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The UPPS model of impulsivity in the abuse of Information and Communication Technologies (ICT) // El modelo UPPS de impulsividad en el abuso de las Tecnologías de la Información y la Comunicación (TIC)


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The UPPS model of impulsivity has recently been proposed, has been widely applied to substance abuse and is one of those recommended in the context of Research Domain Criteria, RDoC. However, its application to the abuse of information and communication technologies (ICTs) has been very limited. In the present work, a sample of n=748 (67% females) was recruited through the Internet, and the reduced version of the UPPS-P was administered, in addition to the MULTICAGE-TIC and the Prefrontal Symptoms Inventory (PSI-20). The psychometric properties of UPPS-P were satisfactory in terms of internal consistency (0.87 > ω > 0.75) and structural validity. Impulsivity measured by UPPS-P correlated with all MULTICAGE-TIC scales, although with a very small effect size, and with greater magnitude with prefrontal dysfunction symptoms. The impulsivity dimension most related to ICT abuse was Urgency (0.3 > r > 0.2). A structural analysis of all the variables was carried out, with impulsivity appearing as a product of the prefrontal malfunction that predicted, through Positive Urgency, the abuse of ICTs. Impulsivity does not seem to be the central nucleus of ICT abuse, but rather failures in the superior control of behavior, of which impulsivity would be a consequence, but not the most important. This makes it advisable to design cognitive rehabilitation interventions that improve the functioning of superior behavior control mechanisms in the prevention and treatment of ICT abuse.
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original adicciones vol. xx, nº x · 2020
The UPPS model of impulsivity in the abuse of
Information and Communication Technologies (ICT)
El modelo UPPS de impulsividad en el abuso de las
Tecnologías de la Información y la Comunicación (TIC)
E J. P P*, S M A*, V G A*,
L B R*, I F E*, J M R S  L**.
* Unidad de Formación e Investigación. Departamento de Evaluación y Calidad. Madrid Salud. Ayuntamiento de Madrid.
** Departamento de Psicología Experimental, Procesos Cognitivos y Logopedia. Universidad Complutense de Madrid.
Received: November 2019; Accepted: May 2020.
Send correspondence to: Eduardo J. Pedrero Pérez. Unidad de Formación e Investigación. Dpto. de Evaluación y Calidad.
Madrid Salud. Ayuntamiento de Madrid. Av. del Mediterráneo 62. 28007 Madrid. Tel. 915887675.
Abstract Resumen
El modelo UPPS de impulsividad se ha propuesto recientemente, ha
sido ampliamente aplicado al abuso de sustancias y es uno de los re-
comendados en el contexto de investigación Research Domain Criteria,
RDoC. Sin embargo, su aplicación al abuso de tecnologías de la infor-
mación y la comunicación (TIC) ha sido muy limitado. En el presente
trabajo se reclutó a través de Internet una muestra de n=748 (67%
mujeres) y se administró la versión reducida de la UPPS-P, además del
MULTICAGE-TIC y el Inventario de Síntomas Prefrontales (ISP-20).
Las propiedades psicométricas de la UPPS-P resultaron satisfactorias
en consistencia interna (0,87>ω>0,75) y validez estructural. La impul-
sividad medida por la UPPS-P correlacionó con todas las escalas del
MULTICAGE-TIC, aunque con un tamaño del efecto muy pequeño,
y con mayor magnitud con las de síntomas de mal funcionamiento
prefrontal. Las dimensiones de impulsividad más relacionadas con el
abuso de las TIC fueron las de Urgencia (0,3>r>0,2). Se realizó un
análisis estructural de todas las variables apareciendo la impulsividad
como un producto del mal funcionamiento prefrontal que predecía,
a través de la Urgencia Positiva, el abuso de las TIC. La impulsividad
no parece ser el núcleo central del abuso de las TIC, sino los fallos en
el control superior de la conducta, de los que la impulsividad sería
una consecuencia, pero no la más importante. Ello hace recomenda-
ble el diseño de intervenciones de rehabilitación cognitiva que mejo-
ren el funcionamiento de los mecanismos de control superior de la
conducta en la prevención y tratamiento del abuso de las TIC.
Palabras clave: Conducta adictiva; Conducta impulsiva; Corteza pre-
frontal; Modelado de ecuaciones estructurales; Adicciones comporta-
mentales; Abuso de tecnologías de la información y la comunicación.
The UPPS model of impulsivity has recently been proposed, has been
widely applied to substance abuse and is one of those recommend-
ed in the context of Research Domain Criteria, RDoC. However, its
application to the abuse of information and communication tech-
nologies (ICTs) has been very limited. In the present work, a sample
of n=748 (67% females) was recruited through the Internet, and the
reduced version of the UPPS-P was administered, in addition to the
MULTICAGE-TIC and the Prefrontal Symptoms Inventory (PSI-20).
The psychometric properties of UPPS-P were satisfactory in terms of
internal consistency (0.87 > ω > 0.75) and structural validity. Impulsiv-
ity measured by UPPS-P correlated with all MULTICAGE-TIC scales,
although with a very small effect size, and with greater magnitude
with prefrontal dysfunction symptoms. The impulsivity dimension
most related to ICT abuse was Urgency (0.3 > r > 0.2). A structural
analysis of all the variables was carried out, with impulsivity appearing
as a product of the prefrontal malfunction that predicted, through
Positive Urgency, the abuse of ICTs. Impulsivity does not seem to be
the central nucleus of ICT abuse, but rather failures in the superior
control of behavior, of which impulsivity would be a consequence, but
not the most important. This makes it advisable to design cognitive
rehabilitation interventions that improve the functioning of superior
behavior control mechanisms in the prevention and treatment of ICT
Keywords: Addictive behavior; Impulsive behavior; Compulsive behav-
ior; Prefrontal cortex; Public health; Modeling of structural equa-
tions; Behavioral addictions; Abuse of information and communica-
tion technologies.
ADICCIONES, 2020 · VOL. xx NO. x · PAGES xx-xx
The UPPS model of impulsivity in the abuse of Information and Communication Technologies (ICT)
Impulsivity is a widely studied psychological con-
struct and is usually linked to a variety of psycho-
logical manifestations. There is, however, no theo-
retical consensus regarding the true meaning of the
construct, which has been dened in very different ways
by each theoretical approach (Nigg, 2017). In general, it
refers to behaviors carried out without sufcient reection,
focused on immediate goals, without calculating medium-
and long-term consequences (Evenden, 1999), although in
certain circumstances they may also represent behaviorally
adaptive options (Dickman, 1990). This type of behavior
is usually linked to multiple psychopathological manifes-
tations, including self-injurious and suicidal behaviors
(Lockwood, Daley, Townsend & Sayal, 2017), violent be-
haviors (Bresin, 2019) and personality disorders (Gagnon,
2017), among many others. Neuropsychological studies
have identied the neural substrates of the construct (Bari
& Robbins, 2013; Chamberlain & Sahakian, 2007), which
must necessarily be considered multidimensional (Rochat,
Billieux, Gagnon & Van der Linden, 2018).
One of the areas in which impulsivity has been most stud-
ied is in substance dependence since impulsivity is consid-
ered a marker of vulnerability for the development of ad-
dictive behaviors (Lee, Hoppenbrouwers & Franken, 2019;
Verdejo-García, Lawrence & Clark, 2008), something that
has been proven in animal studies (Dalley, Everitt & Rob-
bins, 2011). There is also evidence of increased impulsivity
associated with addictive behaviors not involving substanc-
es (Grant & Chamberlain, 2014; S,ims,ek, Zincir, Özen &
Ceyhan, 2019), although the different studies are very het-
erogeneous (Carvalho, Sette & Ferrari, 2018). From a neu-
ropsychological perspective, response inhibition is a skill
linked to the integrity of the dorsolateral prefrontal cortex,
which allows the interruption or non-execution of auto-
mated behavior or an acquired habit when the non-inter-
ruption or execution of the behavior will be unsuitable and
result in an error (Fuster, 1997). Decits in the response
inhibition system and inhibitory control are a central el-
ement in addictive behaviors, according to the consensus
reached recently by a group of scientists in the framework
of the Research Domain Criteria, RDoC (Yücel et al., 2019),
research project.
This group considers that one of the instruments most
suitable for its measurement is the UPPS (Whiteside &
Lynam, 2001). The authors of this test noted the general
confusion between the various conceptualizations of im-
pulsivity and decided to eschew any specic position on the
nature or causes of impulsivity, attempting instead to cap-
ture what they believed to be various etiological pathways
of impulsive behavior. To do this, they used exploratory
factor analysis to assess the various facets of the NEO-PI-R
instrument (Costa &McCrae, 1992) related to impulsivity
and up to eight impulsivity scales of very different theoret-
ical orientations. With the set of items selected for each of
the factors, the authors developed the new questionnaire,
called the UPPS Impulsive Behavior Scale, in which they
identied four traits: negative urgency (impulsive behavior
arising as a reaction to intense negative affect); [lack of]
premeditation, which implies the ability to choose an option
while taking possible consequences into account; [Lack
of] perseverance (the ability to stay on task, especially if it is
difcult or boring); and sensation seeking (the tendency to
look for new activities or activities that involve risk). These
dimensions made it possible to understand impulsivity
through its emotional/affective aspects (in urgency and sen-
sation seeking) as well as through more cognitive aspects (in
lack of perseverance and premeditation). In the original UPPS
review (UPPS-P; Lynam, Smith, Cyders, Fischer & Whi-
teside, 2007) a fth dimension was incorporated: positive
urgency, dened as the propensity to act rashly triggered
by intense positive affect. These ve impulsivity traits can
be measured with the 59-item UPPS-P, from which a short-
ened version of 20 items was subsequently developed (Bil-
lieux et al., 2012).
The traits comprising the UPPS model have been
found to be strongly linked to neural substrates, specic
to a certain degree for each one and primarily involving
fronto-cortical circuits with subcortical structures (Rochat
et al., 2018). These ndings have been replicated in par-
ticular in the study of addictive behaviors linked to various
substances (Yücel et al., 2019).
The initial four-scale version has been used increasing-
ly often in the study of substance addiction (Whiteside &
Lynam, 2003; Magid & Colder, 2007) as well as in non-sub-
stance-related addictive behaviors (Billieux, Rochat, Rebe-
tez & Van der Linden, 2008; Billieux, Van der Linden, M. &
Rochat, 2008; Billieux et al., 2011; Rømer Thomsen et al.,
2018), among other psychological problems. The revised
version, UPPS-P, has also been used in the study of abuse of
substances such as alcohol (McCarty, Morris, Hatz & McCa-
rthy, 2017), cannabis (VanderVeen, Hershberger & Cyders,
2016) and tobacco (Kale, Stautz & Cooper, 2018).
Despite this, there are scarcely any studies which apply
it to so-called non-substance addictive behaviors. There is
currently considerable controversy over whether such be-
haviors should really be considered addictions, with the
prevailing view being that this comparison is not permis-
sible (Billieux, Schimmenti, Khazaal, Maurage & Heeren,
2015; Panova & Carbonell, 2018; Yu & Sussman, 2020). Op-
posing this view, many authors consider that the circuits in-
volved in so-called behavioral addictions are essentially the
same as in substance addiction (Horvath et al., 2020; Yao
et al., 2017). What both perspectives share is the consider-
ation that in both cases a prefrontal hypofunction occurs
that results in a loss of higher behavior control.
The UPPS has been used in the study of online sexual
activity (Savvidou et al., 2017), problematic Internet use
(Navas, Torres, Cándido & Perales, 2014) and pathological
ADICCIONES, 2020 · VOL. xx NO. x
Eduardo J. Pedrero Pérez, Sara Morales Alonso, Vanesa Gallardo Arriero,
Laura Blázquez Rollón, Irene Folguera Expósito, José María Ruiz Sánchez de León
gambling (Jara-Rizzo et al., 2019; Wéry, Deleuze, Canale
& Billieux, 2018). While pathological gambling is mainly
linked to negative urgency, online sexual activity is especially
related to positive urgency, and Internet abuse is not linked
to any dimension in particular. These differences could po-
tentially serve to classify behaviors maintained by negative
or positive reinforcement.
The UPPS-P has been translated to and validated in
Spanish, both in its full version (Verdejo-García, Lozano,
Moya, Alcázar & Pérez-García, 2010) and its short form
(Cándido, Orduña, Perales, Verdejo-García & Billieux,
2012). The present study aims to investigate some psycho-
metric properties of the short UPPS-P and subsequently
analyze the relationships between the impulsive dimen-
sions of the UPPS model, the use/abuse of information
and communication technologies (ICT) and symptoms of
prefrontal malfunction.
A sample of n = 764 was obtained. No exclusion criteria
were set, particularly with regard to age, since the respons-
es in all age groups were of interest. After an outlier de-
tection analysis, 16 participants with atypical scores (2.1%)
were excluded, leaving a nal reduced sample of n = 748.
Table 1 shows the descriptive statistics of the nal sample,
93.6% of whom were born and lived in Spain.
Short version (20 items) of the UPPS-P (Lynam, 2013),
Spanish version (Cándido et al., 2012). This measures ve
impulsivity traits (four items each): negative urgency, lack of
premeditation, lack of perseverance, sensation seeking, and posi-
tive urgency. Item responses are on a four-point Likert-type
scale from 1 (strongly agree) to 4 (strongly disagree). The
score is inverted in the two urgency scales and in sensation
seeking so that they can all be scored in the direction of
impulsivity, with each having a scoring range from 4 to 16.
The internal consistency of the ve scales, estimated using
Cronbach’s α, ranged from 0.61 to 0.81, with the two ur-
gency scales below 0.7, which is considered to be the lowest
acceptable limit.
MULTICAGE-TIC, a 20-item questionnaire comprising
ve scales surveying problems related to the use of the
Internet, mobile phones, video games, instant messaging
and social networks (Pedrero-Pérez et al., 2018). It is based
on MULTICAGE CAD-4, a screening questionnaire for
compulsive behavior, with and without substances (Pedre-
ro-Pérez et al., 2007), which has been used in primary care
(e.g., Reneses et al., 2015), behavioral addictions (e.g.,
Megías et al., 2018) and substance addiction (e.g., Navas,
Torres, Cándido & Perales, 2014). Subsequently, a mobile
phone use/abuse scale was included (Rodríguez-Monje et
al., 2019). The MULTICAGE-TIC has four dichotomous
response (yes/no) items for each problem behavior asking
about the following: item 1, estimated excessive time dedi-
cation; item 2, excessive time estimated by signicant oth-
ers; item 3, difculty in refraining from the behavior; item
4, difculties in voluntarily interrupting the behavior. The
score on each scale is the number of afrmative responses,
ranging from 0 to 4 points, 0 corresponding to the absence
of the problem and 4 to abuse. The psychometric study
showed adequate internal consistency for all its scales (0.74
< ω < 0.93) and evidence of structural validity.
Prefrontal Symptoms Inventory, screening version (PSI-
20; Pedrero-Pérez, Ruiz-Sánchez de León, Morales-Alon-
so, Pedrero-Aguilar & Fernández-Méndez, 2015). This
explores symptoms of malfunction in daily life linked to
neuropsychological disorders attributable to the prefrontal
cortex. This scale has 20 items with Likert-type responses
(0: never or almost never; 1: a few times; 2: sometimes yes,
sometimes no; 3: many times; 4: always or almost always).
The factorial study found a three-factor solution: behavio-
ral control problems, emotional control problems and so-
cial behavior problems. Higher scores correspond to more
prefrontal malfunction symptoms. Validation in both the
general population and people being treated for addictive
behaviors reported adequate internal consistency for all
subscales (0.87 < αs < 0.89). In our sample, the multivariate
consistency of the complete test was αs = 0.91 and that of
the scales 0.81 < αs < 0.90.
Since the target population was regular ICT users, a sur-
vey was developed using Google Docs® and anonymous and
voluntary participation was sought through instant messag-
ing programs (WhatsApp®), social networks (Facebook®,
Instagram®) and email. At the same time, participants were
Table 1. Sample descriptives
Men Women Total
n  (.%)  (.%) 
 -   (.%)  (.%)  (.%)
 -   (.%)  (.%)  (.%)
 -   (.%)  (.%)  (.%)
 -   (.%)  (.%)  (.%)
>   (.%)  (.%)  (.%)
Primary or lower  (.%)  (.%)  (.%)
Lower secondary  (.%)  (.%)  (.%)
Higher secondary  (.%)  (.%)  (.%)
University student  (.%)  (.%)  (.%)
University degree  (.%)  (.%)  (.%)
ADICCIONES, 2020 · VOL. xx NO. x
The UPPS model of impulsivity in the abuse of Information and Communication Technologies (ICT)
asked to forward the questionnaire to their contacts, thus a
chain sampling technique was used. The online question-
naire was restricted to prevent it being completed more
than once on the same device. Since participation was
voluntary, subjects were told about the aims of the study,
but informed consent was not included as it was implicit in
completing the test. Data collection ran from January 2 to
February 12, 2019, and a sample of n = 764 was nally ob-
tained. This sample was considered large enough since the
ratio between the sample n and the number of items (60
in total) was higher than 10, which is usually considered
adequate according to the most demanding criteria.
Data analysis
Firstly, in order to detect and exclude outliers, an analy-
sis was performed using the Mahalanobis distance with a p
< 0.001 criterion. The univariate descriptions of the items
were then obtained and the Mardia (1970) criterion was
applied to test whether the data tted a multivariate nor-
mal distribution. Conrmatory factor analysis was carried
out, using rstly the maximum likelihood method to favor
comparability with previous studies, and then an unweight-
ed least squares analysis as the method best suited to the
nature of the data (Morata-Ramírez, Holgado-Tello, Barbe-
ro-García & Méndez, 2015). Two possible factorial solutions
were compared by applying the goodness-of-t indices in
AMOS 21: absolute (GFI, AGFI, RMR), relative (NFI, RFI)
and parsimonious (PGFI, PNFI). Suitable values were those
exceeding 0.95 for GFI, AGFI, NFI and RFI, those below
0.05 for RMR and those closest to 1 in PGFI and PNFI.
Once the best model was selected, the questionnaire struc-
ture was congured, also using AMOS 21. Internal consist-
ency was studied using various estimators, as recommended
when the data are not from linear variables or not normally
distributed (Revelle & Zinbarg, 2009; Sijtsma, 2009); specif-
ically, standardized Cronbach’s alpha (α
; Enders & Banda-
los, 1999) and McDonald’s omega (ω) were used. A corre-
lational study was performed using Pearson’s r and a linear
stepwise regression analysis, conrming the contribution to
the model using R
and effect size using β. In the multi-
ple correlations, the Bonferroni correction was applied to
avoid Type I error. Finally, path analysis was carried out to
structurally link all the variables previously studied and by
means of the previously used method and t indices. The
SPSS 22 statistical package and the AMOS 21 program were
used for all analyses, except for internal consistency estima-
tors, which were obtained through the FACTOR 10.10.01
program. (Lorenzo-Seva & Ferrando, 2006).
Confirmatory factor analysis (CFA)
On applying Mardia’s criterion, it was seen that item dis-
tribution did not t multivariate normality (p < 0.001). We
examined whether the theoretical model tted the data
obtained in the present study. First, a maximum likelihood
analysis was carried out, which provided acceptable t indi-
ces in almost all cases (CMIN/DF = 3.28; NFI = 0.905; RFI
= 0.887; IFI = 0.932; TLI = 0.919; CFI = 0.932; PNFI = 0.760;
RMSEA = 0.055). As most previous studies have used this
method, it was calculated here to make results comparable.
However, and given the nature of the data (non-continu-
ous Likert scale and absence of multivariate normality in
data distribution), an unweighted least-squares analysis was
then performed as the most suitable method. The t indi-
ces of a 3-factor (with urgency grouped into a single factor,
and lack of perseverance and premeditation into another) and
a 5-factor solution were studied. Both solutions showed an
adequate t to the data, although the 5-factor (GFI = 0.985;
AGFI = 0.980; PGFI = 0.750; NFI = 0.973; RFI = 0.968; PNFI
Figure . Structure of short UPPS-P
Nota. NU = Negative Urgency; LPr = Lack of Premeditation; LPe = Lack of Perseverance;
SS = Sensation seeking; PU = Positive Urgency.
Covariances Variances Item
Regression weights Error var
ADICCIONES, 2020 · VOL. xx NO. x
Eduardo J. Pedrero Pérez, Sara Morales Alonso, Vanesa Gallardo Arriero,
Laura Blázquez Rollón, Irene Folguera Expósito, José María Ruiz Sánchez de León
= 0.820; RMR = 0.028) was slightly higher than the 3-factor
solution (GFI = 0.959; AGFI = 0.949; PGFI = 0.763; NFI =
0.930; RFI = 0.920; PNFI = 0.817; RMR = 0.046. The result-
ing model is shown in Figure 1.
Internal consistency
Table 2 shows the internal consistency estimators of the
short UPPS-P scales. It can be seen that, as in the valida-
tion study (Cándido et al., 2012), the values for the two
urgency scales are unacceptable (< 0.70) when Cronbach’s
α is applied, but when the estimators most appropriate to
the nature of the data are applied, internal consistency is
acceptable in all cases.
Relationship with ICT abuse
Table 3 shows the correlations obtained between the
UPPS-P and MULTICAGE-TIC scales. As can be seen, there
are signicant correlations in almost all cases, except in
the use/abuse of video games. However, the effect size of
such differences is very small. Table 4 shows the resulting
regression models for each MULTICAGE-TIC scale. In all
cases, the proportion of the variance of the use/abuse of
each ICT is very low, with the urgency scales (positive and
negative) contributing most to the models, although again
with a very small effect size.
Relationship with prefrontal symptoms
Table 6 shows the correlations obtained between the
UPPS-P and PSI-20 scales. In this case, the effect sizes of
the correlations obtained between both urgency scales and
the lack of perseverance scale with all the subscales and the
total score on the PSI-20 were considerable, and somewhat
less so with the others.
Table 2. Reduced UPPS-P internal consistency estimators
α αs ω
Negative urgency . . .
Lack of premeditation . . .
Lack of perseverance . . .
Sensation seeking . . .
Positive urgency . . .
Note. α = Cronbach’s alpha; αs= standardised item; ω= McDonald’s omega.
Table 3. Bivariate correlations between the scales of the reduced
Lack of
Lack of
Internet .* .* .* .* .*
Mobile phones .* .* .* .* .*
Video . . . .* .*
Instant messaging .* .* . . .*
Social networks .* .* .* .* .*
Note. * Significant correlation after Bonferroni correction (p< 0.005).
Table 4. Regression models of the UPPS-P scales reduced on each of the MULTICAGE-TIC scales
Lack of
Lack of
perseverance Sensation seeking Positive urgency
R2*100 (β) Total % explained
Internet .% (.) .% (.) .% (.) .%
Mobile phones . % (.) .% (.) .% (.) .%
Video games .% (.) .%
Instant messaging .% (.) .% (.) .%
Social Networks .% (.) .% (.) .% (.) .%
Table 5. Bivariate correlations between the scales of the UPPS-P and the PSI-20.
ISP-20 Negative
Lack of
Lack of
seeking Positive urgency
Social behavior problems .* .* .* .* .*
Emotional control problems .* .* .* .* .*
Executive control problems .* .* .* .* .*
Total .* .* .* .* .*
Note. * Significant correlation after Bonferroni correction (p < 0.025).
ADICCIONES, 2020 · VOL. xx NO. x
The UPPS model of impulsivity in the abuse of Information and Communication Technologies (ICT)
General structural model
Figure 2 shows the predictive relationships between all
the variables used. To simplify the image, two restrictions
were imposed: (a) the ve subscales were used, proposed
by the authors as the best solution; and (b) regression
weights below 0.15 were removed. The model thus ob-
tained achieved adequate t indices (GFI = 0.997; AGFI =
0.992; NFI = 0.972; RFI = 0.936), although they could have
been better in some cases (RMR = 0.479; PGFI = 0.363;
PNFI = 0.424). It can be seen how, on the one hand, the
greatest predictive capacity corresponds to prefrontal symp-
tomatology on the UPPS-P subscales, and, on the other, that
positive urgency predicts all the MULTICAGE-TIC use/
abuse scales, albeit with small effect size. Negative urgency
only shows poor predictive capacity for instant messaging
use/abuse, lack of premeditation predicts the use/abuse of
mobile phones and social networks, sensation seeking only
predicts the latter, and lack of perseverance is not signicantly
predicted by any ICT scale.
The aim of this study was to examine the application
of the UPPS-P questionnaire, in its short 20-item version,
in a sample of people using or abusing information and
communication technologies. The test showed adequate
psychometric properties in its application to the sample
obtained in the present study. Conrmatory factor analysis
yielded adequate indices of t to the data of the theoretical
ve-scale structure. As in the initial validation study of the
Spanish version (Cándido et al., 2012), an alternative three-
scale structure was tried in which the two urgency scales
were merged on the one hand, and the lack of premeditation
and perseverance one the other; this also had adequate t to
the data, but was bettered by the ve-scale model.
The internal consistency of the ve scales was adequate
in all cases when multivariate estimators were used. This
was not the case when only Cronbach’s α was applied in
the validation study, something unacceptable at the cur-
rent level of knowledge (McNeish, 2018) yet common in
previous validation studies of the questionnaire (Billieux
et al., 2012; Bteich, Berbiche & Khazaal, 2017; D’Orta et
al., 2015; Dugré, Giguére, Percie du Sert, Potvin & Dumais,
2019; Fossati et al., 2010; Verdejo et al., 2010).
When the UPPS-P and MULTICAGE-TIC scales were
compared, it was observed that almost all correlations were
statistically signicant, but that effect sizes were very small
in all cases: the maximum coefcient of mutual correlation
is that between the use/abuse of mobile phones and posi-
tive urgency (r2 = 0.068), which can be interpreted as each
Figure . Structural model linking prefrontal symptoms, UPPS-P subscales, and ICT use / abuse scales.
Note. In italics, error variance; boxed and bold, standardized regression weights.
Regression weights below |0.15|.
Internet Mobile phones Video Instant
messaging Social networks
Lack of
Lack of
ADICCIONES, 2020 · VOL. xx NO. x
Eduardo J. Pedrero Pérez, Sara Morales Alonso, Vanesa Gallardo Arriero,
Laura Blázquez Rollón, Irene Folguera Expósito, José María Ruiz Sánchez de León
variable only being capable of predicting 6.8% of the oth-
er. These results contrast with those obtained on the same
sample when ICT-related compulsivity was explored, some
variables reaching up to 40% of mutual determination
(Pedrero-Pérez, Morales-Alonso & Ruiz-Sánchez de León,
2020). Based on these data, it may be deduced that ICT
abuse is a behavior better governed by the rules of compul-
sion (avoidance of discomfort, governed by negative rein-
forcement) rather than by those of impulsivity (search for
gratication, governed by positive reinforcement). In real-
ity, negative urgency as dened by the UPPS model does not
differ from the denition of compulsivity: the authors de-
ne negative urgency as the tendency to experience strong
impulses, often under conditions of negative affect, so that
those who score high on negative urgency engage in impul-
sive behaviors in order to alleviate negative effects despite
the damaging long-term consequences of these actions
(Whiteside & Lynam, 2001).
On eliminating common variance in one regression
model, it is observed that the set of impulsivity scales pre-
dicts, at most, 8% of the ICT abuse scales, and that only
positive urgency contributes signicantly to the models, al-
though in no case does this reach 7%. The exception is in-
stant messaging use/abuse, which would be better predicted
by negative urgency. In other words, while use of the mobile
phone and its applications would be linked to the grati-
cation they provide, instant messaging use/abuse would be
governed by the reduction of the discomfort caused by the
uncertainty of not knowing the content of the messages
or as a way of escaping discomfort by producing messages.
However, in both cases the contribution of the impulsivity
scales is minimal compared to that obtained when consid-
ering compulsivity (Pedrero-Pérez et al., 2020).
When the impulsivity scales are correlated with those of
prefrontal malfunction symptoms, the relationships with
the urgency and lack of perseverance scales are consistent,
and somewhat less so with lack of premeditation. The effect is
greater when related to problems of executive functioning, as
might be expected. Just as predictably, the urgency scales
also correlate strongly with problems of emotional control.
In contrast, sensation seeking has very small effect size in all
its correlations. The latter is probably more of a stable per-
sonality trait (Hughson et al., 2019), while the rest of the
UPPS-P scales are applied to tendencies of behavioral func-
tioning more dependent on the stimulus context.
The joint structural model links the three levels being
examined: symptoms of prefrontal malfunction, impulsivi-
ty and ICT use/abuse. What can be observed is the strong
capacity of prefrontal malfunction to predict all aspects of
impulsive behavior and the central role of positive urgency
on ICT abuse. Urgency in the search for reinforcement re-
duces reective capacity and favors involvement in the use
of ICT beyond prefrontal control due, as previously men-
tioned, to the failure of executive control mechanisms, but
also to a lack of control of emotional inputs. This model
suggests that the best way to improve the use and reduce
the abuse of ICTs would be the development of cognitive
stimulation and rehabilitation programs that improve the
higher behavior control mechanisms, relating both to ex-
ecutive and emotional aspects. Cognitive rehabilitation has
already shown its usefulness in the eld of addictions with
or without substances (Verdejo-García, Alcázar-Córcoles &
Albein-Urios, 2019).
The main limitation of the present study is, without
doubt, the sampling method. Diffusion through social
networks does not allow control of the quality of partic-
ipation, the motivation and sincerity of the participants,
nor, of course, generalization of results. The only way to
control the quality of the responses, at least globally, is to
obtain a sample large enough so that the specic weight of
inappropriate responses in the overall results is reduced.
Atypical scores were detected so that random responses or
inconsistent completion could be eliminated. The inter-
nal consistency and structural validity tests are also guar-
antees of correct completion. Nevertheless, this method of
information gathering has been gaining increasing inter-
est and its use is considered normal in psychosociological
research (Geisen & Murphy, 2020). Future studies should
nd sampling methods which allow generalization of the
In conclusion, the UPPS-P in its reduced 20-item ver-
sion is a consistent and structurally valid test for exploring
impulsivity with the multidimensional UPPS model. Given
the results, the impulsive components of ICT abuse are not
the central nucleus of the problem, unlike when compul-
sive components have been analyzed. This consideration
can guide the design of more effective interventions that
should probably be oriented towards improving cortical,
executive, and emotional control mechanisms, and the
ability to generate valid response alternatives, rather than
merely blocking or modifying excessive use behaviors.
Conflicts of interest
The authors declare no conicts of interest.
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ADICCIONES, 2020 · VOL. xx NO. x
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The compulsive habit model proposed by Everitt and Robbins has accumulated important empirical evidence. One of their proposals is the existence of an axis, on which each a person with a particular addiction can be located depending on the evolutionary moment of his/her addictive process. The objective of the present study is to contribute in addressing the identification of such axis, as few studies related to it have been published to date. To do so, the use/abuse of Information and Communication Technologies (ICT) was quantified on an initial sample of 807 subjects. Questionnaires were also delivered to measure impulsivity, compulsivity and symptoms of prefrontal dysfunction. Evidence of the existence of the proposed axis was obtained by means of Machine Learning techniques, thus allowing the classification of each subject along the continuum. The present study provides preliminary evidence of the existence of the Impulsivity-Compulsivity axis, as well as an IT tool so that each patient that starts getting treatment for an addiction can be statistically classified as “impulsive” or “compulsive.” This would allow the matching of each person with the most appropriate treatment depending on his/her moment in the addiction/abuse process, thus facilitating the individualized design of each therapeutic process and a possible improvement of the results of the treatment.
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Compulsiveness has been considered one of the core characteristics of addictive behaviours. One of the abusive behaviours that has acquired importance in recent times involves the use of mobile phones. The aim of this study is to obtain a version of the Obsessive-Compulsive Drug-Use Scale (OCDUS) to study the compulsivity associated with mobile phone abuse, its basic psychometric properties and the results of its application. The OCDUS-ICT was created and administered over the Internet, through instant messaging programs, social networks and e-mail, and anonymous and voluntary participation was requested. Additionally, MULTICAGE-ICT and the Inventory of Prefrontal Symptoms were administered. A sample of n=748 subjects, 33% males and 94% born and resident in Spain was obtained. The test obtained adequate values of internal consistency, applying different estimators. Confirmatory factor analysis of the theoretical scales yielded adequate fit indices. Obsessive-compulsive components were observed to become stronger as mobile phone use increased and approached abuse levels. OCDUS-ICT scales showed large correlations with prefrontal malfunction symptoms, especially Thoughts-Interference (r>0.80). In conclusion, OCDUS-ICT explores with psychometric accuracy the obsessive-compulsive components of mobile use/abuse, which are closely related to malfunctions in daily life attributable to the prefrontal cortex. If impulsivity has so far been the focus in the study of mobile phone abuse, the data from the present study suggest that greater attention should be paid to compulsivity as a factor in maintaining abuse.
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Due to the high accessibility and mobility of smartphones, widespread and pervasive smartphone use has become the social norm, exposing users to various health and other risk factors. There is, however, a debate on whether addiction to smartphone use is a valid behavioral addiction that is distinct from similar conditions, such as Internet and gaming addiction. The goal of this review is to gather and integrate up-to-date research on measures of smartphone addiction (SA) and problematic smartphone use (PSU) to better understand (a) if they are distinct from other addictions that merely use the smartphone as a medium, and (b) how the disorder(s) may fall on a continuum of addictive behaviors that at some point could be considered an addiction. A systematic literature search adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was conducted to find all relevant articles on SA and PSU published between 2017 and 2019. A total of 108 articles were included in the current review. Most studies neither distinguished SA from other technological addictions nor clarified whether SA was an addiction to the actual smartphone device or to the features that the device offers. Most studies also did not directly base their research on a theory to explain the etiologic origins or causal pathways of SA and its associations. Suggestions are made regarding how to address SA as an emerging behavioral addiction.
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This study investigates the predictive value of impulsivity traits (as measured by the UPPS-P impulsive behaviour scale) and relevant covariates (sociodemographics, gambling severity, dysphoric mood, other potentially addictive behaviours, and non-verbal intelligence) with regard to treatment dropout and level of adherence to therapy guidelines and instructions in patients with gambling disorder. Sixty six patients seeking treatment for gambling disorder, and recruited to participate in a larger protocol (G-Brain), were initially assessed in impulsivity traits and relevant covariates in the first six months after admission. Of these, 24 patients dropped out (DO) and 42 patients remained in therapy (NDO) during the subsequent 6-month followup period. A multivariate analysis of impulsivity subscales suggested prospective differences between DO and NDO, with affect-driven dimensions (positive and negative urgency) seemingly driving these differences. Among these, only positive urgency independently predicted a slight increase in the drop-out probability. In the NDO group, a higher degree of adherence to therapy was independently predicted by lower sensation-seeking scores and stronger awareness of gambling-related problems. Results suggest the presence of affect-driven impulsivity traits as dropout predictors in patients with gambling disorder. Awareness of gambling-related problems and lower sensation-seeking enhanced compliance with therapeutic guidelines and instructions.
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Objective: Impulsivity is a multidimensional construct that has an important role for the understanding of diverse psychopathologies and problematic behaviors. The UPPS-P impulsive behavior scale, measuring five distinct facets of impulsivity, has been subject to several studies. No study has investigated the clinical utility of this questionnaire amongst an unstable psychiatric population. The aim of the current study is to examine the psychometric properties of the short version of this scale in a psychiatric emergency unit. Method: The S-UPPS-P was administered to 1097 psychiatric patients in an emergency setting, where a subgroup of 148 participants completed a follow-up. The internal consistency, the construct validity, the test-retest reliability and the convergent validity of the scale were examined. Results: Confirmatory factor analyses supported a five-factor solution. Results indicated good psychometric properties across psychiatric diagnoses and gender. The S-UPPS-P was partially invariant across sexes. The authors have found differences on the loading of one item and on the thresholds of two items from lack of premeditation and positive urgency subscales. Conclusion: This validation study showed that the UPPS-P conserved good psychometric properties in an unstable psychiatric sample, indicating that the instrument can be utilized in such settings. Keywords: impulsivity, Short version, Reliability, validity, Psychiatric Emergency
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It is well established that poor inhibitory control confers both a vulnerability to, and maintenance of, addictive behaviors across the substance and behavioral spectrums. By comparison, the role of compulsivity in addictive behaviors has received less research focus. The neurocognitive literature to date is vast, and it is unclear whether there are any convincing lines of systematic evidence delineating whether and how aspects of impulsivity and compulsivity are shared and unique across different substance and behavioral addictive disorders. Such information has significant implications for our understanding of underlying mechanisms and clinical implications for assessing and treating neurocognitive deficits across addictions. Here, we conducted a systematic meta-review of the quantitative meta-analyses to date, specifically examining the neurocognitive functions central to impulsive-compulsive behaviors transdiagnostically across addictive behaviors. Out of 1186 empirical studies initially identified, six meta-analyses met inclusion criteria examining alcohol, cannabis, cocaine, MDMA, methamphetamine, opioid and tobacco use, as well as gambling and internet addiction. The pooled findings across the systematic meta-analyses suggest that impulsivity is a core process underpinning both substance and behavioral addictive disorders, although it is not equally implicated across all substances. Compulsivity-related neurocognition, by comparison, is important across alcohol and gambling disorders, but has yet to be examined systematically. The gestalt of findings to date suggests that both impulsivity and compulsivity are core constructs linked to addictive behaviors and may not be solely the secondary sequelae associated with the effects of prolonged substance exposure.
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There are a number of traits that are thought to increase susceptibility to addiction, and some of these are modeled in preclinical studies. For example, “sensation-seeking” is predictive of the initial propensity to take drugs; whereas “novelty-seeking” predicts compulsive drug-seeking behavior. In addition, the propensity to attribute incentive salience to reward cues can predict the propensity to approach drug cues, and reinstatement or relapse, even after relatively brief periods of drug exposure. The question addressed here is the extent to which these three ‘vulnerability factors’ are related; that is, predictive of one another. Some relationships have been reported in small samples, but here a large sample of 1,598 outbred male and female heterogeneous stock rats were screened for Pavlovian conditioned approach behavior (to obtain an index of incentive salience attribution; ‘sign-tracking’), and subsequently tested for sensation-seeking and novelty-seeking. Despite the large N there were no significant correlations between these traits, in either males or females. There were, however, novel relationships between multiple measures of incentive salience attribution and, based on these findings, we generated a new metric that captures “incentive value”. Furthermore, there were sex differences on measures of incentive salience attribution and sensation-seeking behavior that were not previously apparent.
The purpose of this chapter is to introduce emerging survey pretesting methodologies and compare these with traditional methods in the light of modern data collection technologies to consider where the standard approaches for pretesting can be improved. We begin by discussing the key limitations of traditional pretesting methods such as expert review, cognitive interviewing, and pilot testing for evaluating “modern” surveys. We then provide an overview of emerging pretesting methods including usability testing, eye tracking, and online pretesting. We discuss the advantages offered by these methods – particularly in terms of budget and schedule – and provide examples of how these methods can improve data quality. We conclude with a theoretical mode for the optimal combination of traditional and newer methods for pretesting modern surveys.
Trait impulsivity has long been proposed to play a role in aggression, but the results across studies have been mixed. One possible explanation for the mixed results is that impulsivity is a multifaceted construct and some, but not all, facets are related to aggression. The goal of the current meta-analysis was to determine the relation between the different facets of impulsivity (i.e., negative urgency, positive urgency, lack of premeditation, lack of perseverance, and sensation seeking) and aggression. The results from 93 papers with 105 unique samples (N = 36, 215) showed significant and small-to-medium correlations between each facet of impulsivity and aggression across several different forms of aggression, with more impulsivity being associated with more aggression. Moreover, negative urgency (r = 0.24, 95% [0.18, 0.29]), positive urgency (r = 0.34, 95% [0.19, 0.44]), and lack of premeditation (r = 0.23, 95% [0.20, 0.26]) had significantly stronger associations with aggression than the other scales (rs < 0.18). Two-stage meta-analytic structural equation modeling showed that these effects were not due to overlap among facets of impulsivity. These results help advance the field of aggression research by clarifying the role of impulsivity and may be of interest to researchers and practitioners in several disciplines.