Malevolent Forces

Abstract

The Dark Triad is represented by three interrelated personality characteristics thought to share a “dark core”—that is, to be associated with a range of negative outcomes. We investigate this link alongside another potent predictor of crime, low self-control. Our analyses found the Dark Triad was strongly predictive of delinquency, especially violent delinquency, where it accounted for the effects of self-control. Yet it exerted no significant effect on drug-based delinquency. However, an interaction between the Dark Triad and low self-control remained substantive and predictive across all models, where low self-control amplified the effects of the Dark Triad on delinquency.

Keywords

dark triad low self-control psychopathy malevolence juvenile delinquency

The publication of Gottfredson and Hirschi’s (1990) A General Theory of Crime generated unparalleled criminological interest. Backed by an easy to employ attitudinal scale developed by Grasmick, Tittle, Bursik, and Arneklev (1993), along with a slew of other scales constructed in secondary data sets, studies and debates into the effects of self-control have flourished (de Ridder, Lensvelt-Mulders, Finkenauer, Stok, & Baumeister, 2012; Moffitt et al., 2011; Pratt & Cullen, 2000; Rebellon, Straus, & Medeiros, 2008). Indeed, by any metric, tests of self-control have accumulated at a rate never before witnessed in the criminological cannons. Few theories or variables can claim to have had such an impact on criminological discourse, theorizing, or research. Even so, the success of the general theory in directing research and scholarly interest has likely also had heretofore unrealized consequences.

One of the more important consequences has been that the almost exclusive focus on self-control has drawn attention away from other individual-level variables related to criminal behavior. Research into personality factors and individual traits related to aggression and criminal involvement has received scant attention in criminology even though a large body of evidence in psychology documents a link between personality and conduct problems (Fridell, Hesse, Jaeger, & Kuhlhorn, 2008; Le Corff & Toupin, 2010; Miller, Lynam, & Leukefeld, 2003; Samuels et al., 2004). Individual traits, such as negative emotionality (Krueger et al., 1994), intelligence (Lynam, Moffitt, & Stouthamer-Loeber, 1993), psychopathy (Hare, 1996), impulsivity (White et al., 1994), and callous and unemotional (CU) traits (Frick & White, 2008), have all been linked to problem behavior, as have the personality factors of low contentiousness and agreeableness (Jones, Miller, & Lynam, 2011; Miller & Lynam, 2001; Ozer & Benet-Martinez, 2006; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007).

Historically, Agnew, Brezina, Wright, and Cullen (2002, p. 45) notes, “the role of personality traits was discounted by mainstream criminologists until recently and most data sets do not allow for the examination of personality traits” (see also, Andrews & Wormith, 1989; Caspi et al., 1994; Walsh, 2000). Granting Agnew et al.’s (2002) argument, the almost exclusive focus on self-control has likely further precluded investigation into other individual features—features that may compete with, interact with, or otherwise account for the effects of self-control on conduct problems. By any measure, omitted variable bias is potentially serious, empirically and theoretically. A second concern, however, emerges when Gottfredson and Hirschi’s (1990) assumptions about the nature of crime are juxtaposed against a growing body of research evidence—a body of evidence that presents a different picture of criminal behavior than they proposed originally.

Malevolent Forces

Gottfredson and Hirschi (1990) based their conception of self-control on what they called the “nature of crime.” The nature of crime is that it is easy to commit, takes little planning, and is driven predominately by available opportunities. Criminals, by extension, are simply opportunists who lack the ability to control their impulse to offend in the presence of a criminal opportunity. They are impulsive, do not think of the consequences of their behavior, prefer immediate gratification over long-term planning and rewards, and they put little cognitive effort into their criminal actions. Offenders haphazardly stumble from crime to crime and are easily induced to act in ways that violate social mores and laws.

At one level, Gottfredson and Hirschi’s conception of the nature of crime is supported by a broad array of evidence. Criminals are generally impulsive (Lynam et al., 2000; White et al., 1994), show little planning in the commission of crime (Hochstetler, 2001; Petrosino & Brensilber, 2003), and engage in a variety of offenses ranging from petty crimes to serious crime (Baron, 2003; Evans, Cullen, Burton, Dunaway, & Benson, 1997; Keane, Maxim, & Teevan, 1993; Piquero, MacDonald, Dobrin, Daigle, & Cullen, 2005). This depiction has gone largely unchallenged in criminology. By contrast, however, threads of disparate studies paint a very different picture of an important subgroup of offenders: a subgroup of offenders that are predatory and callous. These offenders are, at a minimum, indifferent to the suffering they cause others or they may appear to relish in the suffering they cause. Their behaviors, moreover, may seem excessively cruel and morally repugnant. And contrary to the assumptions of Gottfredson and Hirschi, their behaviors are not entirely driven by opportunity but instead appear rooted in emotional and cognitive preferences to inflict harm on others for reasons that are often instrumental. They are, in other words, malevolent.

Some psychologists have called attention to the role of malevolence in human conduct generally (Goldberg, 1995; Hurlbert & Apt, 1992). Others, however, have argued that a subgroup of individuals with antisocial personality disorder can be characterized as malevolent. Millon, Grossman, Millon, Meagher, and Ramnath (2004, p. 161), for example, describe these individuals as “belligerent, rancorous, vicious, malignant, brutal, callous, vengeful, and vindictive.” Malevolent individuals “anticipate betrayal and punishment,” and they are willing to victimize “those too weak to retaliate or those whose terror might prove particularly entertaining.” Similar to other antisocial individuals, malevolent individuals engage in a diverse range of problem behaviors, including crime, but appear to do so with greater frequency and across a broader set of environmental conditions. That said, the relative frequency of their misconduct is matched only by the extremity or severity of their behavior.

Case studies of serious offenders, including serial murderers and sexual sadists, illustrate well the concept of malevolence (Carlisle, 1993; Fox & Levin, 1998; Heide & Keeney, 1995; Santtila et al., 2008). Even so, seemingly divergent areas of research evidence can be connected to shed light on how malevolence can be seen as an organizing framework. The first line of research points to “callous-unemotional (CU)” traits (Frick & White, 2008). These traits predispose individuals to view others as objects to be manipulated, they reflect an absent or deficient level of concern for others, and they reflect a willingness to use violence and coercion for instrumental gains. Research on CU traits has grown precipitously since the early 1990s and converges to show a relatively strong association between these trait clusters and especially serious and temporally stable conduct problems in children (Caspi, 2000; Heaven, 1996; Jolliffe & Farrington, 2004; Lahey et al., 1995; Loeber, Green, Keenan, & Lahey, 1995; Murray & Farrington, 2010; Stams et al., 2006). The CU traits are highly heritable, tend to cluster within some children, and have been found to differentiate seriously conduct disordered (CD) children from those who display less threatening antisocial behavior but still fit the diagnosis of CD (Barry et al., 2000; Christian, Frick, Hill, Tyler, & Frazer, 1997; Fontaine, McCrory, Boivin, Moffitt, & Viding, 2011; Frick, Cornell, Barry, Bodin, & Dane, 2003; Frick, Stickle, Dandreaux, Farrell, & Kimonis, 2005; Viding, Blair, Moffitt, & Plomin, 2005; Viding, Frick, & Plomin, 2007). Frick, O’Brien, Wootton, and McBurnett (1994) argued that CU traits displayed in childhood overlap considerably with traits thought to measure psychopathy in adulthood and that a significant number of CU-defined children mature into adult psychopaths. “Current findings suggest that CU traits may define CD children who have extreme behavior problems,” summarized Moffitt and her colleagues (2008, pp. 8–9), and these children have a “stronger genetic risk, and at-risk neurocognitive profiles […] children with CU traits show more conduct problems, more severe aggression and more proactive aggression than other children with CD.”

The second line of research reflects a relatively new psychological construct—one that aligns closely with research on childhood CU traits and one that captures the more willful and intentional motivations underpinning some serious behavior. Known as the “Dark Triad (DT),” this construct is represented by three “dark” interrelated personality profiles: narcissism, Machiavellianism, and psychopathy (Paulhus & Williams, 2002). Narcissism reflects exaggerated self-importance, a sense of entitlement, and a desire for social superiority and admiration (Corry, Merritt, Mrug, & Pamp, 2008). Machiavellianism reflects a cold, calculating, manipulation of others, often through deception, and most often to achieve goals that benefit self (Jones & Paulhus, 2009). Psychopathy reflects impulsive decision-making, selfishness, a lack of empathy, and a lack of remorse (Hare, 1996; Lilienfeld & Andrews, 1996). Each of the three constructs has been subject to substantial psychological testing and research and each is accompanied by an extensive literature. However, only recently have psychologists advanced the likelihood that these three personalities reflect the malevolent aspects of human personality. “Despite their diverse origins,” note Paulhus and Williams (2002, p. 557), “the personalities composing the ‘Dark Triad’ share a number of features. To varying degrees, all three entail a socially malevolent character with behavioral tendencies toward self-promotion, emotional coldness, duplicity, and aggressiveness.”

In language typical of psychological research, narcissists have been found to engage in aggression only after an ego threat was presented (Jones & Paulhus, 2010), while Machiavellians have been found to be more likely to plagiarize (Nathanson, Paulhus, & Williams, 2006). Of course, psychopathy has a long history of research, but it has also been found to be highly predictive of aggressive behavior in studies of the DT (Baughman, Dearing, Giammarco, & Vernon, 2012; Pailing, Boon, & Egan, 2014). Overall, DT research has shown that individuals who score high on DT traits are more “toxic” in work settings (Jonason, Slomski, & Partyka, 2012; O’Boyle, Forsyth, Banks, & McDaniel, 2012), that they engage in relatively risky behaviors, such as gambling and mate poaching (Jonason, Li, & Buss, 2010; Jones, 2013b), that they report less intimate relationships and more frequent sexual encounters (Jonason, Li, Webster, & Schmitt, 2009; Jonason, Luevano, & Adams, 2012), engage in animal cruelty (Kavanagh, Signal, & Taylor, 2013), and that they report higher levels of racism (Jonason, 2015; Jones, 2013a).

To date, however, only a few studies have examined the association between DT and delinquency. Chabrol, Van Leeuwen, Rodgers, and Sejourne (2009) examined the relationship between the DT scales, measures of sadistic personality traits, and self-reported delinquency in a sample of 615 French high school students. They found that psychopathy and sadism were significant predictors of delinquency for boys but not for girls and that Machiavellianism and narcissism were unrelated to delinquency. In the second study, Kerig and Stellwagen (2010) examined teacher reports of DT traits and measures of aggression in 252 youth age 11–14 years old. Each of the DT subscales produced differential effects on the various measure of childhood aggression. Finally, Muris, Meesters, and Timmermans (2013) examined self and parent reports of child DT traits and problem behavior in 117 youth from the Netherlands. Child-reported Machiavellianism and psychopathy were positively and significantly correlated with measures of aggression and delinquency even after controlling for shared variance of the influence of a broad range of other personality factors.

Third, criminologists have created rich ethnographic accounts of offender behavior. In general, these accounts provide robust support for Gottfredson and Hirschi’s (1990) conception of criminal offenders as opportunists. On the other hand, these same ethnographic accounts reveal glaring examples of predatory, callous offending. Wright and Decker’s (1994, 1997) interviews with active armed robbers and burglars, for example, contained several examples. Many of their offenders reported that they enjoyed committing crime in part because of the power, control, and terror they induced in their victims. Elements of toughness and even cruelty are also present in Anderson’s (1999) account of the “code of the streets.” Street credibility, according to Anderson, is an important psychosocial mechanism that justifies all sorts of brutality. Shover’s (1996) underappreciated study of persistent thieves also details the important ways subgroups of offenders view the world and their behavior. Shover, for example, classifies a group of thieves he studied as “fuck ups” (1996). These individuals align closely to Gottfredson and Hirschi’s (1990) conception of the criminal offender. They lack follow through, are influenced by criminal opportunities, are hedonistic, and generally fail in most of their life endeavors. Still, however, Shover portrays another group of thieves as lifestyle criminals that prefer crime, enjoy committing crime, and show little remorse for their actions.

Yet Shover (1996) and Wright and Decker’s (1994, 1997) accounts of active offenders and their callousness pale in comparison to those provided by Copes, Hochstetler, and Williams (2008) and Hochstetler, Copes, and Williams (2010). In sometimes graphic detail, their interviews of men convicted of street crimes reveal a brazen and utilitarian use of violence against others, including vulnerable “crackheads” (Copes et al., 2008). Subjects described the purposeful exploitation and manipulation of drug addicts to secure their position in the social hierarchy of the street culture, while some detailed carjackings and other excessively violent assaults. Many of those interviewed expressed a remarkable lack of empathy. Some stated that they found “instrumental violence” necessary to assert dominance over their victims, to maintain control during a robbery, or even to inhibit further physical escalation. However, many made a clear distinction between their “justifiable” actions and those on the street who they deemed “authentically violent” as Hochstetler et al. (2010) relayed in one such case:

Mark hit him hard enough to where, dude, he didn’t shake back. Dude was in a coma for a long time…ended up with brain damage. It was messed up. We had the dude beat. The dude gave us the car keys. Mark, he didn’t care. His adrenaline was full he didn’t care if he killed the kid or not. (p. 502)

Malevolent offenders are known, feared, and distrusted by other criminal offenders in part because their behaviors are unnecessarily violent and their temperaments unpredictable. According to Hochstetler and his colleagues (2010) even their co-offenders describe them as, “senseless, self-defeating, and crazy,” with some claiming that their accomplice’s pathologies are biologically rooted (p. 503). For instance, in another example, an offender detailed how his partner chose not to carry a gun because “he enjoyed beating victims with his bare hands” (p. 501).

The Current Study

Similar to research on CU traits, where CU children share behavioral styles with their CD peers but stand apart in terms of the seriousness of their behavior, we suspect that our measure of malevolent personalities, called the Dark Triad, and our measure of low self-control will predict variation in delinquency. However, we also expect that malevolence should be more strongly associated with violent behavior and should be less associated, if at all, with minor forms of deviance. Theoretically, our study also juxtaposes two competing views about the nature of crime. If Gottfredson and Hirschi (1990) are correct and the nature of crime is intimately linked to low self-control, then our measure of malevolence should be statistically unrelated to our dependent measures. If so, then a core assumption of self-control theory would be supported. Conversely, if malevolence matters then the nature of crime described by Gottfredson and Hirschi would be called into question, if not entirely then at least partially.

To organize our empirical examination, we developed a priori four research hypotheses. These hypotheses reflect expectations drawn from prior research and theorizing, including the research examined above (Agnew, Brezina, Wright, & Cullen, 2002; Block, 1995; Caspi et al., 1994; Lilienfeld, 1999). The first three hypotheses, for example, reflect expectations culled from prior studies and are reasonably specific. They are also falsifiable. The last hypothesis, however, is less specific but still falsifiable. While theory would predict the likelihood of a multiplicative interaction between low self-control and malevolence, we know of no studies that have examined this possibility. As such, we treat models that include the interaction term as exploratory, especially since our data cannot establish temporal ordering.

Hypotheses

Prior research suggests a series of testable propositions related to self-control, the Dark Triad, and delinquent and violent behavior. We make these propositions explicit below.

Hypothesis 1: We expect that the Dark Triad index will predict variation in problem behaviors independent of levels of self-control.

Hypothesis 2: We expect the Dark Triad index to account for the effects of self-control on measures of serious violence.

Hypothesis 3: We expect the Dark Triad index will be unrelated to less serious forms of problem behavior.

Hypothesis 4: We expect a significant multiplicative interaction between the Dark Triad index and the measure of low self-control.

Method

Sample

Data for this study resulted from a collaboration between Western scholars and academics from the Kingdom of Saudi Arabia. The collaboration represents an effort by the Kingdom to reform and examine Saudi society through the development of a vibrant social science. American faculty consulted in the creation of the survey and adapted the wording of questions to reflect the culture and language of Saudi youth. Since this was the first time systematic data on the offending behaviors of Saudi youth had been collected, the decision was made to utilize previously validated measures to assess key constructs. The use of validated measures reduced the chance that findings could be attributable to measurement error and they provided a comparative benchmark to evaluate the patterns of responses provided by Saudi youth (see also, Sacarellos et al., 2016). The survey was originally produced in English, translated to Arabic, and then provided to students who primarily spoke Arabic.

Subjects for this sample were drawn from a large city in Saudi Arabia with a population of over three million. The development of the sampling frame included all public and private religious high schools in the city, totaling over 200 schools and more than 100,000 students, which was then stratified by geography since it corresponded closely to socioeconomic differences within the city. As schools in Saudi Arabia are segregated by sex, we then identified schools on this characteristic and randomly selected eight schools for boys and eight schools for girls from the four geographic areas of the city: North, South, Central, and East. Two schools from each area were selected, one for data collection and one to be placed on a reserve list.

King Abdulaziz University (KAU) faculty approached the administration of identified schools and requested permission for the implementation of this survey. No principal refused this request. The KAU faculty then randomly selected “homeroom” teachers from within each school and sought their support. Again, none declined. There were no objections raised by any officials nor did officials in the schools or the Saudi government influence the creation or implementation of the survey. Five hundred survey questionnaires were distributed to 10th through 12th grade male students and another 500 to female students. Participation in the survey was optional. Confidentiality was assured to students and schools alike as no identifying information was collected. Surveys were distributed during a 50-min block of class time, where trained KAU staff were present and oversaw the administration of the survey.

Although we cannot make a definitive statement as to the generalizability of the male and female samples to broader Saudi society, we note that the patterns of behavior reported here are virtually identical to the patterns reported in samples of Western youth. Methodological differences limit direct comparisons, however, prevalence estimates from data in three major U.S. cities found that approximately 20% to 25% of juvenile males engaged in various street crimes—with female juveniles engaging in such crimes less than half as much (Huizinga, Loeber, & Thornberry, 1993). In our sample, males often committed anywhere from 10% to 25% or more of various delinquent acts with girls committing about half of that amount. For example, 25% of Saudi boys reported stealing or attempting to steal something and 18% reported being involved in a gang fight. In contrast, only 9% of Saudi girls reported theft and 7% reported involvement in a gang fight. Additionally, although the use of alcohol and marijuana is much lower in our sample due to its country-wide prohibition, drug use was not absent in our sample: 6% reported drinking alcohol, 8% used marijuana, 7% abused prescription drugs, 27% used tobacco, and 11% used other illicit substances. These cross-cultural findings indicate that youth delinquency, whether occurring among boys or girls, is a relatively common phenomenon even in traditionally conservative societies like Saudi Arabia.

Dark Triad

Originally, measures of the Dark Triad personalities included extensive batteries of assessments for each trait (Paulhus & Williams, 2002). Narcissism, for example, was measured by use of the 40-item NPI, Machiavellianism was measured by the 20-item MACH-IV, and psychopathy was captured by the 31-item SRP-III. Collectively, prior assessments of the DT contained 91 items, making use of the DT scale cumbersome. Recognizing this limitation, Jonason and Webster (2010) created a reduced form measure of the DT containing 12 items, 4 for each personality construct. Known as the “Dirty Dozen,” it has received considerable attention and validation in psychological research (Jonason & Luevano, 2013; Maples, Lamkin, & Miller, 2014; Rauthmann & Kolar, 2012; Webster & Jonason, 2013). Jonason, Kaufman, Webster, and Geher (2013) assert that, “the Dirty Dozen has good convergent validity with the HEXACO model of personality, has good psychometric properties in terms of Item Response Theory, and has been useful in theory-testing” (p. 81).

Debate about how best to measure the Dark Triad continues (Jonason, Kavanagh, Webster, & Fitzgerald, 2011; Jones & Paulhus, 2010; Paulhus, 2014) with some scholars suggesting that the modest positive correlations between the scales reflect a broader personality archetype (Jakobwitz & Egan, 2006; O’Boyle, Forsyth, Banks, Story, & White, 2015) or that it can be subsumed under psychopathy (Glenn & Sellbom, 2015). Paulhus and Williams (2002), however, conceptualized the Dark Triad as three separate but overlapping personality constructs. Understood this way, scholars have analyzed the independent effects associated with each personality scale (Rauthmann, 2011) and have argued that the three personalities are unique due to their “behavioral, attitudinal and belief-related components” (Jones & Figueredo, 2013, p. 528). For instance, narcissists are egotistical, Machiavellians are detached and calculating, and psychopaths lack concern for others. Together, contend Paulhus and Williams (2002), these personalities share a dangerous “dark core” that manifests as a callous and manipulative, malevolent personality (Furnham, Richards, & Paulhus, 2013).

Other scholars, however, have argued that the intercorrelations between the three scales suggest that they are empirically indistinguishable, and thus DT should be measured as a broad index (Jonason, Li, & Teicher, 2010). Playing to both the conceptual and empirical overlap between the Dark Triad’s dimensions, the use of Jonason and Webster’s (2010) summated 12-item index facilitates examination of the joint effects of these subscales across outcomes. Example items for the “Dirty Dozen” ask whether the student seeks admiration and status, lies and manipulates others to get his or her way, or is unconcerned with the morality of his or her actions and tends to lack guilt. Higher scores indicate greater levels of Dark Triad traits, and items were rated on a 3-point Likert-type scale where 1 = not true, 2 = sometimes true, and 3 = often true (α = .80).

We note that the mean for the DT index was a relatively low 18.2 (range = 12–36) and that the distribution was positively skewed. Given that we use a community sample of youth in school, the distributional qualities of the DT index are to be expected with comparatively few subjects showing high levels of malevolent personality traits. Similar distributional qualities have been found in other studies of the Dark Triad using a variety of different samples. The limited variation in the DT index, coupled to a sample of youth still in school, provides a conservative test of the association between the DT and our measures of delinquency.

Low Self-Control

The measure of low self-control consists of 25 items tapping several characteristics such as impulsivity, risk-seeking behavior, task completion, self-centeredness, and anger management. Included within this measure are 16 items modified from the original Grasmick Scale of low self-control (Grasmick, Tittle, Bursik, & Arneklev, 1993) and 9 items adapted from the Project on Human Development in Chicago Neighborhoods (PHDCN) survey regarding temperament and perseverance at school (Earls, 1999). This measure is coded so that higher scores indicate lower levels of self-control. Items were rated on a 3-point scale where 1 = not true, 2 = sometimes true, and 3 = often true (α = .86). Appendix A contains the list of items used to construct the self-control and Dark Triad measures.

Delinquency

The student’s delinquency was captured using 27 items modified from the National Youth Survey (NYS), a comprehensive self-report measure documented in criminological research (Huizinga & Elliott, 1986, 1987; Lauritsen, Sampson, & Laub, 1991). This measure inquires about a host of behaviors ranging from being loud and unruly in public, to theft or drug use, and physical violence against a person. Items asked the student how often they engaged in specific delinquent behaviors and were scored on a 3-point scale where 1 = not true, 2 = sometimes true, and 3 = often true with higher scores reflecting more misbehavior (for a complete listing, see Sacarellos et al., 2016). The full index (α = .92) is used in our initial models, but we later decompose this measure into two distinct categories for further analysis: violent delinquency and drug delinquency. Violent delinquency consists of 5 items regarding the student’s use of physical force, threats, or the intent to injure or kill (α = .71). Drug delinquency consists of 8 items asking about the student’s use of illegal drugs or their involvement in drug dealing (α = .75).

Control Variables

Several contemporary control variables are included in our study, including the student’s gender (female = 0, male = 1), grade level (10th = 0, 11th = 1, 12th = 2), and average grades at school (0 = A, 1 = B, 2 = C, 3 = D). Two variables capture socioeconomic status: a measure of whether the student resided in a two-parent family household (0 = yes, 1 = no) and the level of education for both the mother and father (0 = university level, 1 = high school, 2 = less than high school). The latter was a combination of two scales and the single measure we use (ranging from 0 to 4) indicates lower levels of parental education at higher values. We also controlled for the amount of family conflict in the household. This measure was composed of 12 items adapted from the PHDCN family conflict and control scales and features questions pertaining to the level of attachment and supervision the student has with their family, the amount of arguing and violence in the home, and how often family members have been in trouble with the police or arrested. Items were scored on a 3-point Likert-type scale where 1 = never, 2 = sometimes, 3 = always (α = .72).

Additionally, in recognition of prior research on youth delinquency, we controlled for the student’s own victimization and their delinquent peer-group associations (Lauritsen et al., 1991; Matsueda & Anderson, 1998; Warr & Stafford, 1991). Victimization was captured using 7 items taken from the Boston Youth Survey regarding whether the student has been bullied, harassed, threatened, or physically assaulted (Sparks, 1981). Items were scored on a 3-point Likert-type scale where 1 = never, 2 = sometimes, 3 = often (α = .80). Delinquent peers were measured using 11-items derived from the NYS, containing similar questions related to that asked of the individual student. Examples include whether their friends use illegal drugs, engage in theft or physical violence, or have gotten into trouble with the authorities. Items were scored on a 3-point Likert-type scale where 1 = none of them, 2 = some of them, and 3 = most of them (α = .88). Appendix B contains a correlation matrix of our variables and delinquent outcomes.

Results

Descriptive statistics are presented in Table 1. The sample was equally male and female, the typical student was in the 12th grade, had roughly a “B” grade point average at school, and the vast majority of students resided in a two-parent household. Similar to studies of delinquency in Western youth, base rates of offending, association with delinquent peers, and victimization were relatively low. Even so, correlational patterns present in the Saudi sample mirror patterns found in Western samples. We note that we examined several transformations of our dependent variables to account for skewness. Results were not influenced by skewness, so we report parameter estimates associated with nontransformed dependent variables.

Table 1.

Descriptive Statistics.

Independent Variables	Minimum	Maximum	Mean	SD	α
Gender	0	1	.500	.500	—
Grade level	0	2	1.74	.591	—
School grades	0	3	.728	.784	—
Two-parent household	0	1	.082	.275	—
Parent’s education	0	4	1.97	1.32	—
Family conflict	12	36	20.94	4.15	.715
Victimization	7	21	9.45	2.65	.795
Delinquent peers	11	33	14.36	4.04	.884
Low self-control	25	75	44.32	8.10	.855
Dark triad	12	36	18.22	4.20	.799
Dependent variables
All delinquency	27	77	30.80	6.09	.916
Violent delinquency	5	15	5.67	1.35	.709
Drug delinquency	8	24	8.91	1.81	.751

Table 2 presents the results of our regression on the full measure of student delinquency. In Model 1, we include the control variables and the measure of low self-control. The findings indicate that higher levels of family conflict (β = .05), interpersonal victimization (β = .16), and delinquent peers (β = .45) were significantly associated with increased levels of individual delinquency. Moreover, as expected, lower levels of individual self-control (β = .13) were also significantly associated with delinquency.

Table 2.

OLS Regression of Independent Variables on All Delinquency.

Independent Variables	Model 1			Model 2			Model 3
Independent Variables	b	SE	β	b	SE	β	b	SE	β
Gender	.303	.392	.025	.140	.392	.012	.179	.372	.015
Grade level	.073	.286	.007	−.009	.286	−.001	−.123	.271	−.012
School grades	.347	.214	.045	.297	.213	.038	.332	.202	.043
Two-parent household	.952	.562	.043	.975	.559	.044	.781	.530	.035
Parent’s education	.093	.120	.020	.103	.119	.022	.074	.113	.016
Family conflict	.077	.039	.053*	.057	.039	.039	.000	.038	.000
Victimization	.360	.065	.156***	.323	.065	.141***	.319	.062	.139***
Delinquent peers	.677	.045	.449***	.661	.045	.439***	.611	.043	.406***
Low self-control	.099	.021	.132***	.053	.024	.071*	.054	.023	.072*
Dark triad	—	—	—	.172	.047	.119***	.126	.045	.087**
Interaction	—	—	—	—	—	—	.034	.003	.258***
	R ² = .387			R ² = .395			R ² = .457
	N = 1,000			N = 1,000			N = 1,000

Note. OLS = ordinary least square.

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

In Model 2, we introduced the Dark Triad measure into the equation. The inclusion of this measure accounted for the effects of family conflict but had only a slight impact on the estimated coefficients for victimization (β = .14) and for delinquent peers (β = .44). Notably, however, the addition of the DT measure reduced the influence of low self-control by almost 50% (β = .07). Moreover, the estimated effect of DT on self-reported delinquency was comparatively larger than the effect of low self-control on delinquency (β = .12) although a differences of slopes tests was statistically insignificant. This finding strongly suggests that the Dark Triad index captures variation in offending typically attributed to low self-control.

Finally, in Model 3, we introduced a multiplicative interaction term between the low self-control and Dark Triad measures. The interaction was analyzed through the use of an SPSS computational tool called MODPROBE produced by Andrew Hayes (Hayes & Matthes, 2009). The analytical procedure embedded in MODPROBE centers the main effects prior to multiplication and then estimates predicted values in the dependent variable across levels of the interaction. Inclusion of the interaction term reduced only slightly the significant effects of victimization (β = .14) and delinquent peers (β = .41). Both main effects retained statistical significance. As hypothesized, the interaction term was statistically significant and substantive (β = .26). Inclusion of the interaction term increased the explained variance of the model by 6%. Inspection of variance inflation factors and correlations matrices, however, revealed no substantive influence of multicollinearity. To explore the interaction further, we show in Figure 1 a visualization of the interaction. For purposes of clarity, scores are presented as plus or minus 1 standard deviation (SD) from the mean. As is apparent, individuals scoring at or above 1 SD on the measure of self-control, which translates to low self-control, and who also scored 1 SD or above on the Dark Triad had the highest level of reported delinquency.

Figure 1.

Interaction of self-control and Dark Triad on all delinquency.

Our next set of analyses separate measures of general delinquency from the measures that tap into violent delinquency. Prior research and theory suggests that individuals with CU traits and those who score high on the Dark Triad are more likely to engage in more serious types of problem behavior. Recall that these characteristics have been associated with a higher propensity to use violence and to engage in levels of violence that are more extreme (Frick & Dickens, 2006). We test this possibility in the next set of analyses by examining the influence of low self-control and the Dark Triad on the subset of items that measure interpersonal violence.

Table 3 shows the results of these analyses. In Model 1, we found that school grades (β = .07), victimization experiences (β = .11), delinquent peers (β = .43), and low self-control (β = .12) were statistically associated with the measure of violent delinquency. In Model 2, we included the measure of the DT. The effect of the DT on violent delinquency was statistically significant and nontrivial (β = .16). More importantly, the inclusion of the DT index accounted entirely for the effect associated with low self-control. In Model 3, we again entered the interaction term, recognizing that the main effects of low self-control were not statistically significant. The interaction term was nonetheless substantive and statistically significant (β = .29). Figure 2 presents the visualization of this interaction on violent delinquency.

Table 3.

OLS Regression of Independent Variables on Violent Delinquency.

Independent Variables	Model 1			Model 2			Model 3
Independent Variables	b	SE	β	b	SE	β	b	SE	β
Gender	−.002	.092	−.001	−.049	.091	−.018	−.040	.086	−.015
Grade level	.056	.067	.025	.032	.067	.014	.004	.063	.002
School grades	.116	.050	.068*	.102	.050	.059*	.110	.047	.064*
Two-parent household	.257	.131	.052	.263	.130	.054*	.216	.123	.044
Parent’s education	−.003	.028	−.003	.000	.028	.000	−.007	.026	−.007
Family conflict	.016	.009	.051	.011	.009	.033	−.003	.009	−.011
Victimization	.056	.015	.111***	.046	.015	.090**	.044	.014	.088**
Delinquent peers	.142	.011	.425***	.137	.011	.411***	.125	.010	.375***
Low self-control	.019	.005	.116***	.006	.006	.035	.006	.005	.036
Dark triad	—	—	—	.050	.011	.157***	.039	.010	.122***
Interaction	—	—	—	—	—	—	.008	.001	.287***
	R ² = .314			R ² = .329			R ² = .397
	N = 1,000			N = 1,000			N = 1,000

Note. OLS = ordinary least square.

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

Figure 2.

Interaction of self-control and Dark Triad on violent delinquency.

The findings presented in Table 3 show that youth high on DT traits are significantly more likely to engage in acts of interpersonal violence and that low self-control is not a necessary precondition (Cretacci, 2009). Indeed, these findings suggest that the effects of self-control may be upwardly biased if controls for malevolent personality characteristics are not included. However, as noted previously, low self-control may be more proximately related to behaviors that are comparatively less serious and may account for malevolent personality factors. We tested this proposition by utilizing a measure of drug behavior as an outcome variable. Drug use has been consistently related to impulsiveness and to low self-control (de Wit, 2009; Winfree & Bernat, 1998) and may occur independent of other character traits.

Table 4 shows the results related to drug use behavior. Model 1 shows that school grades (β = .08), single-parent households (β = .08), victimization experiences (β = .13), delinquent peers (β = .37), and low self-control (β = .14) were significantly associated with drug delinquency. In Model 2, we included the measure of the Dark Triad. Consistent with theoretical expectations, the measure of the DT was unrelated to the measure of drug behavior. Even so, the inclusion of the interaction term in Model 3 did reach statistical significance and was substantive in magnitude (β = .29). The results of this interaction are depicted in Figure 3.

Table 4.

OLS Regression of Independent Variables on Drug Delinquency.

Independent Variables	Model 1			Model 2			Model 3
Independent Variables	b	SE	β	b	SE	β	b	SE	β
Gender	.102	.125	.028	.080	.125	.022	.093	.118	.026
Grade level	.020	.091	.007	.009	.091	.003	−.029	.086	−.009
School grades	.180	.068	.078**	.174	.068	.075*	.185	.064	.080**
Two-parent household	.539	.179	.082**	.542	.179	.082**	.477	.169	.072**
Parent’s education	.006	.038	.005	.008	.038	.006	−.002	.036	−.001
Family conflict	.016	.012	.036	.013	.013	.030	−.006	.012	−.014
Victimization	.088	.021	.129***	.083	.021	.122***	.082	.020	.120***
Delinquent peers	.166	.014	.369***	.164	.014	.365***	.147	.014	.328***
Low self-control	.032	.007	.144***	.026	.008	.116**	.026	.007	.118***
Dark triad	—	—	—	.023	.015	.054	.008	.014	.018
Interaction	—	—	—	—	—	—	.011	.001	.292***
	R ² = .299			R ² = .301			R ² = .379
	N = 1,000			N = 1,000			N = 1,000

Note. OLS = ordinary least square.

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

Figure 3.

Interaction of self-control and Dark Triad on drug delinquency.

Discussion

Outside of criminology, research on individual traits and their connection to a variety of life outcomes is flourishing. Large-scale meta-analytic reviews, for example, consistently reveal robust connections between traits, personality factors, and a remarkably impressive list of life events and life outcomes (DeNeve & Cooper, 1998; Judge & Bono, 2001; Poropat, 2009; Roberts et al., 2007). Many of these studies, we note, also include assessments of the connection between personality constructs and antisocial behavior (Jones et al., 2011; Miller & Lynam, 2001; Miller, Lynam, & Jones, 2008). Collectively, these meta-analytic reviews provide ample evidence of a complex link between personality and criminal behavior. Yet as Jones and his colleagues (2011, p. 330) note, “With the possible exception of Gottfredson and Hirschi’s (1990) general theory, no major criminological theory incorporates personality.” Perhaps this is not surprising because criminology has a long, documented bias against individual-level explanations of crime. According to Andrews and Wormith (1989, p. 289) “studies of the psychology of crime—of individual differences (IDs) and of personality in particular—have been devalued within criminology for decades” (see also, Gibbons, 1986; Hirschi & Hindelang, 1977; Jones et al., 2011). Although exceptions exist, the general criminological reaction to individual-level theories, including theories rooted in biology, genetics, and rational choice, has ranged from the demure to the hypercritical (Burt & Simons, 2014; Carrier & Walby, 2014; Geis, 1994, 2000).

Gottfredson and Hirschi’s (1990) theory has been subject to an unusual amount of criminological criticism (Akers, 1991; Benson & Moore, 1992; Miller & Burack, 1993; see also, Hirschi & Gottfredson, 2008). Although part of this body of critical scholarship was aimed at fully appraising the logical inconsistencies of the theory, the measurement of the core construct, and the generalizability of self-control, another part was concerned about the close connection between self-control and personality (Arneklev, Grasmick, Tittle, & Bursik, 1993; Tittle, Ward, & Grasmick, 2003). Indeed, despite stating, “there is no personality trait disposing people toward crime” (Hirschi & Gottfredson, 1993, p. 49), numerous follow-on studies continued to conceptualize self-control as an individual difference rooted in personality. Over a decade later, Hirschi made the point more explicit. In their original conceptualization of self-control, he argued (2004, pp. 541–542), they “introduced a language I did not understand, championed ideas contradicting our theory, and otherwise muddied the waters. […] We can now see the errors introduced by our excursion into psychology” (see also, Jones et al., 2011).

Despite Hirschi’s protests, however, there is good reason to view self-control as an important personality trait. Doing so links criminology to the larger and more advanced fields of cognitive psychology and neuroscience—both of which have conducted experimental tests on the ability of individuals to resist emotional impulses (de Ridder et al., 2012; Lieberman, 2007), to deal with conflict and inhibit prepotent responses (Aharoni et al., 2013; Rueda, Posner, & Rothbart, 2005), and to take risks (Chein, Albert, O’Brien, Uckert, & Steinberg, 2011). Moreover, psychology and cognitive neuroscience pioneered the study of self-control and the broader constellation of brain-based executive functions (Bechara et al., 1995; Heatherton, 2011; Heatherton & Wagner, 2011). Clearly, Gottfredson and Hirschi’s (1990) concept of self-control is not orthogonal to psychological constructs that go by the same name or that deviate only slightly, such as effortful control (Eisenberg, Smith, & Spinrad, 2011). If scholars see a connection between Gottfredson and Hirschi’s (1990) original conceptualization of self-control and personality, it is simply because such a connection has been made explicit in a larger body of theory and research that predates their work and continues today.

Nonetheless, an unanticipated byproduct of the research on self-control may be a broader disciplinary recognition of the role that individual factors play in criminal behavior. Over the years, a small but steady stream of studies documenting the association between personality factors (Krueger, Caspi, Moffitt, White, & Stouthamer-Loeber, 1996; Krueger et al., 1994; Furnham & Thompson, 1991), physiological factors (Cauffman, Steinberg, & Piquero, 2005; Van Goozen, Fairchild, Snoek, & Harold, 2007), and biological and genetic factors (Arseneault et al., 2003; Ortiz & Raine, 2004; Raine, 2002; Rhee & Waldman, 2002) on crime and antisocial behavior have been published. Speaking broadly, these diverse studies converge to show that, at a minimum, criminologists ignore individual differences to their own peril.

Our study joins a growing list of empirical examinations into the influence of personality on self-reported problem behavior. Using data collected from a sample of Saudi Arabian high school students, we examined the joint influence of self-control and a relatively new personality construct, the Dark Triad, on delinquency. The Dark Triad is rooted in the realization that some individual personalities have a dark core. That is, individuals who are subclinically psychopathic, narcissistic, or Machiavellian, according to Furnham, Richards, and Paulhus (2013), engage in behaviors that are often more serious, more violent, and more instrumental than individuals who are simply impulsive or who lack these characteristics. Based in research on the Dark Triad, we hypothesized that an index of these interrelated personality measures would predict involvement in delinquency independent of levels of self-control, that scores on the Dark Triad would account for the influence of self-control on violent offending, and that the Dark Triad would be unrelated to other forms of offending—namely, drug use and distribution. We also hypothesized that self-control would interact significantly with the Dark Triad index.

Our results were supportive of each of these research hypotheses. Despite robust controls that share variance with delinquent involvement, namely, our measure of delinquent peers and self-reported victimization, we found that scores on the Dark Triad were predictive of delinquency independent of variation in self-control. We found that the Dark Triad accounted for the effects of self-control on serious, violent offending and that the interaction between the Dark Triad and the measure of self-control was not only statistically significant but was substantively stronger than either main effect. Lastly, as expected, we found no evidence that the Dark Triad exerted a significant main effect on drug use, although the interaction between self-control and the Dark Triad remained significant. Stated simply, individuals low in self-control may engage in behaviors that are impulsive and periodically dangerous, but those who are low in self-control and high in a dark core appear far more likely to engage in more crime and, more often, in more serious crime.

Understanding Malevolence

These results also raise substantive theoretical concerns. As we stated earlier, Gottfredson and Hirschi (1990) offer one view of criminal offenders. Their view is that offenders are impulsive opportunists who lack foresight and the ability to delay gratification. Their view is backed by a wide array of evidence. Yet another view of criminal offenders also exists. This view doesn’t deny the important roles of self-control and criminal opportunities but instead argues that a subgroup of offenders are significantly more cruel, are more sadistic, and are more malevolent in their treatment of others. For these individuals, aggression and violence, especially in more extreme forms, are part of a broader behavioral repertoire that can best be characterized as predatory. “Predatory violence,” notes Meloy (2006, p. 539), “is not preceded by autonomic arousal, is characterized by the absence of emotion and threat, and is cognitively planned.” Meloy’s distinction between affective violence and predatory violence parallel closely the theoretical distinctions in behavioral etiologies made here. Human predation involves strategizing and the weighing of alternative options, it involves goal exclusivity and the targeting of specific individuals or classes of individuals, such as women, and it often requires a substantial delay between the motive and the act. Meloy’s descriptions, which are rooted in anthropological and psychological research, provide a sharp contrast to the view of offenders offered by Gottfredson and Hirschi (1990) and broadly accepted by many criminologists.

In a similar way, research on psychopathy parallels our findings. In particular, psychometric analyses of Hare’s psychopathic checklist generally shows that psychopathy is characterized by two underlying factors (Hare et al., 1990; Harpur, Hare, & Hakstian, 1989) that are highly correlated and can be explained by a single, superordinate factor (Hare & Neumann, 2008). The first factor reflects the characterological traits commonly found in psychopaths, such as grandiosity, cunningness, emotional callousness, and superficial charm (Benning, Patrick, Hicks, Blonigen, & Krueger, 2003; Harpur, Hakstian, & Hare, 1988). These characteristics are similar to the items that compose the Dark Triad. The second factor reflects a lifestyle that is parasitic, impulsive, and chaotic. Again, this factor overlaps in strikingly similar ways to Gottfredson and Hirshci’s (1990) concept of low self-control.

The conceptual overlap between self-control and the Dark Triad suggests that the Dark Triad index reflects the traits closely aligned with psychopathy and that when combined with measures of self-control form a scale that parallels the factor structure associated with Hare’s psychopathy checklist (Glenn & Sellbom, 2015). This type of incidental convergence is unusual and suggests that the broader constellation of traits and lifestyle factors that characterize psychopathy can be effectively assessed by other means (Edens, Marcus, Lilienfeld, & Poythress, 2006). More importantly, however, incidental convergence strongly suggests that Gottfredson and Hirschi’s (1990) initial conception of self-control could also be brought under the broader theoretical construct of psychopathy. Self-control and psychopathy may indeed reflect a “unified theory of crime” described by DeLisi (2009). According to DeLisi (2009, p. 257), psychopathy “mirrors the elemental nature […] of antisocial behavior”—that is, the affective and lifestyle characteristics that define psychopathy correspond closely with criminal behavior over the life course (DeLisi & Vaughn, 2008; Vaughn & DeLisi, 2008). Moreover, DeLisi (2009) has argued that “the predictive validity of self-control [can be] subsumed by psychopathic traits, such as narcissism” (pp. 257–258; see also, Vaughn, DeLisi, Beaver, Wright, & Howard, 2007). Our results provide reasonable evidence of the convergence between self-control and the dark core of specific personalities and, we believe, represent a productive theoretical elaboration and extension of Gottfredson and Hirschi’s (1990) theory.

Future research should attempt to verify our findings using expanded measures of the DT, with samples more diverse in age, geography, offending levels, and in data that are longitudinal. Such investigations may benefit from an exploration of the potential mediating effects of delinquent peers and victimization. Furthermore, longitudinal assessments should also examine whether, like self-control, the DT exhibits stability over time and how this may impact intervention or treatment for delinquent youth (Hay & Forrest, 2006). These limits in our study obviously temper the generalizability of our results. However, the limitations of our sample and measures also constrained effects associated with the Dark Triad. Saudi youth in our sample were culturally homogenous, their base rates in offending were relatively low, and their lived experiences are highly circumscribed by Saudi and Islamic traditions and customs—customs that place a high premium on social conformity and customs that inflict harsh penalties on law breaking. Even so, our findings show that individual differences in self-control and the DT were detectable and differentiated youth across a range of offending domains. The substantive association between the DT index and problem behavior suggests a core group of malevolent offenders can be identified—even in samples limited in offending seriousness. With these insights in mind, future theoretical developments and elaborations should recognize meaningful differences between individuals in the offending population. Although some offenders may be prone to commit crime because they lack impulse control, overestimate rewards, and underestimate costs, other offenders are more motivated by malice, are comparatively more predatory, and are thus more malevolent. We suggest that it is time to recognize malevolence as a key feature of some offending behavior and encourage future research into the area.

Footnotes

Appendix A

3-Point scale (not true/sometimes true/often true)

“Please tell us how well the following statements describe you or your behavior.”

Modified PHDCN

I have trouble resisting temptation.

I often act on the spur of the moment.

I have self-control. (R)

I always like to make detailed plans before I do something. (R)

I like to do things that are fun even if they can get me into trouble.

I will try anything once.

I think school is a waste of time.

I try to do well at school. (R)

If I study hard, I will get good grades. (R)

Modified Grasmick

I often do whatever brings me pleasure here and now, even at the cost of some distant goal.

I frequently try to avoid projects that I know will be difficult.

When things get complicated, I tend to quit or withdraw.

The things in life that are the easiest to do bring me the most pleasure.

I like to test myself every now and then by doing something a little dangerous.

Sometimes I will take a risk just for the fun of it.

I sometimes find it exciting to do things for which I might get in trouble.

Excitement and adventure are more important to me than security.

I seem to have more energy and a greater need for activity than most other people of my age.

I try to look out for myself first, even if it means making things difficult for other people.

I’m not very sympathetic to other people when they are having problems.

If things I do upset people, it’s their problem, not mine.

I will try to get the things I want even when I know it’s causing problems for other people.

I lose my temper pretty easily.

Often, when I’m angry at people I feel more like hurting them than talking to them about why I am angry.

When I’m really angry, other people better stay away from me.

Dark Triad

I tend to manipulate others to get my way.

I tend to exploit others toward my own end.

I have used deceit or lied to get my way.

I have used flattery to get my way.

I tend to lack remorse.

I tend to be unconcerned with the morality of my actions.

I tend to be callous or insensitive.

I tend to be cynical.

I tend to want others to admire me.

I tend to want others to pay attention to me.

I tend to seek prestige or status.

I tend to expect special favors from others.

Appendix B

Table B1.

Correlation Matrix.

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13
(1) Gender	1
(2) Grade level	.422**	1
(3) School grades	.316**	.030	1
(4) Two-parent household	.015	–.039	.113**	1
(5) Parent’s education	.016	.044	.234**	.006	1
(6) Family conflict	.300**	.136**	.096**	.111**	–.062	1
(7) Victimization	.088**	.028	–.014	.097**	.023	.133**	1
(8) Delinquent peers	.330**	.083**	.127**	.046	.080*	.191**	.411**	1
(9) Low self-control	–.133**	–.067*	–.025	–.002	.070*	–.039	.303**	.288**	1
(10) Dark triad	.165**	.108**	.094**	.025	.037	.176**	.351**	.361**	.553**	1
(11) All delinquency	.203**	.058	.119**	.089**	.077*	.170**	.395**	.580**	.303**	.380**	1
(12) Violent delinquency	.181**	.062	.128**	.095**	.055	.158**	.332**	.526**	.266**	.368**	.866**	1
(13) Drug delinquency	.182**	.048	.143**	.124**	.064*	.144**	.339**	.495**	.282**	.311**	.824**	.646**	1

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

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under Grant no. 2-125-1434/2013. The authors, therefore, acknowledge with thanks DSR technical and financial support.

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