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The aim of this research was to examine centrality and redundancy of the Dark Tetrad traits (psychopathy, Machiavellianism, narcissism, and sadism) using network analysis. The first sample (N = 546) was assessed using a short instrument, the second (N = 404) and the third (N = 410) samples were assessed with full instruments for the first three dark traits, while for sadism the same instrument was used in all three studies. The results showed that psychopathy is the central feature across all networks, especially its facets which correspond to primary psychopathy or interpersonal manipulation and callousness. Narcissism seemed redundant when total scores of the dark traits were analyzed, but these results should be interpreted with caution given the small number of variables in the network. However, on the facet level, some 2 facets of psychopathy were redundant (secondary psychopathy or lack of cognitive responsiveness). These results reiterate the importance of psychopathy in the core of the dark traits and provide a deeper insight into the relations between the Dark Tetrad traits.
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Bojana M. Dinić
Department of Psychology, Faculty of Philosophy, University of Novi Sad, Serbia
Anja Wertag
Institute of Social Sciences Ivo Pilar, Zagreb, Croatia
Aleksandar Tomašević
Department of Sociology, Faculty of Philosophy, University of Novi Sad, Serbia
Valentina Sokolovska
Department of Sociology, Faculty of Philosophy, University of Novi Sad, Serbia
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Centrality and redundancy of the Dark Tetrad traits
The aim of this research was to examine centrality and redundancy of the Dark Tetrad traits
(psychopathy, Machiavellianism, narcissism, and sadism) using network analysis. The first
sample (N = 546) was assessed using a short instrument, the second (N = 404) and the third
(N = 410) samples were assessed with full instruments for the first three dark traits, while for
sadism the same instrument was used in all three studies. The results showed that psychopathy
is the central feature across all networks, especially its facets which correspond to primary
psychopathy or interpersonal manipulation and callousness. Narcissism seemed redundant
when total scores of the dark traits were analyzed, but these results should be interpreted with
caution given the small number of variables in the network. However, on the facet level, some
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facets of psychopathy were redundant (secondary psychopathy or lack of cognitive
responsiveness). These results reiterate the importance of psychopathy in the core of the dark
traits and provide a deeper insight into the relations between the Dark Tetrad traits.
Keywords: Dark Tetrad; Dark Triad; network analysis
1. Introduction
The Dark Triad includes three most prominent malevolent or dark personality traits –
Machiavellianism (characterized by cynical world view and a tendency towards
manipulation), psychopathy (characterized by callousness and impulsivity), and narcissism
(characterized by grandiosity, egocentrism and a sense of entitlement), while sadism
(characterized by enjoyment in cruelty) was later added as the fourth dark trait, constituting
the Dark Tetrad (Paulhus, 2014). Despite different notions on what the core of the dark traits
is, recent studies showed that the best candidates are Honesty-Humility from the HEXACO
personality model (Book et al., 2016) and two psychopathy facets – callousness and
manipulation (Jones & Figuredo, 2013; Marcus, Preszler, & Zeigler-Hill, 2018). However, the
dark traits also exhibit some specific relations with certain outcomes, with Machiavellianism
being exclusively related to long-term scheming, narcissism to ego-prompting outcomes,
psychopathy to antisocial behavior, and sadism to cruel behavior (Paulhus, 2014).
Given that there is a theoretical and empirical overlap between the dark traits, there are
debates on whether some of them are redundant. Namely, due to high overlap between
Machiavellianism and psychopathy, some authors consider that Machiavellianism, at least
measured with the existing measures such as Mach IV (Christie & Geis, 1970), is redundant
(e.g. McHoskey, Worzel, & Szyarto, 1998; Vize, Lynam, Collison, & Miller, 2018).
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However, other authors pointed out that the traits have different relations with some
outcomes, including sensitivity to provocation, tactics of manipulating, etc. (for details see
Koehn, Okan, & Jonason, 2018), which showed that these traits are divergent. Furthermore,
there are findings that psychopathy is the dominant malevolent trait, accounting for unique
variance in psychosocial outcomes (Muris, Merckelbach, Otgaar, & Meijer, 2017), and that
shared variance across the Dark Triad traits overpredicted psychopathy scores, whereas it
predicted variance in the other indicators only to a minimal degree (Glenn & Sellvom, 2015).
Moreover, when Machiavellianism and narcissism are examined on the residualized level
(with partialling out variance of psychopathy), they showed relatively few robust relations
with other constructs, compared to relations which they obtained on the bivariate level (Sleep,
Lynam, Hyatt, & Miller, 2017). Finally, Bertl, Pietschnig, Tran, Stieger, and Voracek (2017)
showed that a single Dark Core had a better model fit than the Dark Triad model with separate
traits, but also that callousness and manipulation, as the features of psychopathy, accounted
for 66% of the variance in the Dark Core. Addition of sadism did not change these results, i.e.
callousness and manipulation continued to have the main explanatory value of the Dark Core.
In the same line, some of the previous studies showed that sadism had negligible effect in
predicting morality (Jonason, Zeigler-Hill, & Okan, 2017), social motives (Jonason &
Zeigler-Hill, 2018), and utilitarian decisions (Karandikar, Kapoor, Fernandes, & Jonason,
2019) over the Dark Triad.
There have been some debates on the psychometric and statistical procedures used to
investigate the shared variance of the dark traits (for details, see Furnham, Richards, Rangel,
& Jones, 2014), and Sleep et al. (2017) pointed to the problems of using partial correlations
and residual scores in studying the overlapping variables such as the dark traits. Therefore, the
aim of this study was to explore centrality or the core trait of the Dark Tetrad along with
potential redundancy of the dark traits, using a novel approach to personality – network
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analysis. There have been only a few studies exploring the centrality of the dark traits. In the
first study, the Dark Tetrad traits were examined along with empathy, aggressiveness, and
impulsivity facets, and the analysis showed that psychopathy was the central trait, while
sadism was the most peripheral trait (Dinić & Wertag, 2017). The second study examined the
Dark Triad traits with spitefulness and aggression, indicating that some facets of psychopathy
(interpersonal manipulation and callousness) were the central features, while spitefulness
showed the highest redundancy (Marcus et al., 2018). Although centrality of the dark traits
was not the aim of the study conducted by Papageorgiou et al. (2019), this study investigated
network analysis of the Dark Triad and mental toughness. The results revealed a different
picture of the position of the dark traits and showed that narcissism is the most central dark
trait when prosocial traits were included into the network. These results suggested that
narcissism may act as a "bridge" between the prosocial and malevolent side of personality, but
they also questioned the inclusion of narcissism in the dark traits constellation. Since in Dinić
& Wertag (2017) the Dark Tetrad traits were examined along with other traits and in Marcus
et al. (2018) and Papageorgiou et al. (2019) sadism was not included, in this study we wanted
to examine centrality of the Dark Tetrad traits only, both on a trait and on a facet level. Given
the concerns that some of the dark traits largely overlap and are captured almost completely
by other dark traits (e.g. Vize et al., 2018) and considering the question whether sadism
should be included into the dark traits constellation (e.g. Bertl et sl., 2017; Jonason et al.,
2017), it is important to include all Dark Tetrad traits into analysis of redundancy.
Furthermore, since inclusion of other traits into the dark traits network could change the
centrality of the dark traits (e.g. Papageorgiou et al., 2019), this study included only the dark
traits. Moreover, instead of analysis on partial correlations applied in all previous studies that
used network analysis (Dinić & Wertag, 2017; Marcus et al., 2018; Papageorgiou et al.,
2019), where problems occurred when analyzing overlapping variables, we conducted
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analysis on zero-order correlations as suggested by Miller, Vize, Crowne, & Lynam (2019).
Furthermore, as the dark traits have different assessment approaches and measures (i.e.
independent instruments of all four traits and brief measures of the Dark Triad), we conducted
three studies using different instruments in order to gain insight into the consistency of
findings across the measurements. More precisely, we explored the Dark Tetrad network
based on the total score level as well as on the facet level. Consideration of
multidimensionality of the dark traits is especially important for psychopathy, given that only
its two facets (callousness and manipulation) and not all psychopathy facets, emerged as the
Dark Core (e.g. Marcus et al., 2018).
2. Method
2.1 Participants and Procedure
The study included three different samples from the general population from Serbia and all
participants were Caucasians (Table 1). Data from sample 3 represent part of the data
collected in the study by Dinić and Vujić (2018). In order to get a heterogeneous sample, each
student had to collect the data from a specific number of participants, based on given sex and
age quotas. For example, in sample 1 each student needed to collect data from 6 participants,
of which 3 were males (one should be 18-25 years of age, second 26-35 years of age, and
third 36 or older) and 3 females with the same instructions for age. Sex and age were chosen
for quotas given that these characteristics were strongly related to the dark traits (e.g., Carter,
Campbell, Muncer, & Carter, 2015), thus it is important that the samples were balanced
regarding these characteristics. Regardless of the given quotas, all samples were convenience
samples, thus examiners chose participants they are familiar with (family members, friends,
neighbors...). All measures were given in a paper-and-pencil form and participants completed
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the questionnaires at home in the presence of the examiner. The research was approved by the
Institutional Review Board and informed consent was obtained from each participant prior to
participating in the study.
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TABLE 1
2.2 Instruments
The instruments administered on sample 1 were the following two instruments: 1. Short Dark
Triad (SD3; Jones & Paulhus, 2014, for Serbian adaptation see Dinić, Petrović, & Jonason,
2018) which measures three dark traits, each per 9 items: Machiavellianism (α = .78),
psychopathy (α = .72), and narcissism (α = .69); 2. Short Sadistic Impulse Scale (SSIS;
O'Meara, Davies, & Hammound, 2011, for Serbian adaptation see Dinić, Bulut, Petrović, &
Wertag, 2019) which measures sadistic inclination (n = 10, α = .78).
The instruments administered on sample 2 were the following four instruments: 1. Mach IV
(Christie & Geis, 1970, for Serbian adaptation see Međedović & Petrović, 2015), which
measures Machiavellianism (n = 20, α = .77); 2. Levenson Self-Report Psychopathy Scale1
(LSRP; Levenson, Kiehl, & Fitzpatrick, 1995), which consists of 26 items (α = .87)
measuring primary psychopathy which refers to callousness, lack of remorse, and
manipulation (n = 16, α = .88) and secondary psychopathy which refers to impulsivity,
intolerance of frustration, quick-temperedness, and lack of long-term goals (n = 10, α = .67);
3. Narcissistic Personality Inventory (NPI: Raskin & Terry, 1988, for Serbian adaptation see
Dinić & Vujić, 2018), which measures grandiose narcissism (n = 40, α = .89). Although there
are many proposed scorings of NPI, the scoring selected for this study is the one proposed by
Ackerman et al. (2011), used in order to compare the results with a previous study related to
the dark traits network (Marcus et al., 2018). By this scoring system, only 25 out of 40 items
were used and three facets of narcissism could be distinguished: a. leadership/authority, which
refers to self-perceived leadership ability, social potency, and dominance (n = 11, α = .78); b.
1 To the best of our knowledge, this is the first use of LSRP in Serbian language. The model fit was excellent,
DWLSχ2(298) = 549.66, CFI = .96, TLI = .95, RMSEA = .05 (95% CI .04-.05), SRMR = .07).
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grandiose exhibitionism, which refers to self-absorption, vanity, superiority, and
exhibitionistic tendencies (n = 10, α = .74); c. entitlement/exploitativeness, which refers to
entitled beliefs and behaviors related to interpersonal contexts, such as a sense of deserving
respect and a willingness to manipulate and take advantage of others (n = 4, α = .53); 4. SSIS
(α = .86).
The instruments administered on sample 3 were the following four instruments: 1. Mach IV
(α = .74); 2. Psychopathic Personality Trait Scale (PPTS: Boduszek, Debowska, Dhingra, &
DeLisi, 2016, for Serbian adaptation see Dinić & Vujić, 2018; Međedović, Bulut, Savić, &
Đuričić, 2018), which comprises four facets of psychopathy – lack of affective responsiveness
(n = 5, α = .60), lack of cognitive responsiveness (n = 5, α = .60), interpersonal manipulation
(n = 5, α = .76), and egocentricity (n = 5, α = .50) with the total α = .74; 3. NPI, with the same
scoring method as in sample 2 (for leadership/authority α = .73, for grandiose exhibitionism α
= .76, and for entitlement/exploitativeness α = .52), with α = .87 on all 40 items; 4. SSIS
= .80).
A five–point Likert scale format was used for all instruments (from 1 = strongly disagree to 5
= strongly agree), except for NPI which has pairs of forced-choice items.
2. 3 Data analysis
The first step was calculation of zero-order correlations between all variables. It was followed
by network analysis performed to investigate the associations between variables within each
sample, while the analysis on sample 2 and 3 was performed on both total and facet scores.
Network analysis was applied to examine the complex pattern of relationships between
variables on the level of the global structure (or topology) of their interactions and the roles
played by the specific elements of the network (Constantini et al., 2015, 2019; Epskamp,
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Borsboom, & Fried, 2017). Compared to analyses aimed to detect a latent structure based on
covariance between variables, network analysis focuses on pairwise relationships between
observed variables and the structure of the emergent network of relationships.
A network consists of nodes, which represent observed variables, and edges connecting the
nodes and representing some form of statistical relationship which is estimated from the data.
The method of edge estimation used in this study was the zero-order correlations. The main
reason for choosing this method is related to the problem called "perils of partialling" detected
in the Dark Triad literature (e.g. Sleep et al., 2017). Namely, when multidimensional and
highly correlated constructs are being partialled, there are significant problems in drawing
conclusions about the nature of these constructs and their nomological networks, because
once the variance shared with other independent variables is removed, it is difficult to
interpret what construct is represented by the residualized variable. Another reason for using
the zero-order correlations is recent skepticism about the accuracy and replicability of the
partial correlation networks (Forbes et al., 2017; Stainley et al., 2017). Although there have
been recent developments in network analysis which prove that some of the criticism of these
methods is no longer viable (Borsboom et al., 2017; Epskamp et al., 2018), there are still
concerns that stronger inferences based on specific aspects of network structure (e.g. node
centrality) yield results with mixed consistency across different studies. Therefore, for each
estimated network, we performed a robustness check using both case-drop and non-
parametric bootstrapping methods with 95% CIs for all estimated network indices (Borsboom
et al., 2018; Epskamp et al., 2017). In this way we were be able to evaluate the consistency of
all inferences about key network indicators across different samples, instruments, and
estimation methods. The aim of our analysis was to identify the most important and the most
redundant nodes in all estimated networks. This was achieved by analyzing centrality and
clustering measures of all nodes. Centrality measures quantify the relative importance of a
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node in the context of the overall topology of the network. Closeness centrality indicates that
nodes are likely to be quickly affected by changes in another personality characteristic. On the
other hand, high betweenness centrality indicates that a node frequently lies on the shortest
path between other pair of nodes in the network, meaning that the removal of this node from
the network would lead to increased distances between other nodes in the network
(Constantini et al., 2015). Nodes with low centrality indices of both types are the nodes which
are not affected by changes in other nodes, nor is their removal significant for the overall
connectivity of the network.
Another network indicator is local clustering coefficient which can be seen as the tendency of
a node's neighbors to be directly connected to each other. A node that has a high clustering
coefficient is primarily connected to other nodes which are already directly related to each
other and thus centrality can be seen as a measure of local redundancy of a node (Constantini
et al., 2019). However, clustering must be interpreted and evaluated in relation to other
structural features in the network, and the strongest case for redundancy of a node can be
made if it has both low centrality measures and high clustering coefficient.
All networks, centrality, and clustering coefficients were estimated using R package "qgraph"
(Epskamp et al., 2012) and bootstrap robustness analysis was performed using "bootnet"
package (Epskamp et al., 2017). R code and data can be found at https://osf.io/gmnky/.
3. Results
3. 1 Correlations between the dark traits
The correlations between the dark traits were all significant, with the highest correlations
between psychopathy and Machiavellianism, and between psychopathy and sadism across all
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samples and used instruments (see Tables 2–4). On the facet level, the intensity of
correlations varied, with the highest correlations between Machiavellianism on the one hand,
and primary psychopathy (Table 3) or interpersonal manipulation (Table 4) on the other. It
should be noted that the correlation between two facets of psychopathy – interpersonal
manipulation and lack of cognitive responsiveness – was negative, although low (Table 4).
TABLES 2-4
3. 2 Network analysis
Bootstrap methods used to assess accuracy and stability of networks centrality (see Figure A
in Supplement) and edges (see Figure B in Supplement) showed robustness of these indices
obtained from SD3+SSIS and from the total scores of full-length instruments. In the case of
two networks based on the facet level, edge weights were robust, but the centrality measures
had wide CIs which is why further tests were used in order to determine differences between
the centrality of different nodes.
In the SD3+SSIS network on sample 1, the psychopathy-Machiavellianism and psychopathy-
sadism edges were the strongest edges, while narcissism-sadism edge was the weakest (Figure
1, top). Psychopathy is the central node in the network and serves as a mediator between most
of the other dark traits.
In the network based on the total scores on sample 2 (Figure 1, middle left), psychopathy-
Machiavellianism and psychopathy-sadism were again the strongest edges, while
Machiavellianism-sadism link was the weakest. Psychopathy was again the central node. On
the facet level on the same sample (Figure 1, middle right), primary psychopathy was the
central node and it formed the strongest edge with Machiavellianism. The edge between two
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facets from psychopathy was among the strongest, and both of them were highly connected
with sadism. It was noticed that narcissism facets formed a well-connected cohesive
substructure.
In the case of the network based on the total scores on sample 3, psychopathy was the central
node and psychopathy-Machiavellianism edge was the strongest. The edges narcissism-
Machiavellianism and narcissism-sadism were very weak (Figure 1, bottom left). On the facet
level, it could be noted that two facets of psychopathy – lack of affective and lack of cognitive
responsiveness – had a strong connection, while the facets interpersonal manipulation and
egocentricity were very loosely connected to the rest of their group (Figure 1, bottom right).
The central nodes were two facets of psychopathy interpersonal manipulation and lack of
affective responsiveness. Compared to the facets of psychopathy, the facets of narcissism
were more cohesive.
FIGURE 1
Since bootstrap robustness analysis showed wide CIs around most centrality indicators,
difference test (implemented in bootnet package) was applied in order to determine which
nodes significantly (p < .05) differ in their centrality from other nodes (see Figure C in
Supplement). In the case of the networks based on the total scores, there were no significant
differences in betweenness centrality, but according to closeness centrality psychopathy was
clearly the central node in all networks (Figure 2). This means that psychopathy is the
variable which is the most quickly affected by changes in other variables and vice versa.
However, no consistent conclusion can be made in relation to the least central or redundant
node. In sample 1, sadism and narcissism have identical – the lowest levels of closeness
centrality, in sample 2 no differences were found between sadism, narcissism and
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Machiavellianism, and only in sample 3 the results showed that narcissism is the redundant
node. Although the results were different across the samples, it could be noticed that
narcissism appeared in all three networks as the node with the lowest closeness centrality.
In the case of the network based on the facet level on sample 2, centrality indices showed that
the most central node was primary psychopathy, again only in terms of closeness centrality.
Grandiose exhibitionism, leadership/authority, sadism and secondary psychopathy had the
lowest values. In the case of the network based on the facet level on sample 3, centrality
indices showed that interpersonal manipulation, lack of affective responsiveness and
Machiavellianism were the most central nodes (Figure 2). The node with the lowest closeness
centrality was clearly a facet of psychopathy – lack of cognitive responsiveness.
FIGURE 2
Since the networks based on the total scores were small and dense, it is expected that the most
central node was also the most clustered one. However, when we take a look at the nodes with
low centrality, it can be noted that narcissism had consistently higher clustering coefficient
than, for example, sadism in the networks based on the total scores (Table 5). Given that in all
samples narcissism was among the nodes with the lowest levels of centrality (most evidently
in sample 3), high clustering of this node leads to the conclusion that narcissism is the
redundant node in these networks. However, the specifics of the relationships between the
dark traits are not conclusive from these small networks. The clustering coefficients from the
networks based on the facet level could provide a better insight into redundancy of these
nodes. In the case of sample 2, secondary psychopathy stands out with the highest clustering
coefficient among nodes with low centrality. Likewise, in case of sample 3, lack of cognitive
responsiveness is the node with the highest clustering coefficient. In the two networks on the
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facet level, Machiavellianism and sadism did not show consistently low levels of centrality
and high clustering.
To summarize, the central node in the network based on the total scores is psychopathy and
the redundant node is most likely narcissism. However, in each network on the facet level one
of the facets of psychopathy was identified as redundant (in sample 2 it is secondary
psychopathy and in sample 3 it is lack of cognitive responsiveness), while the others were
identified as some of the most important nodes (in sample 2 it is primary psychopathy and in
sample 3 interpersonal manipulation and lack of affective responsiveness).
TABLE 5
4. Discussion
The main aim of this study was to explore centrality and redundancy of the Dark Tetrad traits
using the network analysis approach, by which these positions of the dark traits could be
directly tested. The results on three samples showed that psychopathy or its facets were the
most central element of the Dark Tetrad network, which is in line with previous studies that
used the network analysis approach (Dinić & Wertag, 2017; Marcus et al., 2018). When
psychopathy was analyzed on the facet level, in the case of LSRP the central feature was
primary psychopathy, while in the case of PPTS the central features were interpersonal
manipulation and lack of affective responsiveness. The results are in line with previous
findings showing that features of Factor 1 psychopathy (manipulation and callousness) are the
core of the dark traits (Jones & Figuredo, 2013) or that callousness is a key feature of all four
dark traits (Paulhus, 2014). Moreover, the results contribute to the cross-cultural
generalization of previous findings on centrality of psychopathy facets not only among the
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dark traits constellation, but among psychopathy constellation as well. Thus, in more recent
studies (Preszler, Marcus, Edens, & McDermott, 2018; Verschuere et al., 2018),
callousness/lack of empathy characteristics emerged as the most central psychopathy trait in
network analysis of the Psychopathy Checklist-Revised (PCL-R; Hare, 2003) in both general
and forensic population.
The centrality of psychopathy and its facets does not necessarily mean redundancy of other
traits. Our results showed that other dark traits had strong mutual connections, besides
psychopathy as the central trait (for example, Machiavellianism and sadism). Results of low
centrality and high clustering coefficient could lead to the conclusion about the redundancy of
some traits. In the networks based on the total scores, narcissism was the only dark trait
showing consistently low centrality and high clustering coefficients, which sets narcissism as
a candidate for a redundant node. These results stand in contrast to the previous study which
showed that narcissism was the most central dark trait, but in the network with prosocial traits
(Papageorgiou et al., 2019). Thus, when only dark traits are analyzed, narcissism seems
redundant, but it may have the mediating role in connecting prosocial and malevolent
characteristics. However, since these networks have only four nodes and difference tests
based on bootstrapped centrality measures did not consistently show that narcissism is clearly
the node with the lowest centrality, the conclusion about redundancy should be taken with
caution.
In the network based on the facet level on sample 2, secondary psychopathy emerged as a
redundant node, while on sample 3 another facet of psychopathy – lack of cognitive
responsiveness – emerged as redundant. Different redundant facets of psychopathy across the
samples reflect the difference in two psychopathy instruments. Both measures are based on
Cleckey's (1941) conceptualization of psychopathy. However, LSRP fits Hare's (1991) model
of psychopathy and differentiates between primary (Factor 1) and secondary (Factor 2)
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psychopathy, while in PPTS the items referring to antisocial and impulsive behaviors are
omitted and other aspects of psychopathy are included (such as egocentricity). Although there
is disagreement over whether antisocial and criminal behaviors, aligned in secondary
psychopathy, should be part of psychopathy (e.g. Neuman, Vitacco, Hare, & Wypperman,
2005) or not (e.g. Cooke, Michie, Hart, & Clark, 2004), it is certain that this component is not
the central component of psychopathy. Our results confirmed that secondary psychopathy is
redundant in the context of the Dark Core as well as deficits in recognizing others people's
emotions. This is in line with general agreement that the affective-emotional deficits are
central characteristics of psychopathy (see Skeem, Polaschek, Patrick, & Lilienfeld, 2011),
and the findings that psychopathy is linked more to the deficits in affective empathy than the
deficits in cognitive empathy and recognizing emotions (e.g. Blair, 2005; Mullins-Nelson,
Salekin, & Leistico, 2006; Baron-Cohen, 2011). Furthermore, Međedović et al. (2018)
showed that the lack of cognitive responsiveness from PPTS should not be considered as an
indicator of psychopathy but as its correlate.
In all networks, Machiavellianism and sadism had a role in bringing together other members
of the Dark Tetrad and in the maintenance of the network coherence. For example, in the
networks based on the facet level in sample 3, both Machiavellianism and sadism had a role in
bringing together the facets of psychopathy, and they were well connected to the other nodes
in the networks. Thus, Machiavellianism and sadism showed uniqueness among the Dark
Tetrad traits and do not seem to be redundant.
Although the results of this study are compelling, there are certain limitations that need to be
addressed. First, instead of a common measure of psychopathy – Self-Report Psychopathy
Scale (SPR; Paulhus, Neumman, & Hare, 2009), PPTS and LSRP were used. PPTS focuses
only on psychopathic traits and, unlike SRP, it does not include indicators of antisocial
behavior. On the other hand, LSRP is based on PCL-R, just like SRP, and it includes
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secondary psychopathy which is linked to antisocial traits and behaviors (e.g. Miller,
Gaughan, & Pryor, 2008). Second, some of the scales had lower alpha coefficient (e.g.
egocentricity), but considering the small number of items per scale, alphas were adequate.
Third, Machiavellianism and sadism were not represented on the facet level. However, the
most commonly used measures for assessing these traits either do not offer facets (SSIS) or
there are some difficulties regarding the number and nature of the facets (Mach IV, see Panitz,
1989), so the total scores are widely used. In future studies, other measures which consider
multidimensionality of the dark traits should be also included, such as Five Factor
Machiavellianism Inventory (Collison, Vize, Miller, & Lynam, 2018). Moreover, it would be
useful to replicate the findings on samples with higher levels of the dark traits (i.e. clinical
and incarnated samples), in order to gain a better insight into the structural organization of the
traits. Likewise, replication on a larger sample would be useful due to wide CIs on
bootstrapped network centrality measures in the present study.
This study contributes to the existing literature primarily by using network analysis as a novel
approach and by using different instruments of the dark traits on three different samples. In
sum, the results of this study consistently showed that psychopathy is the most central element
of the Dark Tetrad network, reiterating the previous findings that psychopathy is the core of
the dark traits. However, facets of psychopathy are very diverse and while the facets including
manipulation and callousness were central, others referring to antisocial behaviors and lack of
recognizing emotions seemed redundant. This finding could be particularly useful for
researchers interested in the Dark Core, as our results suggest that secondary psychopathy as
well as indicators of lack of cognitive empathy could be excluded from the assessment tools.
Moreover, the results indicated that sadism and Machiavellianism play a significant role in the
Dark Tetrad network, while the status of narcissism depends of the hierarchical level of the
traits used in analysis. These findings are potentially important given the concerns that sadism
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does not show significant incremental contribution to the dark traits constellation (e.g.
Jonason et al., 2017) or that narcissism does not fit well in the Dark Triad and forms a
separate, independent factor (e.g. Rogoza & Cieciuch, 2018).
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25
Table 1
Sample characteristics
Characteristics Sample 1 = 546 Sample 2 = 404 Sample 3 = 410
Men 50.2% 49.5% 50.0%
Age range 18-45 20-76 18-79
M(SD) 25.62(7.22) 34.59(11.95) 39.92(14.06)
Education elementary or high
school graduate
26.9% 32.2% 40.0%
university students 51.5% 29% 37.3%
college or
university degree
21.6% 38.8% 22.7%
26
Table 2
Zero-order correlations between dark traits in SD3+SSIS network (sample 1, N = 546)
Machiavellianism psychopathy narcissism M(SD)
Machiavellianis
m
1
2.97(0.61)
psychopathy .49 1 2.12(0.55)
narcissism .37 .37 1 2.85(0.53)
sadism .35 .47 .18 1.51(0.44)
Note. All correlations are significant at p < .001. Score range is from 1 to 5.
27
Table 3
Zero-order correlations between dark traits in full-length instruments network (sample 2, N =
404)
M P primary P secondary P N L
A
G
E
EE M(SD)
Machiavellianism 1 2.80(0.47)
psychopathy .6
2
1 2.23(0.51)
primary .6
6
.87 1 2.12(0.65)
secondary .3
7
.82 .43 1 2.34(0.56)
narcissism .4
3
.45 .54 .20 1 0.31(0.19)
LA .3
7
.32 .43 .09 .88 1 0.35(0.26)
GE .3
2
.37 .41 .20 .78 .55 1 0.28(0.24)
EE .4
1
.52 .50 .37 .63 .48 .42 1 0.23(0.27)
sadism .3
4
.56 .51 .43 .35 .26 .25 .3
6
1.36(0.55)
Note. M = Machiavellianism, P = psychopathy, N = narcissism, LA = leadership/authority,
GE = grandiose exhibitionism, EE = entitlement/exploitativeness. All correlations ≥ .20
significant at p < .001. Score range is from 1 to 5 for all measures except for narcissism, in
which case it is from 0 to 1.
28
Table 4
Zero-order correlations between dark traits in full-length instruments network (sample 3, N =
410)
M P lack
CR
lack
AR
Man Eg
o
N L
A
G
E
EE M(SD)
Machiavellianis
m
1 2.90(0.45)
psychopathy .5
1
1 2.47(0.45)
lack CR .2
1
.50 1 2.24(0.62)
lack AR .3
6
.75 .40 1 2.16(0.69)
Man .4
1
.71 -.02 .28 1 2.50(0.89)
Ego .2
9
.59 .01 .26 .36 1 2.98(0.56)
narcissism .2
4
.37 -.06 .24 .43 .25 1 0.18(0.12)
LA .1
7
.26 -.14 .23 .32 .19 .87 1 0.35(0.25)
GE .1
9
.31 -.02 .14 .38 .23 .83 .49 1 0.27(0.24)
EE .2
6
.34 .07 .22 .35 .18 .62 .40 .39 1 0.21(0.26)
sadism .4
5
.44 .16 .35 .37 .22 .21 .19 .12 .2
3
1.62(0.57)
Note. M = Machiavellianism, P = psychopathy, lack CR = lack of cognitive responsiveness,
lack AR = lack of affective responsiveness, Man = interpersonal manipulation, Ego =
egocentricity, N = narcissism, LA = leadership/authority, GE = grandiose exhibitionism, EE =
29
entitlement/exploitativeness. All correlations ≥ .16 are significant at p < .001. Score range is
from 1 to 5.
30
Table 5
Centralized Zhang clustering coefficients
Machiavellianism psychopathy narcissism sadism
SD3+SSIS
(sample 1, N = 546)
-0.46 -1.19 0.93 0.71
Full instruments: total
score level
(sample 2, N = 404)
-0.04 -1.40 0.78 0.66
Full instruments: facet
level (sample 2, N = 404)
-0.10 Primary = -1.85 LA = 0.49 0.42
Secondary = 1.26 GE = 0.42
EE = -0.62
Full instruments: total
score level
(sample 3, N = 410)
-0.35 -1.12 1.25 0.22
Full instruments: facet
level
(sample 3, N = 410)
-0.83 lackCR = 1.00 LA = -0.46 0.05
lackAR = -1.80 GE = 0.68
Man = -0.43 EE = 0.35
Ego = 1.43
Note. lackCR = lack of cognitive responsiveness, lackAR = lack of affective responsiveness,
Man = interpersonal manipulation, Ego = egocentricity, LA = leadership/authority, GE =
grandiose exhibitionism, EE = entitlement/exploitativeness.
SD3+SSIS (sample 1 = 546)
Full-length instruments (sample 2 = 404)
31
Figure 1 Networks of dark traits.
Note. M = Machiavellianism, P = psychopathy, N = narcissism, S = sadism, lackCR = lack of
cognitive responsiveness, lackAR = lack of affective responsiveness, Man = interpersonal
manipulation, Ego = egocentricity, LA = leadership/authority, GE = grandiose exhibitionism,
EE = entitlement/exploitativeness, PP = primary psychopathy, SP = secondary psychopathy.
Full-length instruments (sample 3 = 410)
32
33
Figure 2 Betweenness and closeness centrality measures.
SD3+SSIS (sample 1 = 546)
Full-length instruments (sample 2 = 404)
Full-length instruments (sample 3 = 410)
34
Note. M = Machiavellianism, P = psychopathy, N = narcissism, S = sadism, lackCR = lack of
cognitive responsiveness, lackAR = lack of affective responsiveness, Man = interpersonal
manipulation, Ego = egocentricity, LA = leadership/authority, GE = grandiose exhibitionism,
EE = entitlement/exploitativeness, PP = primary psychopathy, SP = secondary psychopathy.
Bootstrap CIs are highlighted.
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With this meta-analytic review, we aimed to estimate the relationship that sadistic personality has with the Dark Triad traits and, secondarily, describe the research on the Dark Tetrad traits. We searched for articles in the following databases, PsycARTICLES, PsycINFO, PubMed, ScienceDirect, SCOPUS, and Web of Science, where we found 128 articles to qualitatively evaluate and 103 articles to quantitatively analyze. Sadism correlated with narcissism (r = 0.26), Machiavellianism (r = 0.43), and psychopathy (r = 0.58). The most common themes across the studies were: (a) structural aspects of the Dark Tetrad; (b) online behavior; (c) aggressiveness; (d) moral beliefs and behavior; (e) video games; (f) sexual behavior, and (g) emotional functioning. The Dark Tetrad traits correlated with several dysfunctional behaviors and socially maladaptive outcomes. Finally, sadism is potentially more similar to psychopathy and Machiavellianism, than narcissism.
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The Dark Tetrad refers to a cluster of four socially aversive and undesirable personality traits: narcissism, Machiavellianism, psychopathy, and sadism. The main aim of the present study was to validate the recently developed Short Dark Tetrad (SD4) scale among a sample of young adults (N=429, M=22.11 years, SD=3.35, range=18-42) from Portugal, composed of men (n=192, M=22.14 years, SD=3.34, range=18-35) and women (n=237, M=22.08 years, SD=3.35, range=18-42). Results revealed that the expected four-factor latent structure of the SD4 obtained an adequate fit. The four factors mostly presented positive moderate significant intercorrelations, and adequate to good reliability. The four subscales showed distinctive correlates with other measures (e.g., low self-control, suppression of aggression, anxiety) and variables (e.g., delinquency acts, substance abuse). Strong cross-gender measurement invariance was demonstrated, with men scoring significantly higher than women on the Narcissism, Machiavellianism, Psychopathy, and Sadism subscales. The current findings support the use of the SD4 in Portuguese.
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Recent studies of socially aversive (negative) personality traits have focused on the expansion of different concepts and models. As a result, there emerged the Dark Tetrad personality model (which includes Machiavellianism, subclinical psychopathy, narcissism, and sadism). The paper provides a review of current works on the Dark Tetrad of personality. According to recent research, everyday sadism is a personality trait characterized by a tendency to purposefully humiliate people, causing physical, sexual or psychological suffering for the sake of pleasure. Similar manifestations of everyday sadism and the Dark Triad are antisocial behavior in everyday life and on the Internet. Everyday sadism is the best predictor of various features: deviant behavior in adolescents, affective and cognitive empathy, unprovoked aggression, bullying, cyberbullying, and counterproductive work behavior. Sadism and psychopathy have the «darkest» properties. In general, the results of the studies demonstrate that (1) sadism leads to greater stability of the Dark Tetrad as a complex of personality traits, (2) all of the «dark» properties overlap empirically and theoretically, and (3) the Dark Core is described by empathy deficit (callousness) and manipulativeness rather than other characteristics (e.g. Factor 1 of psychopathy).
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This comprehensive review summarizes and evaluates the present state of the Dark Triad research literature (or more broadly, the dark personality trait literature), and as such serves both a pedagogical purpose, by providing an introduction or primer on the dark personality literature and a scientific purpose by directing future research on key issues that still have not been sufficiently addressed. In this review, we discuss and critique current operational conceptualizations of what it means for a personality trait to be classified as ‘dark’. Also discussed is the Dark Core, as well as quantitative issues such as limitations of commonly used statistical treatments, such as multivariate analyses, bifactor modeling, and composite measures, and proposed solutions to some of these issues. Based on a comprehensive and critical appraisal of the literature, future directions are suggested to drive the dark trait field towards a more organized, parsimonious, and productive future.
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The aim of this study was to evaluate psychometric properties of three sadism scales: Short Sadistic Impulse Scale (SSIS), Varieties of Sadistic Tendencies (VAST, which measures direct and vicarious sadism), and Assessment of Sadistic Personality (ASP). Sample included 443 participants (50.1% men) from the general population. Reliability based on internal consistency of all scales was good, and results of Confirmatory Factor Analysis (CFA) showed that all three scales had acceptable fit indices for the proposed structure. Results of Item Response Theory (IRT) analysis showed that all three scales had higher measurement precision (information) in above-average scores. Validity of the scales was supported through moderate to high positive correlations with the Dark Triad traits, especially psychopathy, as well as positive correlations with aggressiveness and negative with Honesty-Humility. Moreover, results of hierarchical regression analysis showed that all three measures of direct, but not vicarious sadism, contributed significantly above and beyond other Dark Triad traits to the prediction of increased positive attitudes toward dangerous social groups. The profile similarity index showed that the SSIS and the ASP were highly overlapping, while vicarious sadism seems distinct from other sadism scales.
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Objective: We employed the network methodology to explore the connections between the Dark Triad (DT) traits with Mental Toughness (MT) and the degree to which they account for perceived stress beyond the Big Five (B5). Method: Network analyses were undertaken to explore connections between the DT, MT and perceived stress, independently in two samples, and in the combined dataset; and whether B5 factors are responsible for the connections that emerged in the original network. Results: DT and MT traits improved the prediction of perceived stress above the B5. Furthermore, narcissism occupied a strategic position in the network acting as a bridge between prosocial and “dark” sides of personality. The pattern of network connections could not be explained by B5 traits alone. Conclusions: The results suggest that there is more to personality than what can be captured by the B5 and that broadening the domain of personality beyond the B5 can improve the prediction of important outcomes, such as perceived stress. Narcissism is a unique trait and studying its connection with MT may be the key to moving forward from a dichotomous way of perceiving personality traits, as beneficial or malevolent, to focusing on a dynamic continuum of personality. Keywords: Dark Triad, Mental Toughness, Big Five, Perceived Stress, Network Analysis.
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Since its introduction in 2002, Dark Triad (DT) research– the simultaneous study of psychopathy, narcissism, and Machiavellianism – has exploded, with the publication of hundreds of peer reviewed articles, books and chapters, as well as coverage by the lay media. Unfortunately, there are several limitations to this research that are unrecognized or ignored. These limitations include 1) the treatment of DT constructs as unidimensional contrary to evidence for their multidimensionality, 2) the indistinctness between current measures of Machiavellianism and psychopathy, 3) the use of multivariate statistical approaches that pose statistical and interpretive difficulties, 4) failure to test DT relations directly against one another, and 5) methodological limitations related to convenience sampling and reliance on mono-method approaches. We discuss these problems in detail and describe solutions that can result in a more robust, replicable, and meaningful literature moving forward.
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Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. We argue that fixed-margin sampling cannot be used for this purpose, as it generates data under a particular null-hypothesis: a unidimensional factor model with interchangeable indicators (i.e., the Rasch model). We show this by discussing relevant psychometric literature and by performing simulation studies. Results indicate that while eLasso correctly estimated network models and estimated almost no edges due to chance, fixed-margin sampling performed poorly in classifying true effects as "interesting" (Steinley et al. 2017, p. 1004). Further simulation studies indicate that fixed-margin sampling offers a powerful method for highlighting local misfit from the Rasch model, but performs only moderately in identifying global departures from the Rasch model. We conclude that fixed-margin sampling is not up to the task of assessing if results from estimated Ising models or other multivariate psychometric models are due to chance.
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The objective of this research was to validate the Narcissistic Personality Inventory across different response formats, given that several factor structures were proposed, ranging from two to seven factors. The original forced-choice format of the Narcissistic Personality Inventory was given to 410 participants and a modified, i.e., Likert format was given to 423 participants from the general population, along with personality and other narcissism measures. The results showed that the five-factor model proposed by Ackerman et al. had the best model fit in both response formats and that a distinction between adaptive (Leadership, Vanity, and Superiority) and some aspects of maladaptive (Manipulativeness and Exhibitionism) narcissism factors could be established. However, the redundancy of items in certain factors could be problematic and further improvements of the Narcissistic Personality Inventory should include more indicators of some proposed factors, especially of Vanity.
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Machiavellianism is characterized by planfulness, the ability to delay gratification, and interpersonal antagonism (i.e., manipulativeness and callousness). Although its theoretically positive relations with facets of Conscientiousness should help distinguish Machiavellianism from psychopathy, current measurements of Machiavellianism are indistinguishable from those of psychopathy in large part because of their assessment of low Conscientiousness. The goal of the present study was to create a measure of Machiavellianism that is more in line with theory using an expert-derived profile based on the 30 facets of the five-factor model (FFM) and then test the validity of that measure by comparing it with relevant constructs. Previously collected expert ratings of the prototypical Machiavellian individual on FFM facets yielded a profile of 13 facets including low Agreeableness and high Conscientiousness. Items were written to represent each facet, resulting in a 201-item Five Factor Machiavellianism Inventory (FFMI). Across 2 studies, with a total of 710 participants recruited via Mechanical Turk, the FFMI was reduced to its final 52-item form and was shown to relate as expected to measures of Big Five personality traits, current Machiavellianism measures, psychopathy, narcissism, ambition, and impulsivity. The FFMI is a promising alternative Machiavellianism measure.
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We conducted three studies to examine the psychometric properties of the Serbian translations of the Dark Triad Dirty Dozen (Study 1, N = 364) and the Short Dark Triad (Study 2, N = 409), as well as their convergent and discriminant validity in relation to basic HEXACO personality traits and empathy (Study 3, N = 443). The three-factor structure, convergent validity, and discriminant validity were confirmed for both instruments. The main correlates of the traits, from both instruments, were low Honesty-Humility and lack of affective empathy. Also, alpha coefficients for scale scores were satisfactory and scale information was good, with more precision in above-average levels of trait for some of the scales (e.g., psychopathy). Both instruments are recommended to be used in further research.
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A useful way of understanding personality traits is to examine the motivational nature of a trait because motives drive behaviors and influence attitudes. In two cross-sectional, self-report studies (N = 942), we examined the relationships between fundamental social motives and dark personality traits (i.e., narcissism, psychopathy, sadism, spitefulness, and Machiavellianism) and examined the role of childhood socio-ecological conditions (Study 2 only). For example, we found that Machiavellianism and psychopathy were negatively associated with motivations that involved developing and maintaining good relationships with others. Sex differences in the darker aspects of personality were a function of, at least in part, fundamental social motives such as the desire for status. Fundamental social motives mediated the associations that childhood socio-ecological conditions had with the darker aspects of personality. Our results showed how motivational tendencies in men and women may provide insights into alternative life history strategies reflected in dark personality traits.
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We examined (N = 355; 250 women) how the Dark Tetrad traits (i.e., psychopathy, narcissism, Machiavellianism, and sadism) are associated with moral dilemmas and Moral Foundations. The Dark Triad traits were associated with utilitarian decision-making on moral dilemmas. Sadism did not provide incremental variance above the Dark Triad traits in accounting for responses to moral dilemmas. Compromised morality explained higher dilemma scores, beyond the Dark Tetrad traits. Therefore, we suggest that compromised moral values within dark personalities result in higher utilitarian decision-making. Men had darker personalities and were more utilitarian than women were, while women were more moral than men. Subsequently, men made more utilitarian decisions as compared to women, which may be a result of their darker personalities and lower concerns for moral values. Collectively, our results add to the discussion about the need to expand the Dark Triad to include sadism and the role of personality in understanding individual differences, morality, and moral decision-making.