication bias, the naïve mean correlation for direct aggression (r = .22) might have been underestimated by .02 (8%) or overestimated by .08 (38%), the naïve mean correlation for females (r = .21) might
1 For example, the mean naïve correlation for violence was r = .23 with
outliers and r = .21 without outliers (see Table 1). The text states these estimates “might be overestimated by .04 to .16 (20– 70%).” We calculated these values as follows. For these calculations we use three digits to avoid rounding error, although we only report 2 digits in the text. First, we calculated the average estimates of all five publication bias methods with outliers [(.16 þ .23 þ .19 -.42 þ .18)/5 = .068] and without outliers [(.15 þ .21 þ .18 þ .12 þ .18)/5 = .168]. Next, we subtracted these average estimates from the naïve mean with outliers (.23 - .068 = .162) and without outliers (.21 - .168 = .042) to obtain the average differences. To obtain the percentages, we divided the average differences by the mean naïve correlation with outliers (.162/.23 = .70 = 70%) and without outliers (.042/ .21 = .20 = 20%).
486 KJÆRVIK AND BUSHMAN
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E nt it le m en t (w
/o )
98 23 ,9 43
.2 5
[. 22 ,. 27 ]
.0 6, .4 1
39 1. 49
75 .2 2
.1 1
.2 5
.2 4, .2 5
.2 5
[. 22 ,. 27 ]
.2 5
[. 22 ,. 27 ]
.2 2
.2 3
.2 2
.2 7
G ra nd io se
35 8
10 3, 65 1
.2 4
[. 22 ,. 26 ]
.0 0, .4 6
3, 45 5. 26
88 .3 9
.1 5
.2 4
.2 4, .2 5
.2 4
[. 23 ,. 26 ]
R 63
.2 9
[. 27 ,. 30 ]
.2 2
.2 2
.1 8
.2 7
G ra nd io se
(w /o )
34 8
10 0, 80 6
.2 4
[. 22 ,. 25 ]
.0 3, .4 2
1, 94 9. 72
82 .1 8
.1 3
.2 4
.2 3, .2 4
L 2
.2 3
[. 22 ,. 24 ]
.2 4
[. 22 ,. 25 ]
.2 2
.2 2
.2 0
.2 5
V ul ne ra bl e
89 22 ,8 00
.2 6
[. 22 ,. 30 ]
�. 01 ,. 50
88 6. 98
87 .7 1
.1 5
.2 6
.2 6, .2 7
R 23
.3 3
[. 29 ,. 37 ]
R 22
.3 3
[. 29 ,. 36 ]
.2 4
.2 4
.2 1
.3 7
V ul ne ra bl e (w
/o )
88 22 ,5 39
.2 6
[. 22 ,. 29 ]
.0 0, .4 9
65 5. 28
86 .7 2
.1 6
.2 6
.2 5, .2 6
R 15
.3 0
[. 27 ,. 33 ]
R 19
.3 1
[. 28 ,. 35 ]
.2 4
.2 4
.2 1
.3 5
F or m
of ag gr es si on
D ir ec t
20 5
41 ,0 05
.2 2
[. 20 ,. 25 ]
�. 04 ,. 46
1, 48 1. 31
84 .8 6
.1 5
.2 2
.2 2, .2 3
R 53
.3 0
[. 27 ,. 32 ]
R 45
.2 8
[. 26 ,. 31 ]
.3 0
.1 9
�. 39
.3 0
D ir ec t (w
/o )
20 1
40 ,2 13
.2 2
[. 20 ,. 24 ]
�. 01 ,. 42
94 9. 26
78 .9 3
.1 4
.2 2
.2 2, .2 2
R 52
.2 9
[. 26 ,. 31 ]
R 39
.2 7
[. 25 ,. 29 ]
.3 0
.1 9
.1 4
.2 9
In di re ct
59 14 ,0 92
.2 4
[. 18 ,. 29 ]
�. 01 ,. 45
45 4. 61
86 .9 3
.1 5
.2 4
.2 2, .2 4
.2 4
[. 19 ,. 28 ]
.2 4
[. 19 ,. 28 ]
.2 4
.2 1
.1 7
.3 1
In di re ct (w
/o )
58 13 ,6 62
.2 2
[. 19 ,. 26 ]
.0 2, .4 1
26 1. 98
78 .2 4
.1 2
.2 3
.2 2, .2 3
L 1
.2 2
[. 18 ,. 26 ]
.2 2
[. 19 ,. 26 ]
.2 4
.2 0
.1 7
.2 5
D is pl ac ed
12 2, 32 1
.1 8
[. 05 ,. 31 ]
.0 3, .3 1
25 .8 1
59 .8 9
.0 1
.1 6
.1 9, .1 7
L 1
.1 6
[. 09 ,. 23 ]
L 2
.1 5
[. 08 ,. 22 ]
.1 8
.1 6
.1 5
.1 8
P hy si ca l
17 5
36 ,8 59
.2 4
[. 21 ,. 26 ]
�. 03 ,. 47
1, 36 2. 27
85 .6 7
.1 5
.2 4
.2 3, .2 4
R 27
.2 8
[. 25 ,. 30 ]
R 32
.2 9
[. 26 ,. 31 ]
.2 7
.2 1
�. 40
.3 0
P hy si ca l (w
/o )
16 9
34 ,7 83
.2 2
[. 19 ,. 24 ]
.0 1, .4 0
69 0. 47
75 .6 7
.1 2
.2 2
.2 1, .2 2
R 2
.2 2
[. 19 ,. 24 ]
.2 2
[. 19 ,. 24 ]
.1 9
.1 9
.1 5
.2 5
V er ba l
69 28 ,9 74
.2 1
[. 18 ,. 25 ]
.0 1, .4 0
77 4. 03
86 .3 2
.1 2
.2 0
.2 2, .2 1
L 24
.1 3
[. 09 ,. 17 ]
R 21
.2 7
[. 23 ,. 30 ]
.2 7
.2 0
.1 7
.2 3
V er ba l (w
/o )
67 22 ,1 41
.2 1
[. 18 ,. 23 ]
.0 6, .3 5
23 9. 29
72 .4 2
.0 9
.2 1
.2 0, .2 1
R 23
.2 7
[. 24 ,. 29 ]
R 8
.2 3
[. 20 ,. 25 ]
.3 2
.2 0
.1 9
.2 7
O ff li ne
bu ll yi ng
21 11 ,8 16
.2 9
[. 21 ,. 37 ]
.0 4, .5 1
31 0. 96
94 .9 2
.1 7
.3 0
.2 7, .3 1
L 2
.2 6
[. 19 ,. 33 ]
.2 9
[. 23 ,. 35 ]
.2 9
.2 8
.2 6
.3 0
O nl in e bu ll yi ng
18 13 ,8 81
.2 0
[. 17 ,. 24 ]
.0 4, .3 6
12 3. 39
76 .3 8
.0 7
.2 0
.2 0, .2 1
L 9
.1 1
[. 06 ,. 16 ]
L 3
.1 8
[. 14 ,. 23 ]
.1 8
.2 0
.1 9
.0 4
O nl in e bu lly in g (w /
o) 17
7, 15 7
.2 1
[. 18 ,. 25 ]
.1 2, .3 0
35 .4 9
54 .9 2
.0 5
.2 1
.2 1, .2 2
L 3
.2 0
[. 16 ,. 23 ]
.2 1
[. 18 ,. 25 ]
.2 2
.2 1
.2 1
.2 2
F un ct io n of
ag gr es si on
R ea ct iv e
17 9
37 ,0 18
.2 6
[. 24 ,. 29 ]
.0 1, .4 8
1, 35 2. 07
83 .1 6
.1 4
.2 6
.2 6, .2 7
R 25
.3 0
[. 27 ,. 32 ]
R 35
.3 1
[. 28 ,. 33 ]
.2 4
.2 4
.2 1
.3 4
R ea ct iv e (w
/o )
17 6
36 ,3 71
.2 5
[. 23 ,. 28 ]
.0 3, .4 5
86 5. 74
79 .7 9
.1 4
.2 5
.2 5, .2 6
R 19
.2 8
[. 26 ,. 30 ]
R 28
.2 9
[. 27 ,. 31 ]
.2 4
.2 4
.2 1
.3 1
P ro ac ti ve
59 20 ,2 51
.3 4
[. 30 ,. 38 ]
.1 1, .5 4
71 2. 45
90 .7 3
.1 5
.3 4
.3 3, .3 4
.3 4
[. 30 ,. 38 ]
.3 4
[. 30 ,. 38 ]
.3 4
.3 3
.3 2
.4 2
(t a b le co n ti n u es )
NARCISSISM AND AGGRESSION: A META-ANALYTIC REVIEW 487
T hi s do cu m en t is co py ri gh te d by
th e A m er ic an
P sy ch ol og ic al A ss oc ia ti on
or on e of
it s al li ed
pu bl is he rs .
T hi s ar ti cl e is in te nd ed
so le ly
fo r th e pe rs on al us e of
th e in di vi du al us er
an d is no t to
be di ss em
in at ed
br oa dl y.
T ab le
1 (c o n ti n u ed )
M et a- an al ys is
P ub li ca ti on
bi as
an al ys es
F E tr im
an d fi ll
R E tr im
an d fi ll
C M A
S el ec ti on
m od el s
P E T -
P E E S E
D is tr ib ut io n
k N
� r o
95 %
C I
90 %
P I
Q I2
s os r � r o
F P S
ik t&
f F E
� r o
t& f F
E 95 %
C I
F R S
ik t&
f R E
� r o
t& f R
E 95 %
C I
p r 5 � r o
sm m
� r o
sm s
� r o
pp � r o
P ro ac ti ve
(w /o )
57 19 ,6 53
.3 2
[. 29 ,. 35 ]
.1 3, .4 9
34 0. 95
83 .5 8
.1 2
.3 2
.3 2, .3 3
R 9
.3 5
[. 32 ,. 38 ]
.3 2
[. 29 ,. 35 ]
.3 4
.3 2
.3 1
.3 7
R P Q R ea ct iv e
32 14 ,2 80
.2 9
[. 23 ,. 34 ]
.0 5, .4 9
31 6. 79
90 .2 1
.1 5
.2 9
.2 8, .2 9
L 15
.1 8
[. 12 ,. 24 ]
L 7
.2 4
[. 19 ,. 30 ]
.2 4
.2 8
.2 8
.2 8
R P Q P ro ac ti ve
32 14 ,2 80
.3 0
[. 26 ,. 34 ]
.1 1, .4 7
21 3. 09
85 .4 5
.1 2
.3 0
.2 9, .3 0
R 10
.3 5
[. 31 ,. 39 ]
R 9
.3 4
[. 30 ,. 38 ]
.3 4]
.3 0
.2 9
.3 7
R P Q P ro ac ti ve
(w /
o) 30
12 ,8 15
.2 8
[. 25 ,. 31 ]
.1 6, .3 8
86 .4 7
66 .4 6
.0 7
.2 8
.2 7, .2 8
R 9
.3 2
[. 29 ,. 32 ]
R 1
.2 8
[. 25 ,. 31 ]
.2 7
.2 8
.2 7
.3 1
P ro vo ca ti on
P ro vo ke d
38 3, 93 0
.2 9
[. 23 ,. 36 ]
�. 04 ,. 57
31 9. 75
81 .8 4
.1 8
.2 9
.2 6, .3 0
R 7
.2 9
[. 22 ,. 37 ]
.2 9
[. 22 ,. 36 ]
.3 8
.2 6
.2 0
.5 0
P ro vo ke d (w
/o )
37 3, 77 0
.2 6
[. 21 ,. 32 ]
.0 4, .4 6
10 1. 28
64 .4 6
.1 4
.2 6
.2 5, .2 7
.2 6
[. 21 ,. 31 ]
.2 6
[. 21 ,. 32 ]
.3 8
.2 4
.2 1
.3 3
U np ro vo ke d
38 3, 97 1
.1 2
[. 05 ,. 18 ]
�. 26 ,. 47
54 3. 43
84 .1 2
.1 9
.1 0
.1 0, .1 3
R 15
.2 3
[. 16 ,. 30 ]
R 14
.2 2
[. 15 ,. 29 ]
.1 8
.0 5
�. 45
.4 7
U np ro vo ke d (w
/o )
37 3, 81 1
.1 0
[. 05 ,. 15 ]
�. 09 ,. 29
82 .6 3
56 .4 3
.1 1
.1 0
.0 9, .1 1
R 11
.1 7
[. 11 ,. 22 ]
R 10
.1 6
[. 11 ,. 22 ]
.1 8
.0 6
�. 32
.2 1
S ta tu s
35 4, 00 1
.2 2
[. 17 ,. 27 ]
.0 2, .4 1
89 .7 6
62 .1 2
.1 2
.2 2
.2 1, .2 3
R 1
.2 3
[. 18 ,. 28 ]
.2 2
[. 17 ,. 27 ]
.3 0
.2 0
.1 7
.3 3
A ff il ia ti on
20 2, 90 5
.3 9
[. 28 ,. 48 ]
.0 2, .6 6
11 4. 04
83 .3 4
.2 3
.3 9
.3 3, .4 0
L 4
.2 9
[. 16 ,. 42 ]
.3 9
[. 16 ,. 42 ]
.2 8
.3 6
.3 3
.5 3
A ff il ia ti on
(w /o )
19 1, 93 5
.3 3
[. 26 ,. 39 ]
.1 5, .4 8
36 .4 6
50 .6 4
.1 0
.3 3
.3 0, .3 4
L 4
.2 8
[. 20 ,. 36 ]
L 4
.2 8
[. 20 ,. 36 ]
.2 8
.3 1
.3 0
.3 1
P ub li ca ti on
st at us
P ub li sh ed
36 0
10 9, 54 1
.2 6
[. 24 ,. 27 ]
.0 0, .4 8
3, 15 3. 88
88 .6 2
.1 6
.2 6
.2 5, .2 6
.2 6
[. 24 ,. 27 ]
R 71
.3 1
[. 29 ,. 32 ]
.2 2
.2 3
.2 0
.3 1
P ub li sh ed
(w /o )
35 0
10 5, 54 8
.2 4
[. 23 ,. 26 ]
.0 3, .4 4
2, 23 5. 00
84 .3 8
.1 4
.2 4
.2 4, .2 5
.2 4
[. 23 ,. 26 ]
R 50
.2 8
[. 26 ,. 30 ]
.2 2
.2 3
.2 1
.2 7
U np ub li sh ed
77 13 ,5 02
.2 4
[. 20 ,. 27 ]
.0 1, .4 4
32 7. 44
76 .7 9
.1 4
.2 4
.2 3, .2 4
R 17
.2 9
[. 25 ,. 32 ]
R 17
.2 9
[. 25 ,. 32 ]
.2 1
.2 1
.1 7
.3 0
U np ub li sh ed
(w /o )
75 13 ,2 32
.2 2
[. 19 ,. 26 ]
.0 2, .4 1
26 5. 62
72 .1 4
.1 2
.2 2
.2 2, .2 3
R 18
.2 7
[. 24 ,. 31 ]
R 14
.2 6
[. 23 ,. 30 ]
.2 1
.2 1
.1 8
.2 8
G en de r
M al e
10 8
18 ,8 25
.2 4
[. 20 ,. 27 ]
�. 07 ,. 50
74 6. 84
85 .6 7
.1 9
.2 4
.2 3, .2 4
R 12
.2 7
[. 23 ,. 30 ]
R 19
.2 9
[. 25 ,. 32 ]
.2 5
.2 0
�. 40
.3 2
M al e (w
/o )
10 6
18 ,2 12
.2 2
[. 19 ,. 26 ]
�. 04 ,. 46
57 8. 49
81 .8 5
.1 6
.2 2
.2 2, .2 3
R 3
.2 3
[. 20 ,. 27 ]
R 12
.2 6
[. 22 ,. 29 ]
.2 5
.2 0
.1 3
.2 8
F em
al e
51 10 ,6 79
.2 1
[. 16 ,. 26 ]
�. 05 ,. 45
31 1. 69
83 .9 6
.1 6
.2 1
.2 0, .2 1
.2 1
[. 20 ,. 21 ]
R 10
.2 6
[. 21 ,. 30 ]
.1 2
.1 8
�. 39
.2 5
F em
al e (w
/o )
50 10 ,4 18
.2 0
[. 16 ,. 24 ]
�. 01 ,. 39
21 2. 23
76 .9 1
.1 3
.2 0
.1 9, .2 0
.2 0
[. 16 ,. 24 ]
.2 0
[. 16 ,. 24 ]
.1 2
.1 7
�. 36
.2 0
U ni ve rs it y st ud en ts
S tu de nt s
18 3
42 ,1 70
.2 3
[. 21 ,. 25 ]
.0 4, .4 0
73 1. 81
75 .1 3
.1 2
.2 3
.2 3, .2 3
R 13
.2 5
[. 23 ,. 27 ]
R 26
.2 6
[. 24 ,. 27 ]
.1 6
.2 2
.1 9
.2 7
S tu de nt s (w
/o )
17 9
40 ,6 19
.2 3
[. 21 ,. 24 ]
.0 8, .3 6
50 1. 80
64 .5 3
.0 9
.2 3
.2 2, .2 3
R 7
.2 3
[. 22 ,. 25 ]
R 11
.2 4
[. 22 ,. 26 ]
.1 6
.2 1
.2 0
.2 5
N on st ud en ts
25 4
80 ,8 73
.2 7
[. 25 ,. 29 ]
�. 02 ,. 51
2, 73 0. 36
90 .7 3
.1 8
.2 7
.2 6, .2 7
.2 7
[. 25 ,. 29 ]
R 50
.3 2
[. 30 ,. 34 ]
.3 2
.2 4
.2 0
.3 2
N on st ud en ts (w
/o )
25 0
80 ,0 30
.2 6
[. 24 ,. 28 ]
.0 0, .5 0
2, 40 4. 86
89 .6 5
.1 7
.2 6
.2 6, .2 6
.2 6
[. 24 ,. 28 ]
R 46
.3 1
[. 29 ,. 33 ]
.3 2
.2 4
.2 1
.3 1
C ou nt ry
In di vi du al is ti c
38 4
95 ,2 71
.2 5
[. 23 ,. 27 ]
.0 0, .4 7
2, 64 3. 17
85 .5 1
.1 6
.2 5
.2 5, .2 5
R 81
.3 0
[. 29 ,. 32 ]
R 80
.3 0
[. 29 ,. 32 ]
.3 5
.2 3
.1 9
.3 2
In di vi du al is ti c (w
/o )
37 1
90 ,5 11
.2 4
[. 22 ,. 25 ]
.0 4, .4 2
1, 68 4. 13
78 .0 3
.1 2
.2 4
.2 4, .2 4
R 44
.2 7
[. 25 ,. 28 ]
R 50
.2 7
[. 26 ,. 28 ]
.3 0
.2 2
.2 0
.2 8
C ol le ct iv is ti c
50 27 ,4 66
.2 6
[. 21 ,. 31 ]
�. 02 ,. 50
79 6. 10
93 .8 4
.1 7
.2 6
.2 5, .2 7
L 21
.1 2
[. 06 ,. 18 ]
.2 6
[. 21 ,. 31 ]
.2 9
.2 4
.2 1
.2 5
C ol le ct iv is ti c (w
/o )
48 26 ,8 53
.2 4
[. 20 ,. 28 ]
�. 01 ,. 46
61 5. 19
92 .3 6
.1 5
.2 4
.2 3, .2 5
L 20
.1 2
[. 07 ,. 18 ]
.2 4
[. 20 ,. 28 ]
.2 9
.2 3
.2 1
.2 3
T yp e of
de si gn
C ro ss -s ec ti on al
35 8
11 4, 65 6
.2 6
[. 24 ,. 28 ]
.0 0, .4 9
4, 17 7. 49
90 .1 2
.1 5
.2 6
.2 6, .2 6
.2 6
[. 24 ,. 28 ]
.2 6
[. 24 ,. 28 ]
.2 2
.2 4
.2 0
.3 1
C ro ss -s ec tio na l (w /
o) 34 7
11 1, 83 7
.2 5
[. 23 ,. 26 ]
.0 3, .4 5
2, 39 9. 93
85 .5 8
.1 4
.2 5
.2 5, .2 5
.2 5
[. 23 ,. 26 ]
.2 5
[. 23 ,. 26 ]
.2 2
.2 3
.2 1
.2 7
E xp er im
en ta l
76 7, 15 4
.2 2
[. 18 ,. 26 ]
.0 2, .3 9
18 0. 82
58 .3 0
.1 1
.2 2
.2 2, .2 2
R 18
.2 8
[. 24 ,. 31 ]
R 13
.2 6
[. 22 ,. 39 ]
.2 6
.1 9
�. 37
.3 2
E xp er im
en ta l (w
/o )
75 7, 05 4
.2 2
[. 19 ,. 26 ]
.4 2, .3 9
15 3. 79
51 .8 8
.1 1
.2 2
.2 2, .2 3
R 18
.2 8
[. 24 ,. 31 ]
R 12
.2 6
[. 22 ,. 29 ]
.2 6
.2 0
.1 5
.3 2
L on gi tu di na l
13 5, 87 0
.1 9
[. 11 ,. 27 ]
�. 05 ,. 40
11 6. 45
88 .9 4
.1 2
.1 9
.1 6, .2 0
R 6
.2 8
[. 20 ,. 35 ]
R 3
.2 1
[. 14 ,. 28 ]
.2 7
.1 7
.1 4
.3 2
D es ig n ty pe
of se tt in g
L ab
69 5, 56 3
.2 0
[. 16 ,. 24 ]
�. 01 ,. 40
15 4. 87
56 .0 9
.1 3
.2 0
.2 0, .2 1
R 13
.2 5
[. 21 ,. 29 ]
R 10
.2 4
[. 20 ,. 28 ]
.3 3
.1 7
�. 38
.3 2
(t a b le co n ti n u es )
488 KJÆRVIK AND BUSHMAN
T hi s do cu m en t is co py ri gh te d by
th e A m er ic an
P sy ch ol og ic al A ss oc ia ti on
or on e of
it s al li ed
pu bl is he rs .
T hi s ar ti cl e is in te nd ed
so le ly
fo r th e pe rs on al us e of
th e in di vi du al us er
an d is no t to
be di ss em
in at ed
br oa dl y.
have been overestimated by .13 to .14 (64–68%), the naïve mean correlation for laboratory studies of aggression (r = .20) might have been overestimated by .08 (39–40%), the na- ïve mean correlation for other reports of aggression (r = .30) might have been overestimated by .08 to .15 (38–52%) and the naïve mean correlation for behavioral measures of aggres- sion (r = .21) might have been overestimated by .08 to .11 (37–57%).
Discussion
This meta-analytic review found a significant positive rela- tionship between narcissism and aggression. The average cor- relation was, r = .25, which is close to Cohen’s (1988) conventional value for a “medium” effect (r = .30) and to Lipsey and Wilson’s (1993) empirical value for the 75th per- centile in the social sciences (r = .30). It exceeds the r = .12 benchmark value, which is reserved for effects labeled signif- icant, important, notable, or consequential (Promising Prac- tices Network, 2014). Thus, the link between narcissism and aggression is not trivial in size. Both normal and pathological narcissism were related to
aggression, and the correlations did not significantly differ in size. These findings suggest that narcissism levels need not be pathological to be a risk factor for aggression. Narcissism is not a unitary construct, and scholars have
identified a core component of narcissism (i.e., entitlement), as well as the two peripheral components (i.e., grandiose nar- cissism, vulnerable narcissism). In this meta-analytic review, all three components of narcissism were related to aggres- sion, and the correlations were of similar size. These findings suggest that entitlement, grandiose narcissism, and vulnerable narcissism are all risk factors for aggression. Narcissism was related to all forms of aggression measured
in the studies included in this meta-analytic review (i.e., direct, indirect, displaced, physical, verbal, bullying offline and online, trolling). Thus, individuals high in narcissism are not particularly picky when it comes to how they aggress against others. However, more research is needed to ascertain the relation between narcissism and trolling, which was measured in only nine studies. Narcissism was also related to both reactive and proactive
aggression. Thus, individuals with high levels of narcissism are inclined to engage in both annoyance-based and incen- tive-based aggression. As noted previously, the two types of aggression are highly correlated, and aggression often has mixed motives (see Bushman & Anderson, 2001). The correlation between narcissism and violence was only
slightly smaller (r = .23) than the correlation between narcis- sism and less serious forms of aggression (r = .26). Thus, nar- cissism is also a risk factor for violent behavior. This finding is consistent with other research suggesting that narcissism might be a risk factor for extremely violent acts such as mass shootings (Bushman, 2018). As expected, provocation was a key moderator of the link
between narcissism and aggression. Individuals high in nar- cissism are especially likely to aggress against others when they are provoked, insulted, humiliated, criticized, orT
ab le
1 (c o n ti n u ed )
M et a- an al ys is
P ub li ca ti on
bi as
an al ys es
F E tr im
an d fi ll
R E tr im
an d fi ll
C M A
S el ec ti on
m od el s
P E T -
P E E S E
D is tr ib ut io n
k N
� r o
95 %
C I
90 %
P I
Q I2
s os r � r o
F P S
ik t&
f F E
� r o
t& f F
E 95 %
C I
F R S
ik t&
f R E
� r o
t& f R
E 95 %
C I
p r 5 � r o
sm m
� r o
sm s
� r o
pp � r o
L ab
(w /o )
68 5, 46 3
.2 1
[. 17 ,. 25 ]
.0 2, .3 9
13 9. 48
51 .9 6
.1 2
.2 1
.2 1, .2 2
R 13
.2 6
[. 21 ,. 30 ]
R 9
.2 4
[. 20 ,. 28 ]
.3 3
.1 8
�. 38
.3 2
T yp e of
re po rt
S el f- re po rt
31 2
10 5, 72 5
.2 6
[. 24 ,. 27 ]
.0 2, .4 6
2, 93 0. 01
87 .3 7
.1 3
.2 6
.2 6, .2 6
.2 6
[. 24 ,. 27 ]
.2 6
[. 24 ,. 27 ]
.2 2
.2 4
.2 2
.2 9
S el f- re po rt (w
/o )
30 6
10 2, 75 3
.2 5
[. 24 ,. 27 ]
.0 5, .4 3
1, 86 3. 32
83 .6 3
.1 2
.2 5
.2 5, .2 5
L 4
.2 5
[. 23 ,. 26 ]
.2 5
[. 24 ,. 27 ]
.2 2
.2 4
.2 3
.2 7
O th er -r ep or t
48 8, 88 4
.3 0
[. 22 ,. 35 ]
�. 10 ,. 61
70 1. 99
92 .1 7
.2 1
.3 0
.2 8, .3 0
R 4
.3 3
[. 26 ,. 39 ]
.3 0
[. 23 ,. 36 ]
.3 2
.2 6
�. 51
.4 8
O th er -r ep or t (w
/o )
47 8, 72 4
.2 8
[. 22 ,. 34 ]
�. 08 ,. 58
45 9. 28
89 .9 8
.2 2
.2 8
.2 7, .2 9
R 4
.3 1
[. 25 ,. 37 ]
.2 8
[. 22 ,. 34 ]
.3 2
.2 4
�. 48
.4 4
B eh av io ra l
93 10 ,7 62
.2 1
[. 17 ,. 25 ]
�. 12 ,. 49
60 5. 73
78 .7 9
.1 6
.2 0
.1 9, .2 0
R 13
.2 4
[. 20 ,. 29 ]
R 15
.2 5
[. 20 ,. 29 ]
.4 2
.1 6
�. 41
.3 3
B eh av io ra l (w
/o )
91 10 ,1 13
.1 9
[. 15 ,. 23 ]
�. 06 ,. 42
30 7. 94
70 .7 7
.1 5
.1 9
.1 8, .1 9
L 1
.1 9
[. 15 ,. 22 ]
R 10
.2 2
[. 18 ,. 26 ]
.2 3
.1 6
�. 39
.2 2
N o te .
w /o
= w it ho ut
ou tl ie rs ; k = nu m be r of
co rr el at io n co ef fi ci en ts in
th e an al yz ed
di st ri bu ti on . W he n k ,
10 , th e di st ri bu ti on
w as
no t an al yz ed
be ca us e th e nu m be r of
st ud ie s w as
to o sm
al l. N =
m et a- an al yt ic sa m pl e si ze ; r� o
= ra nd om
-e ff ec ts w ei gh te d m ea n ob se rv ed
co rr el at io n;
90 %
P I = 90 %
pr ed ic ti on
in te rv al ; Q = w ei gh te d su m
of sq ua re d de vi at io ns
fr om
th e m ea n;
I2 = ra ti o of
tr ue
he te r-
og en ei ty
to to ta l va ri at io n;
be tw ee n- sa m pl e st an da rd
de vi at io n;
os r = on e sa m pl e re m ov ed , in cl ud in g th e m in im
um an d m ax im
um ef fe ct si ze
an d th e m ed ia n w ei gh te d m ea n ob se rv ed
co rr el at io n;
tr im
an d fi ll = tr im
-a nd -f il l an al ys is ; F P S = fu nn el pl ot
si de
(i .e ., si de
of th e fu nn el pl ot
in w hi ch
sa m pl es
w er e im
pu te d;
L = le ft ; R = ri gh t) ; ik = nu m be r of
tr im
-a nd -f il l sa m pl es
im pu te d;
t& fF E r� o
= fi xe d-
ef fe ct s tr im
-a nd -f il l– ad ju st ed
ob se rv ed
m ea n;
t& fF E 95 %
C I = fi xe d- ef fe ct s tr im
-a nd -f il l– ad ju st ed
95 %
co nf id en ce
in te rv al ; t&
fR E r� o
= ra nd om
-e ff ec ts tr im
-a nd -f il l– ad ju st ed
ob se rv ed
m ea n;
t& fR E
95 %
C I = ra nd om
-e ff ec ts tr im
-a nd -f il l– ad ju st ed
95 %
co nf id en ce
in te rv al ; C M A
= cu m ul at iv e m et a- an al ys is ; pr 5 r� o
= m et a- an al yt ic
m ea n es ti m at e of
th e fi ve
m os t pr ec is e ef fe ct s; sm
m r� o
= on e- ta il ed
m od er at e se le ct io n m od el ’s
ad ju st ed
ob se rv ed
m ea n;
sm s r� o
= on e- ta il ed
se ve re
se le ct io n m od el ’s
ad ju st ed
ob se rv ed
m ea n;
P E T -P E E S E = pr ec is io n- ef fe ct
te st – pr ec is io n ef fe ct
es ti m at e w it h st an da rd
er ro r; P E T -P E E S E r� o
= P E T -P E E S E ad ju st ed
ob se rv ed
m ea n;
n/ a = no t ap pl ic ab le
(b ec au se
sm s r� o
pr es en te d no ns en si ca l re su lt s be ca us e of
hi gh
va ri an ce
es ti m at es ). C Is , P Is , an d Q s fo r co rr el at ed
ef fe ct s ar e ba se d on
ro bu st va ri an ce
es ti m at es .
NARCISSISM AND AGGRESSION: A META-ANALYTIC REVIEW 489
T hi s do cu m en t is co py ri gh te d by
th e A m er ic an
P sy ch ol og ic al A ss oc ia ti on
or on e of
it s al li ed
pu bl is he rs .
T hi s ar ti cl e is in te nd ed
so le ly
fo r th e pe rs on al us e of
th e in di vi du al us er
an d is no t to
be di ss em
in at ed
br oa dl y.
threatened by others. However, people high in narcissism are prone to aggression even when they are not provoked.
Robustness of Effects
The relation between narcissism and aggression was stable over time (i.e., 1985 to 2020), including for student samples. There were no gender differences in the magnitude of the relation between narcissism and aggression, suggesting that both males and females high in narcissism tend to be aggressive. However, it is important to note that this does not contradict research showing that males on average are more narcissistic than females (Grijalva et al., 2015), that males on average are more physically aggressive than females (Archer, 2004), and that males commit more violent crimes than females (Grijalva et al., 2015; Heimer, 2000). Further, participant age did not influence the magnitude of the
relation between narcissism and aggression. However, very few studies included older participants. In this meta-analytic review, mean participant ages ranged from 8.3 to 61.7 years. Prior research has shown that narcissism levels decrease with age (Foster, Camp- bell, & Twenge, 2003; Trzesniewski & Donnellan, 2010), and nar- cissistic aggression might also decrease with age. Previous research has shown that people over age 65 have low narcissism levels (Carter & Douglass, 2018), which is outside the mean age range included in this meta-analytic review. Thus, future research should examine narcissistic aggression in older people. This meta-analytic review also challenges the assumption that
results from student and nonstudent populations are substantially different. Narcissism was positively correlated with aggression in both student and nonstudent samples, although the correlation was slightly larger for nonstudents (r = .27) than for students (r = .23). Globally, the relation between narcissism and aggression did
not differ for people from individualistic and collectivistic coun- tries. However, only 12% of the studies were conducted in collec- tivistic countries. Scholars have proposed that individuals high in narcissism from individualistic countries might behave more aggressively than individuals high in narcissism from collectivistic countries (Foster, Shrira, & Campbell, 2003). Although this hy- pothesis was not supported in this meta-analytic review, more research is needed on the link between narcissism and aggression in collectivistic countries to provide a stronger test of this hypothesis. Results converged for experimental cross-sectional, and longitu-
dinal studies, indicating a triangulation of evidence across differ- ent research designs. The term triangulation comes from surveying techniques that determine the location of a single point with the convergence of measurements taken from two different points (Rothbauer, 2008). The idea behind triangulation is that one can get a more accurate view of relation between two variables when different methodological approaches yield similar results. The results also were relatively robust to publication bias and outliers.
Theoretical Implications
Theoretically, these findings are consistent with the threatened egotism model (Baumeister et al., 1996). As expected, the relation between narcissism and aggression was much stronger when par- ticipants were provoked than when they were not provoked. These
findings suggest that individuals high in narcissism have “thin skins” (i.e., fragile egos) when others threaten, criticize, humiliate, or shame them. Narcissism was positively related to aggression even in the absence of provocation. This finding has interesting theoretical implications. Perhaps seeing others as inferior beings is sufficient to ignite aggression in individuals high in narcissism, even in the absence of provocation.
Contrary to the SPIN model (Grapsas et al., 2020), the relation between narcissism and aggression was weaker for status-related provocations than for affiliation-related provocations. However, both types of provocations increased narcissistic aggression.
However, most studies that examined the link between narcis- sism and provoked aggression were conducted in laboratory set- tings with student samples. Thus, future studies should investigate the influence of provocation on the narcissism-aggression link using other samples (e.g., children, older adults) in other settings (e.g., online, field).
When examining the relation between narcissism and aggres- sion, it appears that all three dimensions are related to aggression (i.e., entitlement, grandiose narcissism, vulnerable narcissism). It is not just individuals who are high in entitlement and grandiose narcissism that lash out aggressively against others; people who are high in vulnerable narcissism do that too.
Narcissism was also related to all forms of aggression studied. Individuals high in narcissism tend to be more aggressive across the board, especially when they are provoked.
Narcissism was also related to both functions of aggression. These findings suggests that individuals high in narcissism do not just aggress against others in an impulsive, hostile, and reactive manner. They also aggress against others in a cold, calculated, deliberate, instrumental, and proactive manner.
Conclusion
This meta-analytic review suggests that narcissism is an important risk factor for both aggression and violence. People high in narcissism believe they are special people who deserve special treatment. They think they are the “center of the universe.” When they do not get the “expected” special treatment they think they are entitled to, they tend to lash out at others in an aggressive manner. Individuals high in nar- cissism also have “thin skins” (i.e., fragile egos). They are especially likely to aggress against others when they are provoked, insulted, humiliated, criticized, or threatened by others. However, they are also prone to aggression when they are not provoked. They not only aggress against others in a “hot-headed” manner. They also aggress against others a “cold-hearted” manner.
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490 KJÆRVIK AND BUSHMAN
T hi s do cu m en t is co py ri gh te d by
th e A m er ic an
P sy ch ol og ic al A ss oc ia ti on
or on e of
it s al li ed
pu bl is he rs .
T hi s ar ti cl e is in te nd ed
so le ly
fo r th e pe rs on al us e of
th e in di vi du al us er
an d is no t to
be di ss em
in at ed
br oa dl y.
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in at ed
br oa dl y.
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*Brennan, S. M. (2014). Pathological narcissism and reflective function: A moderated mediation model of the cycle of violence. ProQuest Information & Learning. http://proxy.lib.ohio-state.edu/login?url=http:// search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2015 -99060-130&site=ehost-live
*Brewer, G., Hunt, D., James, G., & Abell, L. (2015). Dark triad traits, infidelity and romantic revenge. Personality and Individual Differences, 83, 122–127. https://doi.org/10.1016/j.paid.2015.04.007
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*Burns, M. R. (2003). Self esteem, narcissism, and overt aggression in ado- lescents: Exploring the relationship of trust. ProQuest Information & Learning. Retrieved from http://proxy.lib.ohio-state.edu/login?url=http:// search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2004 -99002-247&site=ehost-live
492 KJÆRVIK AND BUSHMAN
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*Chan, H. C., & Beauregard, E. (2016). Non-homicidal and homicidal sex- ual offenders: Prevalence of maladaptive personality traits and para- philic behaviors. Journal of Interpersonal Violence, 31(13), 2259–2290. https://doi.org/10.1177/0886260515575606
*Charbonnier, J. (2017). Female aggression as an interactive effect of in- ternal locus of control and pathological narcissism: A multiple regres- sion analysis. ProQuest Information & Learning. Retrieved from https:// proxy.lib.ohio-state.edu/login?url=http://search.ebscohost.com/login .aspx?direct=true&db=psyh&AN=2017-36665-141&site=ehost-live
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*Maples, J. L., Miller, J. D., Wilson, L. F., Seibert, L. A., Few, L. R., & Zeichner, A. (2010). Narcissistic personality disorder and self-esteem: An examination of differential relations with self-report and laboratory- based aggression. Journal of Research in Personality, 44(4), 559–563. https://doi.org/10.1016/j.jrp.2010.05.012
*March, E. (2019). Psychopathy, sadism, empathy, and the motivation to cause harm: New evidence confirms malevolent nature of the Internet troll. Personality and Individual Differences, 141, 133–137. https://doi .org/10.1016/j.paid.2019.01.001
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*Meier, M. J. (2003). Exploring narcissism in a group of male batterers. ProQuest Information & Learning. Retrieved from http://proxy.lib.ohio- state.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true& db=psyh&AN=2004-99007-060&site=ehost-live
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*Migliosi, B. (2010). The role of parental love inconsistency in the development of narcissism and aggression. ProQuest Information & Learning. Retrieved from http://proxy.lib.ohio-state.edu/login?url=http://search.ebscohost.com/login .aspx?direct=true&db=psyh&AN=2010-99220-307&site=ehost-live
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Received August 26, 2019 Revision received February 3, 2021
Accepted February 3, 2021 n
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- The Link Between Narcissism and Aggression: A Meta-Analytic Review
- Outline placeholder
- Narcissism Is Not a Dichotomy
- Narcissism Is Not a Unitary Construct
- Pathological Levels of Narcissism
- Aggression and Violence
- Narcissism and Aggression
- Provocation
- Exploratory Moderator Variables
- Source Characteristics
- Participant Characteristics
- Design Characteristics
- Previous Meta-Analytic Reviews
- Method
- Literature Search
- Inclusion Criteria
- Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Flowchart
- Theoretical Moderator Variables
- Normal Versus Pathological Narcissism
- Narcissism Dimensions
- Aggression and Violence
- Provocation
- Exploratory Moderator Variables
- Source Characteristics
- Participant Characteristics
- Design Characteristics
- Intercoder Reliability
- Analysis Strategy
- Results
- Study Characteristics
- Overall Results
- The Link Between Narcissism and Aggression and Violence
- Normal Versus Pathological Narcissism
- Narcissism Dimensions
- Forms of Aggression
- Functions of Aggression
- Provocation
- Source Characteristics
- Year
- Publication Status
- Participants Characteristics
- Gender
- Age
- University Students
- Country
- Design Characteristics
- Type of Design
- Type of Setting
- Type of Report
- Sensitivity Analyses
- Discussion
- Robustness of Effects
- Theoretical Implications
- Conclusion
- References