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Several impulsivity-related models have been applied to understanding the vulnerability to addiction. While there is a growing consensus that impulsivity is multifaceted, debate continues as to the precise number of facets and, more critically, which are most relevant to explaining the addiction-risk profile. In many ways, the current debate mirrors that which took place in the personality literature in the early 1990s (e.g., Eysenck's 'Big Three' versus Costa and McCrae's 'Big Five'). Indeed, many elements of this debate are relevant to the current discussion of the role of impulsivity in addictive behavior. Specifically, 1) the use of factor analysis as an atheoretical 'truth-grinding machine'; 2) whether additional facets add explanatory power over fewer; 3) the delineation of specific neurocognitive pathways from each facet to addictive behaviors, and; 4) the relative merit of 'top-down' versus 'bottom-up' approaches to the understanding of impulsivity. Ultimately, the utility of any model of impulsivity and addiction lies in its heuristic value and ability to integrate evidence from different levels of analysis. Here, we make the case that theoretically-driven, bottom-up models proposing two factors deliver the optimal balance of explanatory power, parsimony, and integration of evidence.
Impulsivity: Four ways five factors are not basic to addiction
* Matthew J. Gullo a, Natalie J. Loxton a,b, and Sharon Dawe c
aCentre for Youth Substance Abuse Research, The University of Queensland, K Floor, Mental
Health Centre, Royal Brisbane and Women’s Hospital, Herston, Queensland 4006, Australia.
bSchool of Psychology, The University of Queensland, St Lucia, Queensland 4072, Australia.
cSchool of Applied Psychology, Griffith University, Mt. Gravatt Campus, Brisbane, Queensland
4122, Australia.
*Corresponding author. Tel.: +61-7-3365-5465; fax: +61-7-3365-5488.
Email address:
This is the Preprint version of an accepted journal article. Please cite as: Gullo, M. J., Loxton, N. J., &
Dawe, S. (2014). Impulsivity: Four ways five factors are not basic to addiction. Addictive Behaviors.
Several impulsivity-related models have been applied to understanding the vulnerability to
addiction. While there is a growing consensus that impulsivity is multifaceted, debate continues
as to the precise number of facets and, more critically, which are most relevant to explaining the
addiction-risk profile. In many ways, the current debate mirrors that which took place in the
personality literature (e.g., Eysenck’s ‘Big Three’ versus Costa and McCrae’s ‘Big Five’).
Indeed, many elements of this debate are relevant to the current discussion of the role of
impulsivity in addictive behavior. Specifically, 1) the use of factor analysis as an atheoretical
‘truth-grinding machine’; 2) whether additional facets add explanatory power over fewer; 3) the
delineation of specific neurocognitive pathways from each facet to addictive behaviors, and; 4)
the relative merit of ‘top-downversus ‘bottom-up’ approaches to the understanding of
impulsivity. Ultimately, the utility of any model of impulsivity and addiction lies in its heuristic
value and ability to integrate evidence from different levels of analysis. Here, we make the case
that theoretically-driven, bottom-up models proposing two factors deliver the optimal balance of
explanatory power, parsimony, and integration of evidence.
Keywords: impulsivity, addiction, substance use, alcohol, urgency, UPPS
1. Introduction
Impulsivity, whether measured by self-report, observer-report, or behavioral
performance, is a robust predictor of current and future problems with substance use (Dawe &
Loxton, 2004; Jentsch & Taylor, 1999; Moeller et al., 2001; Moffitt et al., 2011; Nigg et al.,
2006; Potenza, 2013; Tarter et al., 2003). In children, its association with future substance use
remains even after controlling for other markers of risk, including low IQ, socioeconomic status,
and parental history of substance dependence (Moffitt et al., 2011; Nigg et al., 2006; Tarter et al.,
2003). Not surprisingly, the construct is of great interest to addiction scientists.
In addiction science, there is an emerging consensus that impulsive drug use involves two
core processes observable at the neurophysiological, behavioral, cognitive, and trait. The first
involves a heightened propensity or impulse to approach drugs and the second involves a
reduced capacity to inhibit this approach behavior. The summary presented in Table 1 highlights
the considerable overlap of different theoretical models in the importance placed on these two
fundamental processes that have been derived from multiple researchers across diverse
methodological investigations.
-----------------------------INSERT TABLE 1 HERE-----------------------------
Whilst a two-factor model is attractive in its parsimony, other researchers have proposed
that a more useful way to consider impulsivity is to develop a more nuanced delineation of
subtypes. This would have important implications for addiction science. In an attempt to “bring
order to the myriad of measures and conceptions of impulsivity”, Whiteside and Lynam (2001, p.
684) drew upon the Five Factor Model of human personality (Costa & McCrae, 1992; Goldberg,
1993) as a framework for conceptualizing impulsivity. Employing factor analysis of self-report
data, they constructed the four-factor UPPS impulsivity questionnaire consisting of: Urgency,
(lack of) Premeditation, (lack of) Perseverance, and Sensation seeking. Subsequently, Cyders
and colleagues (2007) argued that the UPPS model was incomplete, in that it did not incorporate
impulsive behavior arising from positive mood states. They proposed individual differences in
this tendency were important to consider in understanding risky behavior such as alcohol abuse,
and used factor analysis to derive an additional scale to measure the construct. Thus, the Urgency
subscale was renamed Negative Urgency and a new scale added, Positive Urgency. We refer to
this extended model as the UPPS+P model.
Notably, UPPS Sensation Seeking and (lack of) Premeditation align somewhat with the
core processes previously implicated in impulsive substance use, and impulsivity theories more
generally (Table 1). However, as the authors themselves note, “(lack of) perseverance, like
urgency, is not well represented in other measures of impulsivity” (Whiteside & Lynam, 2001, p.
685). The same could be said of Positive Urgency (Cyders et al., 2007). In debating the
importance of these newly constructed impulsivity traits, the field finds itself in a situation
strikingly similar to that which took place in the personality literature. In particular, the debate
between Costa and McCrae (1992) and Eysenck (1992) in which the former argued that there
were four main lines of evidence to support the five-factor model of personality. Eysenck’s reply
argued against each of the proposed lines of evidence and concluded with a strong call for a
science of personality based on theoretical predictions firmly rooted in biological processes.
Many of the issues raised during the personality debate are relevant for addiction
researchers studying impulsivity. Specifically, 1) the use of factor analysis as an atheoretical
‘truth-grinding machine; 2) whether additional facets of a construct add explanatory power over
fewer; 3) the delineation of specific neurocognitive pathways from each facet to addictive
behavior, and; 4) the relative merit of ‘top-downversus ‘bottom-up’ approaches to the
understanding of impulsivity and the integration of experimental evidence. Each of these issues
will be discussed, in turn, with reference to current research into impulsivity and substance
abuse. It is hoped that this will stimulate further refinements to the understanding impulsivity
and highlight the importance of theoretical integration across fields.
2. Factor analysis is not a ‘truth-grinding machine
The UPPS and UPPS+P are models of impulsivity borne of factor analysis. Using this
statistical technique, Whiteside and Lynam (2001) set out to distil the numerous
conceptualizations of impulsivity into core facets common across measures. The Five Factor
Model of personality, itself a product of factor analysis, was used as the framework within which
to ‘anchor’ these facets within personality more broadly. It should be noted, however, that only
three of the Big Five were included as anchors, those considered by the authors as most relevant
to impulsivity (Extraversion, Neuroticism, and Conscientiousness). While factor analysis is an
extraordinarily useful method of data reduction, it possesses significant shortcomings that limit
its value in theory construction (Block, 1995; Eysenck, 1992).
One important limitation to factor analysis is its vulnerability to ‘prestructuring (Block,
1995). That is, that the number and nature of the factors derived depend on the variables included
in the factor analysis. This can occur regardless of whether the selection was guided by theory or
practical constraints. There is clear evidence of prestructuring in the construction of the UPPS
and UPPS+P. After constructing the UPPS scales, Whiteside and Lynam (2001, Table 7, p. 684)
conducted another factor analysis and found that the new UPPS Urgency scale loaded with all
NEO-PI-R Neuroticism subscales, the UPPS Sensation Seeking scale loaded with all NEO-PI-R
Extraversion subscales, and both UPPS (Lack of) Premeditation and UPPS (Lack of)
Perseverance scales loaded together with all NEO-PI-R Conscientiousness subscales. That is, the
four new UPPS scales loaded onto the three factors initially taken from the Big Five and used as
anchors. This same three-factor structure was later replicated by Smith et al. (2007). Thus, the
inclusion of the three Big Five ‘anchor’ traits might have prestructured the UPPS. This could
explain why its factor structure differed from previous factor analytic studies finding a two-
factor structure (for a review, see Dawe & Loxton, 2004), and why it ‘missed’ Positive Urgency
(Cyders et al., 2007).
The primary shortcoming of factor analysis is that there is no unequivocal basis for
deciding on the number of factors to extract from the data or on the best approach to rotating
them for interpretation (Block, 1995). The history of personality psychology provides a clear
example of this. Costa and McCrae (1992) argued for their Big Five traits of Extraversion,
Neuroticism, Openness to Experience, Conscientiousness, and Agreeableness as forming the
basic structure of personality. By contrast, Eysenck argued the case for his Big Three traits of
Extraversion, Neuroticism, and Psychoticism. The first two traits in each model are closely
aligned. However, Eysenck (1992) argued that Agreeableness and Conscientiousness were too
closely related to be considered distinct, and considered them to be subcomponents of his higher-
order Psychoticism trait. However, he made the point that the subjectivity of factor analysis is
such that there was no psychometric reason for preferring his conceptualization of these traits to
any other. How high a correlation is too high for a given pair of variables to be considered
distinct (or too low to be considered the same)? There is no clear answer to this and,
consequently, no clear consensus emerged on the structure of personality, nor could it through
factor analysis.
Factor analysis is not an objective, ‘truth-grinding’ machine (Meehl, 1992). What you get
out of it is determined by what you put into it. This is why two (Dawe & Loxton, 2004), three
(Carver & White, 1994), four (Whiteside & Lynam, 2001), and five factor (Cyders et al., 2007)
models of impulsivity can emerge from factor analysis, just as it did with personality before it
(Markon, Krueger, & Watson, 2005). Factor analysis, like any tool, is best utilized when it is
constrained by strong theory and a drive for parsimony. Biology provides a strong constraint on
theorizing. As Eysenck (1992, p. 672) argued, “we need to anchor our dimensions of
personality in something more concrete than the morass of factor analysis, and biology
supplies us with the necessary tools.” This argument applies equally to impulsivity when
subjected to factor analysis.
Practically, the addiction researcher is interested in the predictive value of the new
impulsivity facets in understanding substance use. The UPPS+P dimensions of Sensation
Seeking and (Lack of) Premeditation align closely with existing theories of impulsivity
(Whiteside & Lynam, 2001). Of interest is the utility of the three newer facets. The key question
being, does a five-factor conceptualization of impulsivity improve the understanding of addictive
behavior over a more parsimonious, theoretically-driven two-factor account?
2. Ockham's razor: Do additional traits increase explanatory power?
Prior to considering the evidence for additional facets of impulsivity it is worth
considering whether a two-factor model provides additional explanatory power over and above a
single factor. The relationship between measures tapping into reward sensitivity and substance
use is well-established (e.g., Dissabandara et al., in press; Franken & Muris, 2006; Gullo &
Dawe, 2008; Kabbani & Kambouropoulos, 2012; Kambouropoulos & Staiger, 2004; Knyazev,
Slobodskaya, Kharchenko, & Wilson, 2004; Loxton & Dawe, 2001; Lyvers, Czerczyk, Follent,
& Lodge, 2009; Lyvers, Duff, & Hasking, 2011; O’Connor & Colder, 2005; Pardo, Aguilar,
Molinuevo, & Torrubia, 2007; Smerdon & Francis, 2011). So, too, is the relationship between
measures tapping into disinhibition and substance use (e.g., George, Connor, Gullo, & Young,
2010; Howard, Kivlahan, & Walker, 1997; Moffitt et al., 2011; Tarter et al., 2003; Verdejo-
García, Lawrence, & Clark, 2008; Wills, Windle, & Cleary, 1998). However, the key issue is
whether there is evidence that both constructs add unique variance to the prediction of key
aspects of the addiction profile. This has been a research question addressed in recent studies
examining the unique contribution of two impulsivity-related traits.
Quinn and Harden (2013) found changes in (rash) Impulsivity predicted alcohol,
marijuana and cigarette use in adolescence/young adulthood, whereas Sensation Seeking was
only predictive of alcohol use. Also using a large, longitudinal dataset, Handley et al. (2011)
found (rash) Impulsivity to uniquely predict externalizing problems (ADHD and conduct
disorder), while Sensation Seeking uniquely predicted substance use. Castellanos-Ryan, Rubia
and Conrod (2011) similarly found Sensation Seeking and a reward response bias were uniquely
associated with binge-drinking in adolescents, whereas (rash) Impulsivity and deficits in
response inhibition were associated with conduct disorder. Generally, these studies point to
Sensation Seeking as associated with alcohol use, and Impulsivity/disinhibition associated with
more problematic use, behavioral undercontrol, and conduct problems.
Similarly, studies that have tested the two-factor model proposed by Dawe and Loxton
(2004) have found Reward Sensitivity/Drive and Rash Impulsiveness to be uniquely associated
with different drug use behavior and drug-related cognitions in adult and adolescent samples
(Dissabandara et al., 2013; Egan, Kambouropoulos, & Staiger, 2010; S. M. George et al., 2010;
Gullo, Dawe, Kambouropoulos, Staiger, & Jackson, 2010; Gullo, Ward, Dawe, Powell, &
Jackson, 2011; Kabbani & Kambouropoulos, 2013; Loxton et al., 2008; Lyvers, Duff, Basch, &
Edwards, 2012). Generally, while both traits are associated with drug use and hazardous
drinking, Reward Sensitivity has been consistently associated with earlier age of drug use and
positive drinking expectancies. Whereas, Rash Impulsiveness tends to be uniquely associated
with high-risk substance use, such as poly-substance use, higher drug dose, cross-border use and
reduced treatment seeking. Cognitively, Rash Impulsiveness is associated with perceived
impaired control and lower drinking refusal self-efficacy.
This leads to the question as to whether additional variance above and beyond these two-
factor models of impulsivity is accounted for by the additional UPPS+P traits. UPPS Sensation
Seeking and (Lack of) Premeditation can be regarded as overlapping with other measures
tapping reward sensitivity and disinhibition, respectively. However, an important caveat
regarding Sensation Seeking is that, despite measuring a tendency to pursue activities that are
exciting and rewarding, these scales typically also measure one’s openness to trying new
experiences that may or may not be dangerous” (p. 686, Whiteside & Lynam, 2001). This latter
aspect of the trait is separate from reward sensitivity and more closely relates to disinhibition,
resembling Zuckerman’s Sensation Seeking and “rash” impulsiveness (Carlson, Pritchard, &
Dominelli, 2013; Dawe & Loxton, 2004; Zuckerman & Kuhlman, 2000). Therefore, while
Sensation Seeking and Reward Sensitivity are not the same, they differ from (rash) Impulsivity
in a similar way (see Table 1). This underscores the importance of multivariate analyses that
examine unique variance.
Stautz and Cooper (2013) reviewed an extensive literature examining the relationship
between UPPS+P traits and alcohol consumption/problems in adolescents. They also included
Reward Sensitivity as a separate trait. Generally, they found all impulsivity-related traits were
associated with drinking, with Sensation Seeking and Positive Urgency showing the largest
correlations with alcohol consumption, and Positive and Negative Urgency showing strongest
relationships with problematic use. Coskunpinar, Dir, and Cyders (in press) conducted a similar
meta-analysis, but did not limit their focus to adolescents. They too found all UPPS+P traits were
significantly associated with alcohol use, but found (Lack of) Perseverance (rather than
Sensation Seeking) to be most strongly associated with alcohol consumption. Sensation Seeking
was more strongly correlated with binge drinking, while (Lack of) Premeditation, Negative and
Positive Urgency were more strongly associated with alcohol problems and dependence.
It should be noted that, in addition to the UPPS+P scales, both meta-analyses included
studies containing measures believed to be tapping similar constructs to those included in
Whiteside and Lynam (2001) and Cyders et al.’s (2007) questionnaires. However, there was
some inconsistency in the selection and classification of appropriate measures between the two
groups of researchers. For instance, the Impulsiveness scale from the Karolinska Scales of
Personality was included as a measure of (Lack of) Premeditation by Stautz and Cooper (2013),
but not Coskunpinar et al. (in press). Such classifications are understandably difficult, as most
measures were never intended to provide clear distinctions between five facets of impulsivity.
While both meta-analytic studies provide an important contribution to the literature,
neither can speak to the true explanatory value of UPPS+P traits, due to the often sizable overlap
between scales (correlations as high as .73 and .76; Carlson et al., 2013; Stojek & Fischer, 2013).
A clearer indication of their additive value comes from analyses that examine only the unique
variance in substance use accounted for by each trait, as in multiple regression. A number of
studies that have investigated the UPPS+P traits do not do this. In fact, studies of impulsivity and
substance use do not commonly do this (see Gullo et al., 2011, for a discussion). A summary of
studies that have explored the unique role UPPS+P traits in substance use is presented in Table 2.
This summary was limited to only those that administered the UPPS or UPPS+P questionnaire,
given the lack of consensus in classifying past impulsivity measures within the UPPS
framework, and the lack of any alternative Positive Urgency scale.
-----------------------------INSERT TABLE 2 HERE-----------------------------
As shown in Table 2, there was no study in which all five UPPS+P traits made a unique
contribution to addictive behavior. For instance, Adams, Kaiser, Lynam, Charnigo, and Milich
(2012) found that (Lack of) Premeditation, Sensation Seeking, and Negative Urgency each made
a unique contribution to problematic drinking in college students. These contributions were of
approximately equal magnitude. Other studies tend to find only one or two impulsivity traits to
contribute significantly to alcohol use/problems in college drinkers (usually [Lack of]
Premeditation and Negative Urgency). Two clinical studies that examined the unique
contribution of UPPS traits failed to find any that acted as unique predictors of drinking
problems (Verdejo-García, Bechara, Recknor, & Pérez-Gara, 2007; Whiteside, Lynam, Miller,
& Reynolds, 2005). However, Negative Urgency was a unique predictor of drug use. Of the five
traits, Negative Urgency was one of the most consistent predictors of substance use in non-
clinical samples. The majority of studies reviewed in Table 2, though, are cross-sectional.
Therefore, it is possible that Negative Urgency’s unique association with substance use is not
causal, but rather an effect of the negative consequences of heavy, problematic substance use
(Hicks, Durbin, Blonigen, Iacono, & McGue, 2011; Zuckerman & Kuhlman, 2000). The findings
of prospective studies can help to answer the question of temporal precedence.
Four studies have examined the unique prospective relationships between UPPS+P and
substance use. Cyders, Flory, Rainer, and Smith (2009), Zapolski et al. (2009) and Stojek and
Fischer (2013) recruited large samples of mostly female college students. Cyders et al. found that
Positive Urgency uniquely predicted increases in drinking quantity and alcohol problems over a
(approximately) 9-month period, while Sensation Seeking uniquely predicted increases in
drinking frequency. Analyzing a subset of this sample, Zapolski et al. found that Positive
Urgency also uniquely predicted future increases in illegal drug use. In contrast, Stojek and
Fischer found that only (Lack of) Premeditation uniquely predicted the development of alcohol
dependence symptoms over a (approximately) 4-month period. However, in those already
exhibiting dependence symptoms at Time 1, both (Lack of) Premeditation and Negative Urgency
predicted the exacerbation of alcohol dependence. Simons, Dvorak, Batien, and Wray (2010)
conducted a daily diary study to track the drinking habits of 102 moderate/heavy drinking
college students over 3 weeks. They found that (Lack of) Premeditation predicted greater
intoxication over the 3-week period while, unexpectedly, Positive Urgency predicted less. When
predicting symptoms of acute dependence, no UPPS+P trait was significant after controlling for
intoxication. It should be noted that this study did not analyze data from the Sensation Seeking
While limited to the findings of four studies, the evidence suggests that Negative
Urgency may not play a key role in the prediction of early problems with alcohol. Indeed, Stojek
and Fischer’s (2013) results suggest that it plays a more prominent role in the escalation of
problem drinking after dependence symptoms have begun to emerge. That is, increases in
negative affect stemming from the negative consequences of heavy drinking serve to further
increase the risk of those who already display high Lack of Premeditation. Future longitudinal
studies on at-risk drinkers are required to further test this ‘escalation’ hypothesis.
Among cross-sectional and longitudinal studies that have examined unique effects, the
UPPS+P traits consistently associated with substance use appear to be (Lack of) Premeditation
and Negative Urgency. The (Lack of) Premeditation trait is most similar to the (rash)
impulsivity/disinhibition traits typically found in substance use studies. Negative Urgency is
unique. It would appear that the core issue for this trait is whether the propensity to engage in
rash action during heightened negative affect is meaningfully distinct from a general propensity
to engage in rash action. Indeed, much of the association between Neuroticism and substance use
disorders stems from its overlap with trait disinhibition (Chassin, Fora, & King, 2004). In a
substantial meta-analysis of studies investigating personality traits and anxiety, depressive and
substance use disorders, Kotov, Gamez, Schmidt and Watson (2010) found elevated levels of
Neuroticism across all diagnostic groups; although less so for substance use disorders. Notably,
there was a substantial association between trait disinhibition and substance use disorders even
after controlling for Neuroticism. Thus, it is possible that Negative Urgency, a measure derived
in part from the Impulsiveness subscale of Neuroticism (Whiteside & Lynam, 2001), provides an
opportunity to test the combined risk of high Neuroticism and high disinhibition.
Another core issue for the UPPS+P model is the extent to which Sensation Seeking
adequately taps reward sensitivity. Carlson et al. (2013) noted recently that the UPPS+P under-
represents reward sensitivity in relation to externalizing behavior. They tested the unique
contributions of reward (and punishment) sensitivity and UPPS+P to disinhibited behavior
(substance use and antisocial behavior) in 282 undergraduate students. Controlling for age and
gender, the UPPS+P scales accounted for 21% of disinhibited behavior, with (Lack of)
Premeditation and Sensation Seeking the only unique predictors. However, Reward Sensitivity
accounted for significant additional variance over this (3%). Although this study did not separate
substance use from other delinquent behavior, it gives some support to the notion that reward
sensitivity may not be fully captured by the UPPS+P. The potential importance of reward
sensitivity has been recently raised by Smith, Guller and Zapolski (2013) who stated:
a crucial next challenge in this domain of clinical science is to identify what factors
influence the tendency, by some, to engage primarily in externalizing behaviors while
others engage primarily in internalizing behaviors. One possibility is that, separate from
individual differences in the tendency to respond reflexively to emotion, there are
individual differences in incentive or reward sensitivity. (p. 7)
Given the importance of reward sensitivity and incentive sensitization processes in the
neurobiology of addictive behavior, this would seem particularly indicated (Dawe & Loxton,
2004; de Wit & Richards, 2004; Koob & Volkow, 2010; Robinson & Berridge, 2003).
3. Neurocognitive pathways linking impulsivity facets to addictive behavior
Neurobiological models of addiction vulnerability highlight the importance of two
interrelated neural processes: heightened incentive salience arising from the limbic impulsive”
system and impaired response inhibition arising from the prefrontal executive system (see
Table 1). All drugs of abuse (directly or indirectly) activate the mesolimbic dopamine system,
with the nucleus accumbens playing a critical role in their acute reinforcing effects (Koob &
Volkow, 2010). Repeated self-administration results in sensitization of these mesolimbic
dopamine neurons, which further increases the salience of the drug and drug-associated stimuli,
producing a heightened sense of “wanting” and appetitive motivation (Robinson & Berridge,
2003). Whether or not this impulse leads to approach behavior depends, in part, on prefrontal
inhibitory control mechanisms that include the orbitofrontal cortex (OFC), anterior cingulate
cortex (ACC), insula, and inferior frontal cortex (Goldstein & Volkow, 2002; Jentsch & Taylor,
1999; Koob & Volkow, 2010; Swick, Ashley, & Turken, 2011; Whelan et al., 2012).
While both of these core vulnerabilities were once thought to result exclusively from
repeated drug use, growing evidence of pre-existing individual differences has suggested
otherwise (Dawe, Gullo, & Loxton, 2004). Biologically-based models of personality emphasize
the importance of natural variation in the functioning of both the mesolimbic dopamine system
(reward sensitivity) and prefrontal cortex (inhibitory control) in trait” impulsivity (Barratt,
1972; Cloninger, 1987; Depue & Collins, 1999; Eysenck, 1993; Gray, 1970; Zuckerman, 1991).
Such differences, considered to be largely genetic in origin, were theorized to place individuals
at heightened risk for externalizing problems, including substance abuse (Cloninger, 1987; Gray,
1994; Zuckerman, 1991). Indeed, self-report measures of Reward Sensitivity traits have been
shown to predict reward-related activity in the mesolimbic system and stronger craving for
alcohol (Beaver et al., 2006; Costumero et al., in press; Franken, 2002; Hahn et al., 2009;
Kambouropoulos & Staiger, 2001). Self-report measures of Rash Impulsiveness traits have been
shown to predict lower grey matter volume in the OFC and ACC (Matsuo et al., 2009), as well as
lower ventral prefrontal cortex (PFC) activity during response inhibition (Brown, Manuck, Flory,
& Hariri, 2006). These findings provide evidence linking biologically-based impulsivity traits to
the predicted variations in core addictive processes.
High Rash Impulsiveness and poor inhibitory control are familial vulnerability traits that
predate drug abuse (Ersche et al., 2012; Ersche, Turton, Pradhan, Bullmore, & Robbins, 2010;
Ridenour et al., 2009; Tarter, Kirisci, Habeych, Reynolds, & Vanyukov, 2004). Stop-Signal
Reaction Time (SSRT) scores derived from performance on the Stop-Signal Task (Logan,
Schachar, & Tannock, 1997) are one of the most commonly used indices to assess response
inhibition. Ersche et al. (2012) found that white matter connectivity in the inferior PFC was
related to SSRT and risk for stimulant dependence, suggesting it may serve as a neurocognitive
endophenotype for addiction. These findings are consistent with early reports from the
longitudinal IMAGEN project, in which 1,896 14-year olds completed the Stop-Signal Task (and
others) during functional magnetic resonance imaging (fMRI; Whelan et al., 2012). Whelan et al.
(2012) identified a right-hemisphere PFC network comprising the inferior frontal gyrus, insula,
and ACC that was significantly associated with both successful response inhibition and
adolescent substance use. Reduced inhibition-related OFC activation was also a key predictor of
substance misuse in the sample. This is consistent with Ersche et al. (2012), who found reduced
grey matter in the OFC and increased grey matter in the striatum differentiated stimulant-
dependent individuals from non-dependent siblings (Volkow & Baler, 2012).
However, it is important not to oversimplify the distinction made between the
neurophysiological and behavioral components of Reward Sensitivity and Rash Impulsiveness.
Neurological and behavioral processes underlying each trait do not operate in isolation and, as
with self-report measures of the traits, would be expected to overlap and show some correlation
(Gullo & Dawe, 2008). The OFC and striatum are densely interconnected and previous studies
have linked OFC activity with the functioning of striatal areas (Lehéricy et al., 2004).
Specifically, reduced OFC activity is associated with fewer dopamine D2 receptors in the
striatum (Volkow et al., 2006). Given the robust association between reduced striatal D2 receptor
availability and substance dependence, this OFC-striatum link may reflect an important neural
mechanism for the top-down regulation of limbic reward processing and approach motivation
(Koob & Volkow, 2010). In support of this hypothesis, Volkow et al. (2006) reported higher-
than-normal striatal D2 receptor availability in non-dependent members of alcohol-dependent
families, which was correlated with greater OFC metabolism.
The interconnectedness between components has also been observed at the behavioral
level. Padmala and Pessoa (2010) experimentally “impaired” Stop-Signal response inhibition in
otherwise healthy adults simply by rewarding correct go” approach responses on the task. Not
only was inhibition impaired, but participants displayed a similar pattern of reduced activity in
the inferior frontal gyrus and other regions previously observed in addicted populations.
Therefore, functional deficits intop-down cognitive control regions can be produced solely by
increasing the incentive value of approach stimuli and “bottom-up” dysregulation. There are two
important implications here: 1) abnormalities in one domain of impulsivity could manifest in
processes considered to belong to another domain, and 2) given this, no domain of impulsivity
should be studied in isolation without controlling for the other (at any level of analysis). This
underscores the importance of examining the unique contributions of impulsivity facets to
addictive behavior.
It is clear from the above discussion that the neurobehavioral processes underlying
Reward Sensitivity and Rash Impulsiveness play important and distinct roles in the vulnerability
to addiction (see also Dawe et al., 2004; Gullo & Dawe, 2008). Furthermore, such findings might
apply equally to UPPS Sensation Seeking and (Lack of) Premeditation, respectively, given their
overlap with Reward Sensitivity and Rash Impulsiveness traits. With that in mind, what unique
contributions do the other UPPS+P traits make to neurobehavioral processes underlying
addictive behavior?
Clark et al. (2012) reported lower D2/D3 receptor binding in the striatum of pathological
gamblers high in Negative or Positive Urgency. This suggests a potential role in incentive
sensitization and appetitive motivational processes, similar to Reward Sensitivity. However, no
relationship between Urgency traits and D2/D3 receptor binding was found in healthy controls,
nor was there an overall group difference between gamblers and controls in receptor binding.
Analyses also did not control for the 57% shared variance between the Urgency traits (or the
overlap with Reward Sensitivity, which was not measured). Therefore, it is not clear whether this
association is specific to either trait, or reflects a non-specific marker of vulnerability.
Moreno-Lopez et al. (2012) investigated the relationship between UPPS+P traits and
brain volume in 38 cocaine-dependent individuals and 38 matched controls. Cocaine users were
found to have significantly lower grey matter volume in areas that included the OFC, right
inferior frontal gyrus, right insula, left amygdala, and caudate. Higher Lack of Premeditation
scores were associated with less grey matter in the right insula and left putamen in cocaine users,
but not in controls. Unexpectedly, greater Lack of Premeditation was associated with more grey
matter in the left inferior frontal gyrus in cocaine users, but less grey matter in controls. Also
unexpected was the correlation between higher Negative Urgency and more grey matter in left
middle frontal gyrus and right sub-gyral region in cocaine users. However, Negative Urgency did
correlate with grey matter volume in the expected direction in these regions amongst controls.
No significant associations emerged between the UPPS+P traits and white matter volume.
Boy et al. (2011) found that only Negative Urgency correlated with lower GABA
concentrations in the dorsolateral PFC, an inhibitory neurotransmitter. This could represent a
unique mechanism of risk for the trait. However, it is also possible that this association reflects
the negative affect component of the trait, independent of one’s general propensity to engage in
rash action. Indeed, Bielau et al. (2007) reported a higher concentration of dorsolateral PFC
GABA neurons in patients with major depression, compared to healthy controls and those with
bipolar disorder. It should also be noted that neither Negative Urgency nor dorsolateral PFC
GABA levels were related to response inhibition as indexed by SSRT. While this suggests the
association may be more related to negative affectivity than impulsivity per se, the association is
worthy of further study.
Xue, Lu, Levin, and Bechara (2010) experimentally manipulated prior risk experiences to
increase risky decision-making on a gambling task. They found that the increase in risky
decision-making was positively correlated with insular activation. Furthermore, Negative
Urgency scores were positively related to insular activity, although not risky decision-making
Joseph, Liu, Jiang, Lynam, and Kelly (2009) examined the unique contribution of UPPS
traits to neural processes underlying autonomic arousal and emotion regulation. They presented
emotionally arousing stimuli to high (n = 20) and low (n = 20) sensation seekers whilst
undergoing fMRI in order to investigate neural correlates of autonomic arousal and emotional
regulation. They also tested the additive value of UPPS traits in predicting signal differences
detected between the groups. As expected, high sensation seekers showed stronger activation in
regions associated with autonomic arousal (right insula), whereas regions associated with
emotional regulation (anterior medial OFC and left ACC) were more strongly activated in low
sensation seekers. Over-and-above the Sensation Seeking effects, high Negative Urgency was
associated with lower activation in emotion regulation regions among low sensation seekers, as
expected. However, this was not specific to negative stimuli, but applied equally to arousing
stimuli of positive and negative valence. High Negative Urgency was also associated with lower
activation in arousal regions among high sensation seekers, contrary to expectation. That is,
while controlling for Sensation Seeking, Negative Urgency predicted less activation in emotional
control regions, but also less activation in arousal regions. No other UPPS traits contributed
significantly to the prediction of neural activity over Sensation Seeking.
In summary, there are inconsistent relationships between UPPS+P traits and
neurophysiological processes involved in addiction and impulsivity. However, it is important to
note that few neuroimaging studies have been conducted using the UPPS+P scales and most that
have done so did not examine unique associations. Thus, the inconsistency in findings may be
the result of a poor signal-to-noise ratio when examining individual scales in isolation. Closer
examination of unique relationships in future studies is therefore recommended. Future research
would also be assisted by further theoretical development of the underlying mechanisms of
UPPS+P traits. In particular, predictions that specify the neurophysiological processes unique to
each trait. Cyders and Smith (2008) have proposed that variations in an amygdala-OFC circuit
underlie individual differences in Urgency traits. However, they make no predictions concerning
how the neurobiological basis of Positive Urgency differs from that of Negative Urgency, which
it must if they are separate, normally-distributed personality traits uniquely involved in addictive
4. The relative merit of ‘top-down’ versus ‘bottom-up’ approaches to understanding
In the long run, any account of behaviour which does not agree with the knowledge of
the nervous and endocrine system which has been gained through the direct study of
physiology must be wrong- Jeffrey A. Gray (from The psychology of fear and stress
[1987; 2nd ed.], p. 241).
It is clear from the above discussion that the lack of theoretical integration with other
lines of research is a major obstacle for UPPS+P going forward. Whilst research to-date has
failed to support unique contributions of the five traits to substance use, it is not entirely clear
what contributions were expected in the first place. For instance, what aspect of substance use
should be predicted by (Lack of) Perseverance but not (Lack of) Premeditation? Stronger theory
and closer integration with existing models could assist here. Much is already known about the
neurobiology of addiction and impulsive behavior, and this can both inform and constrain
theorizing at ‘higher’ trait levels.
For instance, Koob and Volkow (2010) identify a Withdrawal/Negative Affect stage in
the addiction cycle. During this stage, withdrawal-related negative affect engages the extended
amygdala and negative reinforcement-related drug-seeking. This can begin prior to the
development of substance dependence. Recent evidence from rodent studies suggests that
increased binge drinking causes dysregulation of GABA interneurons in the medial PFC and
reduces the brain region’s functional connectivity with the amygdala, leading to deficits in
executive control over behavior (O. George et al., 2012). Given that individual differences in
Negative Urgency have been theorized to reflect variations in an OFC-amygdala circuit (Cyders
& Smith, 2008) and have been empirically linked to prefrontal GABA levels (Boy et al., 2011), it
is possible that individuals high in Negative Urgency may be uniquely vulnerable to
neuroadaptations during the Withdrawal/Negative Affect stage. This prediction would not only
be in keeping with Stojek and Fischer’s (2013) ‘escalation’ findings, but also suggest an
alternative mechanism underlying it: that the unique role of Negative Urgency in substance
abuse is vulnerability to more significant neuroadaptations subsequent to binge drinking.
Interestingly, George et al. did not observe a general increase in anxiety-like behavior,
suggesting that these neuroadaptations did not increase general negative affectivity (i.e.,
Neuroticism). Of course, the amygdala is involved in more than just negative affect and the
critical question is whether Negative Urgency uniquely predicts vulnerability to these
neuroadaptations and negative reinforcement processes over-and-above general disinhibition,
reward sensitivity, and Neuroticism in human beings. Regardless, this demonstrates the potential
of a ‘bottom-up’ integration of findings to enrich the theory underlying UPPS+P.
The divergence of the UPPS+P from existing models of impulsivity speaks to the relative
merit of ‘top-down’ theory construction that is based on self-report data and factor analysis, as
opposed to a ‘bottom-up’ approach based on neurophysiological and behavioral data. Eysenck,
Barratt, Cloninger, Gray, and Zuckerman all developed their theories (and self-report scales)
with a close eye on biological data. Their ‘impulsivity’ traits focus primarily on reward
sensitivity and general (dis)inhibitory processes, which align well with core dysfunctions
observed in addiction. How might such models, and those summarized in Table 1, more
parsimoniously account for the role of negative affect and urgency? That is, without the addition
of a new trait? Basically, by arguing that impulsive behavior in times of high negative affect still
operates via these same two processes (Gullo & Dawe, 2008). Negative affect sensitizes
mesolimbic reward pathways and active avoidance behavior, which is still approach behavior
mediated by the reward system, not the avoidance/anxiety system (Gray & McNaughton, 2000;
Koob & Le Moal, 2001; Zuckerman & Kuhlman, 2000). Zuckerman and Kuhlman (2000) further
argued that elevated levels of anxiety and Neuroticism observed in substance abusers can be
accounted for by the consequences of drug-taking, and are not causes of it. This is a more
parsimonious explanation for the findings presented in Table 2 concerning Negative Urgency, as
well as other longitudinal findings from different scales (Chassin et al., 2004; Sher, Grekin, &
Williams, 2005).
In summary, impulsivity is a core vulnerability to addictive behavior. However, five
factors are not basic for addiction. There is broad agreement across different levels of analysis
that traits related to reward sensitivity and disinhibition play an important and unique role in
addictive behavior. These processes are reflected, to varying degrees, in the UPPS+P traits of
Sensation Seeking and (Lack of) Premeditation. However, it is likely that UPPS+P Sensation
Seeking does not fully capture individual differences in reward sensitivity. Regardless, these
traits are not unique to UPPS+P and appear in many models of impulsivity and addiction.
Negative Urgency, on the other hand, is not well-represented in alternative models of
impulsivity, despite consistently emerging as a unique predictor of substance use. Tighter
integration with other lines of research may lead to important theoretical innovations concerning
this trait. However, even it may not escape Ockham’s razor, given that the Negative Urgency
findings can still be accounted for in more parsimonious models. These two-factor models,
anchored in biological processes, show remarkable consistency across domains and provide an
optimal balance of explanatory power, parsimony, and integration of evidence.
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Role of Funding Source
Dr Gullo is supported by a National Health and Medical Research Council (NHMRC) of
Australia Early Career Fellowship (APP1036365).
All authors contributed to the development of the review, including the first draft and subsequent
Conflict of Interest
No conflict declared.
Table 1. Distinct components of impulsive substance use.
Approach Impulse
↓ Inhibitory Control
Dawe & Loxton (2004)
Steinberg (2008)
Woicik, Stewart, Pihl, &
Conrod (2009)
Depue & Collins (1999)
Reward Sensitivity/Drive
Sensation Seeking
Sensation Seeking
(Agentic) Extraversion
Rash Impulsiveness
(Low) Constraint
Wiers et al. (2007)
de Wit & Richards (2004)
Bari & Robbins (in press)
Swann, Bjork, Moeller, &
Dougherty (2002)
Goldstein & Volkow (2002)
Potenza & Taylor (2009)
Appetitive Motivation
Delay Discounting
Impulsive Choice
Reward-delay Impulsivity
(Impaired) Salience
Choice Impulsivity
(Poor) Self-regulation
Motor (Dis)inhibition
Impulsive Action
Rapid-response Impulsivity
(Impaired) Response
Response Impulsivity
Bechara (2005)
Jentsch & Taylor (1999)
Bickel et al. (2007)
Impulsive System
(striatum, amygdala)
Limbic System (NAcc,
VTA, amygdala)
Impulsive System (NAcc,
ventral pallidum, amygdala)
Reflective Prefrontal Cortex
ACC, insula)
Frontal Cortical System
Executive System
Note. VMPFC = ventromedial prefrontal cortex, DLPFC = dorsolateral prefrontal cortex, ACC
anterior cingulate cortex, NAcc = nucleus accumbens, VTA = ventral tegmental area, PFC =
prefrontal cortex.
Table 2. Summary of studies investigating unique relations between UPPS+P traits and substance use.
Substance Use
Summary of Findings
Prospective Studies
Cyders et al. (2009)
418 undergraduate students
(75% female; mean age = 18.2,
SD = 0.76, 70% retention at
Time 2)
Drinking Styles
Questionnaire (G. T.
Smith, McCarthy, &
Goldman, 1995)
-SS prospectively
predicted drinking
frequency (approx. 8
months later)
-PU prospectively
predicted drinking
quantity and problems
(approx. 8 months later)
Zapolski et al. (2009)
407 undergraduate students
(73% female; mean age = 18.5,
SD = 8.1)
71% retention at Time 2
Risky Behaviors Scale
(Fischer & Smith,
-PU prospectively
predicted illegal drug
use (approx. 9 months
Stojek & Fischer (2013)
319 female undergraduate
students (modal age = 18)
Short Michigan
Alcoholism Screening
Test (SMAST; Selzer,
Vinokur, & Rooijen,
prospectively predicted
the emergence of
alcohol dependence
symptoms (approx. 4
months later)
-Premeditation and
NU prospectively
predicted the
progression of alcohol
dependence severity
among those reporting
at least one symptoms
at Time 1 (approx. 4
months later)
Simons et al. (2010)
102 moderate-to-heavy
drinking college students (52%
female; mean age = 20.3, SD =
Women: >11 drinks/week;
Men: >15 drinks/week
Modified daily
Drinking Questionnaire
(DDQ-M; Dimeff,
Baer, Kivlahan, &
Marlatt, 1999)
Young Adult Alcohol
Questionnaire (Read,
Kahler, Strong, &
Colder, 2006)
prospectively predicted
greater intoxication
over following 21 days,
PU predicted less
-While controlling for
intoxication, no UPPS
scale prospectively
predicted alcohol
dependence symptoms
Clinical Studies
Verdejo-Garcia et al.
36 substance-dependent
Addiction Severity
-NU predicted drug use
individuals (58.3% female,
mean age = 36.1, SD = 10.7).
Drug of choice: 5 alcohol, 14
methamphetamine, 7 cocaine
36 gender and age-matched
controls (61% female; mean
age = 38.1, SD = 15.8)
Index (McLellan et al.,
-No scale predicted
alcohol use severity
Whiteside et al. (2005)
122 adults recruited from
Alcoholics Anonymous (AA)
groups, Gamblers Anonymous,
and various hospital/community
treatment centres (66.4%
female; mean age = 40.2, SD =
-No scale predicted
unique variance in
alcohol problems.
However, as a set, they
account for 8% shared
variance in alcohol
Developmental Studies
Settles et al. (2012,
Study 2)
-905 5th grade girls
-908 5th grade boys
Drinking Styles
presence vs absence of
1+ drinking problems)
-While controlling for
pubertal status and
negative affect, only
NU predicted problem
drinking in boys and
College Studies
Adams et al. (2012)
432 undergraduate students
(46.9% male; Mean age = 19.0,
SD = 0.8)
Latent factor
comprising 2 items
from AUDIT + highest
amount consumed in
SS, Premeditation, and
NU predicted problem
past year
Murphy & MacKillop
116 college students (80.5%
female; mean age = 20.3, range
Alcohol Use Disorders
Identification Test
(AUDIT; Saunders,
Aasland, Babor, de la
Fuente, & Grant, 1993)
-Items 1-3 comprised a
consumption measure
-Items 4-10 comprised
alcohol problems
-After controlling for
delay discounting &
mindfulness, only NU
predicted alcohol
-After controlling for
delay discounting &
mindfulness, only NU
and Premeditation
predicted alcohol
Fischer & Smith (2008)
246 undergraduate students
(50% male; modal age = 19)
Drinking Styles
Questionnaire (G T
Smith et al., 1995)
-SS and Premeditation
predicted alcohol use
-NU and
predicted problem
Fischer, Smith, Annus,
& Hendricks (2007)
66 female undergraduates (32
with bulimic symptoms). Mean
age = 19.5, SD = 2.1
Structured Clinical
Interview I for DSM-IV
-NU predicted
frequency of alcohol
Gonzalez, Reynolds, &
Skewes (2011)
143 college students (69.9%
female; mean age = 21.3, SD =
Brief Young Adult
Alcohol Consequences
Questionnaire (B-
YAACQ; Kahler,
Strong, & Read, 2005)
-When controlling for
depression, delay
discounting, and
drinking to cope
motives, only NU
predicted alcohol
Magid & Colder (2007)
267 undergraduate students
(53% female; mean age = 19,
range: 18-26)
Alcohol Use: product of
single items measuring
past-month quantity
and frequency
Rutgers Alcohol
Problem Index (RAPI;
White & Labouvie,
-Premeditation and SS
predicted alcohol use
-After controlling for
alcohol use, NU and
Perseverance predicted
alcohol problems
Curcio & George
317 undergraduate students
reporting past-year alcohol use
(aged 18-25 years, 75% female)
College Alcohol
Problems Scale-
Revised (Maddock,
Laforge, Rossi, &
O’Hare, 2001)
-Only SS predicted
problem drinking
Settles et al. (2012,
Study 3)
418 undergraduates (75%
female; mean age = 18.2, SD =
Drinking Styles
Illegal drugs items on
Risky Behavior Scale
(Fischer & Smith,
-While controlling for
negative affect, NU &
predicted problem
drinking and illegal
drug use
A. E. Smith et al.
255 undergraduate students
who reported past month
alcohol use (73.3% female;
mean age = 20.6, SD = 4.3)
Modified daily
Drinking Questionnaire
Young Adult Alcohol
-After controlling for
sex, race, parental
income, & reinforcing
efficacy, NU & SS
predicted alcohol
problems and no. of
drinks per week
Note. NU = Negative urgency; PU = Positive Urgency; Premeditation = (Lack of) Premeditation; Perseverance = (Lack of)
Perseverance; SS = Sensation Seeking.
... Impulsivity is a predisposition to rapid (approach) behavior in response to internal/external stimuli without regard to negative consequences [13][14][15]. Within the context of addiction, the importance of two core dimensions has emerged across biological, behavioral, and self-report studies [3,[16][17][18][19][20][21][22]. The first relates to the strength of the approach impulse requiring inhibition, which we refer to here as reward drive, and relates to reward processing and the mesolimbic dopamine system [23]. ...
... The first relates to the strength of the approach impulse requiring inhibition, which we refer to here as reward drive, and relates to reward processing and the mesolimbic dopamine system [23]. Many models posit such a dimension that is variously referred to as appetitive motivation, sensation seeking, choice impulsivity, or rewarddelay impulsivity [17]. The second dimension relates to the capacity for inhibition of a prepotent approach response due, in part, to the (lack of) consideration of negative consequences, which we refer to here as rash impulsiveness. ...
... It relates more to prefrontal inhibitory control mechanisms and the orbitofrontal and anterior cingulate cortices in particular [23]. Many models posit such a dimension that is variously referred to as impulsivity, (low) constraint, disinhibition, response impulsivity, or (lack of) premeditation [17]. Despite the heritability and stability of the two dimensions [5,24], there is also high within-person variability in the expression of trait-related behaviors [25], providing opportunities for experimental research. ...
Full-text available
Purpose of Review Impulsivity has long been recognized as a risk factor for addiction. The mechanisms through which impulsivity increases risk remain unclear, hindering development of effective impulsivity-targeted addiction treatments. Preclinical human research is ideally placed to isolate these mechanisms because of the experimental control afforded by the laboratory. This review summarizes recent preclinical human studies on impulsivity and addiction that are focused on alcohol use or food consumption/overeating. Recent Findings The emergence of laboratory paradigms specifically modeling impulsive consumption is a promising development, especially paradigms capable of manipulating impulsivity to test causation. Collectively, this evidence highlights the importance of reward mechanisms in impulsivity-related alcohol and food consumption. Summary Findings suggest that impulsivity-targeted addiction interventions may be enhanced by widening the current focus on disinhibition-related mechanisms to include reward drive. Preclinical models of impulsive consumption could be utilized to pilot candidate pharmacological and psychosocial therapeutics on causal mechanisms, informing the next generation of impulsivity-targeted treatment.
... Impulsivity, broadly defined as rapid unplanned reactions to internal or external stimuli without regard for negative consequences [2], has been considered an important construct in the addiction cycle. Both increased reward sensitivity and decreased inhibitory control have been used to describe impulsivity, although some prefer to align impulsivity more closely with one facet over the other [3,4]. Impulsivity is typically conceptualized as a relatively stable characteristic, but more recent evidence suggests that facets of impulsivity can exhibit daily and hourly fluctuations [5,6]. ...
... Alternatively, those who prioritize biological and behaviorist theories of motivation developed questionnaires which map onto two or three factors, such as the Barratt Impulsiveness Scale (BIS-11), Eysenck's impulsiveness scale, and the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) [16][17][18]. These models emphasize measuring theory-driven and biologically based mechanisms of motivation, such as behavioral activation and inhibition systems [3,19]. Others have focused on impulsivity's functional relevance to personality disorders, such as the Difficulties in Emotion Regulation Scale (DERS) [20]. ...
... Additionally, to evaluate an effect on impulsivity, we required studies to include repeated administration of an assessment of impulsivity. This excluded many published studies from the current review, as impulsivity is frequently examined as a predictor or risk factor for substance use or moderator of treatment outcomes, rather than as an outcome itself [3,[62][63][64]. Likewise, the inclusion criterion requiring a RCT design with a CBT treatment condition further limited the number of included studies. ...
Full-text available
Purpose of Review Impulsivity is considered an important construct in the cycle of addiction, yet the effect of evidence-based treatments on impulsivity is unclear. The goal of this paper was to review the evidence regarding the effect of cognitive behavioral therapy (CBT), one of the most studied psychotherapies for addiction, on measures of impulsivity in addictive disorders. Recent Findings There is a robust literature implicating impulsivity as risk factor for development of a range of addictions and poorer treatment outcomes. However, this review identified only four randomized controlled trials evaluating CBT for an addictive behavior that included repeated assessment of impulsivity. All four were studies targeting substance use. Summary There is limited evidence that CBT has a direct effect on change in measures of impulsivity among individuals being treated for substance use. Future clinical trials should include repeated measurement of impulsivity to examine CBT’s effect on the underlying characteristics of addiction.
... Especially, in BED, a stronger impulsive system and a weaker reflective system leads to increased impulsivity and poor cognitive control towards food stimuli [3,6,7]. Another framework highlights food-related impulsivity as a central factor in BED: increased sensitivity to rewarding stimuli, increased rash and spontaneous behaviour towards rewarding stimuli or slower disentanglement of those [8,9]. In sum, attentional biases for food indicate faster processing of food in an early orientation reaction and slower disengagement from these stimuli in patients with BED, thus suggesting to interfere with response inhibition and goaldirected behaviour [10][11][12][13][14][15]. ...
... Although it has to be interpreted with caution as higher levels of impulsivity within the sample did not lead to faster movement initiation towards food. Surprisingly, in contradiction of the assumption of generally elevated food-related impulsivity in patients with BED, food was collected slower than office tools after an approach movement was initiated [8,9]. Even though this finding is unexpected, it coincides with the finding of the study of Max et al. with healthy participants. ...
Full-text available
Cognitive processes play a central role in the development, maintenance and remission in mental disorders, like in Binge Eating Disorder (BED). Insights into cognitive mechanisms reflected by embodied interaction with food and its connections to clinically relevant psychopathology offer new possibilities for translational diagnostics and interventions. We longitudinally investigated the manual interaction with food in a virtual reality (VR) in 31 patients with BED. Patients were assessed at baseline before participating in a randomized-controlled trial (RCT) investigating a computer-based inhibitory control training programme enhanced by transcranial direct current stimulation (tDCS) and at a 6-week follow-up. At both assessments, an experimental VR paradigm was conducted and patients were characterized concerning eating disorder psychopathology, eating behaviour, general impulsivity and food craving. In the experimental task, one of two simultaneously presented objects (food vs. office tools) had to be collected. Food was recognized faster than office tools and subsequent approach behaviour was initiated faster, whereas thereafter, food was collected slower than office tools. Exploratory, we could not find a modulatory effect of applied tDCS on the interaction with food. No relationship between behavioural biases and sample characterizations could be detected. Two different stages in the manual interaction with food were found: a faster first stage that comprises recognition and movement initiation and a slower second stage that comprises controlled handling and may reflect aversive motivational processes. As the behavioural patterns do not change with an ameliorated BED-psychopathology at the second assessment, the task seems insensitive in detecting translational interconnections between behavioural biases and BED-characteristics. Level of evidence: Level I, experimental study.
... Early work indicates that negative urgency impacts patterns of problematic drinking through coping and enhancement motives while sensation seeking and lack of premeditation also have some have some indirect influence through drinking motives [51]. In more recent work on social drinkers, both BIS-11 impulsivity and Cluster B traits were related to alcohol use severity and were mediated by positive alcohol use expectancies [52]. In young women, BPD symptoms indirectly affect alcohol-related problems through two pathways: (a) affective instability and coping motives; and (b) sensation seeking and enhancement motives [53]. ...
... With respect to the Two-Factor Model, the parsimony of just two impulsivity factors-rash impulsiveness and reward sensitivity/drive-has been argued as a more optimal solution than the UPPS-P model in the addiction literature [52]. While rash impulsiveness ostensibly overlaps with positive urgency, negative urgency, and lack of premeditation, reward sensitivity/drive is best considered as a sensation seeking component that does not conflate the attitudinal openness to experience inherent to sensation seeking. ...
Full-text available
Purpose of Review Personality disorders (PDs) are frequently comorbid with substance use disorders (SUDs) including alcohol use disorder (AUD), but the factors explaining their comorbidity are not yet fully understood. This article reviews recent research on the co-occurrence of PD and SUD/AUD and discusses how contemporary research on impulsivity-related personality and psychopathology dimensions might partially account for their high comorbidity. Recent Findings Comorbidity between PDs and SUDs/AUD is substantial across population-based and clinical studies and is most apparent in Cluster B PDs. Studies of trait-based impulsivity suggest this comorbidity may be partly explained by UPPS-P model of impulsivity factors (e.g., negative urgency). Research consistent with the Hierarchical Taxonomy of Psychopathology suggests that impulsivity-relevant psychopathology dimensions, including broader symptom domains (e.g., disinhibited externalizing) and narrower symptom components and maladaptive traits (e.g., risk-taking, delay-discounting), contribute to PD and SUD/AUD comorbidity. Summary Impulsive personality traits and psychopathology dimensions partially account for the high comorbidity between PD and SUD/AUD diagnoses.
... This fallacy alludes to understanding two different concepts as the same just because they have different names or, conversely, interpreting two different concepts that share the same label as the same in content. Consequently, different models have been proposed in the literature to specify the different facets of impulsivity, none of which has yet attracted full consensus among researchers (Gullo et al., 2014;MacKillop et al., 2016;Vergés et al., 2019;Whiteside & Lynam, 2001). However, in recent times, the five-factor model of impulsivity (originally four-factor), assessed by the UPPS-P Impulsive Behavior Scale, which is based on a multifactorial understanding of the construct (Lynam et al., 2006), has been gaining popularity. ...
... Las características neurofisiológicas en la etapa adolescente son vitales para determinar las distintas fases por las que puede pasar un joven en esa época de su vida (Gullo, Loxton, & Dawe, 2014). Además, el tema es bastante amplio, entran aspectos como seguridad, salud, sexualidad, personalidad y así un abanico lo suficiente sustentable para hablar de ello y tratar el tema como tal. ...
Full-text available
PROBLEMA: la adolescencia es una etapa de muchos cambios, por lo que es necesario estudiarla OBJETIVO: determinar las características neuropsicológicas en los pacientes de la clínica del adolescente de Zacapa, Zacapa. MÉTODO: estudio descriptivo de corte transversal con enfoque analítico en la clínica psicológica del adolescente de Zacapa. El universo estará compuesto por pacientes que acudieron a la clínica del adolescente de Zacapa, Zacapa. Y la muestra por 98 pacientes que se encuentren en el rango de 12 a 17 años las cuales puedan ser clasificadas dentro del término de adolescentes. RESULTADOS: arrojaron que los pacientes evaluados presentaron en mayor medida estrés y depresión, en los que prevalece el sexo femenino sobre el masculino con un 48%. Un 78% pertenece al área urbana por cuestiones de acceso. CONCLUSIÓN: la etapa de la adolescencia es una de las etapas más duras por las que todo ser humano tiene que pasar y que ya pasó, pero esa transición trae consigo muchos retos tanto ambientales como psicológicos y físicos que resultan en un reto. Se puede determinar que en mayor medida los adolescentes están propensos a padecer depresión y ansiedad y el grupo actual que está pasando por esa etapa, también tiene una variable que otros no pudieron contar y es la pandemia que se vivió desde el 2020 lo cual significó en muchos cambios para ellos y que también los afectó en menor o mayor.