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J Psychiatry Neurosci 2011;36(3) 165
Background: Impairments in self-regulatory behaviour reflect a deficit in executive functioning and decision-making, as well as higher
levels of self-reported impulsivity, and may be involved in the development and maintenance of addictive disorders. We sought to ex-
plore the association between self-reported impulsivity and neurocognitive measures, and their association with treatment outcome in
pathologic gambling. Methods: We assessed patients with pathologic gambling using executive functioning and decision -making tests
and self-report measures of impulsivity. Patients underwent cognitive–behavioural therapy (CBT) for pathologic gambling. Results: We
included 88 patients (8% women) in our study. High self-reported extravagance was associated with poor performance in the Iowa Gam-
bling Task (IGT)-ABCD version. High impulsiveness, low disorderliness, high exploratory excitability (trend), poor backward block span
and poor IGT-EFGH scores (trend) predicted dropout. We observed no self-reported or neurocognitive predictors of relapse or number of
treatment sessions attended. Limitations: Most participants were slot-machine gamblers seeking treatment. No follow-up data and no
control group were included in the study. The missing sample (i.e., individuals who were recruited and assessed in the pretreatment
stage but who chose not to begin treatment) had higher extravagance scores than the final sample. Conclusion: Neurocognitive reward
sensitivity was related to self-reported overspending behaviour. Self-regulatory impairments (especially rash impulsiveness and punish-
ment sensitivity) and executive dysfunction predicted only dropout of CBT in participants with pathologic gambling. Different neurocogni-
tive processes and personality traits might mediate treatment response to psychological therapy of pathologic gambling according to the
specific target variable assessed.
Research Paper
Effect of executive functioning, decision-making
and self-reported impulsivity on the treatment
outcome of pathologic gambling
Eva M. Álvarez-Moya, PhD; Cristian Ochoa, BS; Susana Jiménez-Murcia, PhD;
Maria Neus Aymamí, BS; Mónica Gómez-Peña, BS; Fernando Fernández-Aranda, PhD;
Juanjo Santamaría, BS; Laura Moragas, BS; Francesca Bove, BS; José M. Menchón, MD
Álvarez-Moya, Jiménez-Murcia, Fernández-Aranda — CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto
de Salud Carlos III, Spain; Álvarez-Moya, Jiménez-Murcia, Aymamí, Gómez-Peña, Fernández-Aranda, Santamaría, Moragas,
Bove, Menchón — Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain; Ochoa —Department of
Psych iatry and Clinical Psychobiology, University of Barcelona, Spain; Menchón — CIBER Mental Health (CIBERSAM), Instituto
Salud Carlos III, Spain
Introduction
Impairments in self-regulatory behaviour seem to be in-
volved in the development and maintenance of pathologic
gambling and other addictive disorders.1,2 From a neuro -
psychological point of view, this impairment reflects a deficit
in executive functioning and decision-making.3,4
Executive functioning includes functions such as cognitive
flexibility (set-shifting), which is associated with orbitofrontal
functioning, and working memory, planning and abstract
thinking, which are associated with dorsolateral prefrontal
functioning.5–7 However, decision-making seems to be mainly
associated with activation of the ventromedial prefrontal cor-
tex.5,8 People with pathologic gambling have shown impaired
Correspondence to: Dr. E.M. Álvarez-Moya, CIBERObn and Department of Psychiatry, University Hospital of Bellvitge, c/Feixa Llarga, s/n,
08907, L’Hospitalet de Llobregat, Barcelona, Spain; eva.alvarez@uab.cat
J Psychiatry Neurosci 2011;36(3):165-75.
Submitted Aug. 4, 2009; Revised Apr. 23, July 3, 2010; Accepted July 6, 2010.
DOI: 10.1503/jpn.090095
© 2011 Canadian Medical Association
performance in tasks measuring both concepts. Specifically,
studies report deficits in cognitive inhibition, complex execu-
tive functions and attention.9–11 This population also shows
impairments in decision-making.12–14 Decision- making im -
pairments are observed in impulsive individuals in general.
Specifically, impulsive individuals show an insensitivity
to variations in reward/loss magnitude of behavioural
decision- making tasks.15,16 Sensitivity to reward has been the
most studied aspect of decision-making. However, decision-
making is also guided by sensitivity to punishment,17 which
has received little attention in pathologic gambling, espe-
cially from a neurocognitive perspective.
Self-regulatory deficits may also manifest in certain per -
sonality traits such as impulsivity. Considering its multi -
dimensionality, at least 2 types of impulsivity have been pos-
tulated: rash impulsiveness (acting rashly when distressed)
and sensitivity to reward (greater response/activation to re-
warding stimuli). The latter is based on Gray’s Behavioural
Approach System.18 In the field of substance dependence,
some authors consider rash impulsiveness to be a risk factor
for uninhibited behaviour and for the progression from sub-
stance use to substance dependence, whereas sensitivity to re-
ward is considered to be associated more with motivation to
use substances than with substance dependence.19,20 However,
there is confusion regarding some impulsivity- related terms
that are not clearly classified into the previous 2-factor hy-
pothesis. For instance, sensation-seeking (similar to novelty -
seeking), which has been defined as a need for varied, novel
and stimulating experiences,21has been associated with
heightened sensitivity to the rewarding effects of drugs.22,23
Sensation-seeking has also been associated with reward-
seeking in animal studies,24 and it seems to be independent of
rash impulsiveness.25 However, many studies of pathologic
gambling use the terms impulsiveness and sensation -seeking
indistinctly, and most of them report high levels of both traits
in this population.26–28 Rash impulsiveness would represent a
failure to inhibit a behaviour that may result in negative con-
sequences, lack of reflection and planning, rapid decision-
making and action and carelessness.29,30 Given the definition of
both concepts (rash impulsiveness and sensation-seeking),
sensation- seekers are not necessarily careless or nonreflective.
As such, we should expect a stronger association between
sensation-seeking and sensitivity to reward than sensation -
seeking and rash impulsiveness.
The novelty-seeking factor of the Temperament and Char-
acter Inventory-Revised31 tool is considered to be a general
measure of impulsivity. However, its different subscales
seem to measure different components of this construct.
Exploratory excitability (reflecting sensation-seeking) and
extravagance (reflecting overspending behaviour and poor
planning) have been related to polymorphisms in the
dopamine (DA) D4 receptor (DRD4).32 These traits have been
considered to represent the exploratory, extravagant and
extro verted subtypes of the novelty-seeking factor. Con-
versely, the impulsive and monotony-avoiding subtypes
would be represented by the impulsiveness (representing un-
reflective and careless behaviour) and the disorderliness (re-
flecting disorganized, uncontrolled, antinormative behav-
iour) subscales.32 The literature about the relation between
Cloninger’s novelty-seeking subscales and the different com-
ponents of impulsivity is scarce.33,34 Nevertheless, considering
these findings in the framework of the previously mentioned
2-factor hypothesis, we may expect an association of explora -
tory excitability and extravagance with sensitivity to reward
on the one hand, and impulsiveness and disorderliness with
rash impulsiveness on the other. The distinction between
these concepts and their association with self-regulatory
deficits in pathologic gambling is understudied. Further, rela-
tively few studies appear to have examined the relations be-
tween these traits and treatment outcome.
In spite of the importance of impulsivity in the generation
and maintenance of pathologic gambling, the link between
neuropsychological and personality (self-report) measures of
impulsivity (as a whole) is relatively unexplored in the field
of pathologic gambling. In addition, only 1 study has focused
on the association of neuropsychological and personality
measures of impulsivity with treatment outcome in patho-
logic gambling. Goudriaan and colleagues35examined the
effect of neuro psychological functions (disinhibition, persev -
eration for reward, cognitive flexibility, decision-making)
and self-report measures of impulsivity and sensitivity to
punishment on vulnerability to relapse after psychological
treatment for pathologic gambling. They found that only dis-
inhibition and perseveration for reward (as measured by
neuropsychological tasks) were predictive of relapse at
1-year follow-up after treatment. No other neuropsychologic -
al predictors were identified, and no self-report measure was
predictive of relapse. They concluded that neuropsychologic -
al measures, particularly disinhibition and perseveration for
reward, are more powerful predictors of treatment outcome
than personality measures. In this regard, Forbush and col-
leagues36 explored the predictive power of neuropsychologic -
al (general intellectual functioning, executive functioning,
decision- making) versus personality (general personality and
impulsivity) measures in a group with diagnosed pathologic
gambling compared with healthy controls. They generated
2 neuropsychological factors and 2 personality factors (by
factor analysis of the different measures) and used these
converted variables as explanatory variables. In contrast to
Goudriaan and colleagues,35 Forbush and colleagues36 found
that personality measures were better predictors of a patho-
logic gambling diagnosis than neuropsychological functions.
Both research groups used different outcome measures, but
to our knowledge, only these 2 studies have addressed the
specific role of neuropsychological and personality measures
in pathologic gambling.
Differentiating the specific role of every measure may help
clarify the mechanisms underlying problem gambling behav-
iour. Adinoff and colleagues37 concluded that the different be-
havioural manifestations of impulsivity may correspond to
different neurocognitive constructs with specific neuroanatom-
ical correlates. Then, impulsivity should be described not only
in terms of phenotypes (as measured by self-report tests) but
also from an endophenotypic/neuropsychological point of
view. These authors recommend the study of the relation be-
tween impulsive behaviours, neurobiological impairments and
Álvarez-Moya et al.
166 J Psychiatry Neurosci 2011;36(3)
Neurocognition, impulsivity and treatment outcome in pathologic gambling
J Psychiatry Neurosci 2011;36(3) 167
risk of relapse in addictive disorders. Llewellyn38 also high-
lighted the importance of exploring the relation between
neuro psychological measures of risk-related decision-making
and personality traits.
In sum, very little research about the link between neuro -
cognitive (endophenotypical) and self-report (exophenotyp -
ical) measures of both impulsivity and self-regulatory deficits
has been done, particularly in the area of pathologic gam-
bling. Second, the association between these constructs and
treatment outcome in pathologic gambling has received little
attention. In this context, we aimed to determine the relations
between self-reported impulsivity, neurocognitive functions
(executive functioning and decision-making, including both
reward and punishment sensitivity) and treatment outcome
(including both relapse and dropout) in pathologic gambling.
Our specific objectives were, first, to establish the pattern of
associations between neurocognitive variables and self-report
(personality) measures of impulsivity in pathologic gambling
and, second, to determine the predictive power of neuro -
psychological and personality meas ures in relation to relapse
and dropout during psycho logical treatment for pathologic
gambling.
Methods
Participants
We recruited consecutive patients seeking treatment for
pathologic gambling in a Pathological Gambling Unit
(Department Psychiatry, University Hospital of Bellvitge,
Barcelona, Spain) for participation in our study. Pathologic
gambling was diagnosed according to DSM-IV-TR criteria.39
Entry into the study was from November 2005 to September
2007. Exclusion criteria at intake were age younger than 18 or
older than 65 years, history of neurologic disorder or head in-
jury, psychotic disorder and history of substance abuse in the
previous 3 months. Substance abuse was measured with the
substance use disorders module of the Structured Clinical
Interview for DSM-IV Axis I Disorders.40 We assessed pa-
tients with the South Oaks Gambling Screen (SOGS).41
This study was carried out according to the latest version
of the Declaration of Helsinki. The University Hospital of
Bellvitge Ethics Committee of Clinical Research approved
this study, and we obtained informed consent from all final
participants.
Instruments and measures
Self-report measure of impulsivity
Novelty-seeking is 1 of 4 temperamental factors measured by
the Temperament and Character Inventory-Revised (TCI-R)
tool.31 It reflects several forms of impulsivity,31 and its reliabil-
ity (internal consistency) was 0.77 (Cronbach’s α) in the Span-
ish adaptation of the TCI-R.42 Given our interest in the differ-
ent aspects of impulsivity, rather than the total score, we
focused on the 4 novelty-seeking subscales: exploratory ex-
citability (NS1), impulsiveness (NS2), extravagance (NS3)
and disorderliness (NS4). The NS2, NS3 and NS4 subscales
showed low intercorrelations (all below 0.4) in our sample,
and NS1 (exploratory excitability) was completely independ -
ent of the other 3 subscales.
Neurocognitive measures
The Wisconsin Card Sorting Test (WCST)43 is considered to
be sensitive to frontal lobe dysfunction. It measures strategic
planning, organized searching, using environmental feed-
back to shift cognitive sets, directing behaviour toward
achieving a goal and modulating impulsive responding. The
materials consist of 2 decks of 64 cards that are numbered
from 1 to 64 on the lower left corner of the reverse side to
ensure a standard order of presentation. The participant must
sort response cards to 4 key cards according to colour, form
or number (categories) and alter their approach as shifts in
the sorting principle occur. The examiner gives only feedback
of “correct” or “incorrect” on every trial. The test finishes
when the examinee completes either 6 categories or 128 trials.
The WCST provides objective scores for overall success and
for specific sources of difficulty in the task such as persevera-
tion or conceptualization. For the present study, we used the
number of completed categories and the percentage of per -
sev erative and nonperseverative errors.
The Stroop Colour and Word Test44 measures cognitive
flexibility, involuntary attention, ability to override a prepo-
tent response (reading a lexical stimulus) and concentration
effectiveness.45 It consists of a word page (first list) with
colour words printed in black ink, a colour page (second list)
with “Xs” printed in colour and a colour–word page (third
list) with names of colors printed in an incongruent colour.
The examinee must read words (first list) or name ink colour
(second and third lists) as quickly as possible within a time
limit (45 s). The test yields 3 scores based on the number of
items correctly completed on each of the 3 stimulus sheets,
i.e., number of read words in first list (W), number of colour-
named items in second list (C) and number of colour-named
words in third list (CW). In addition, Golden44 proposed an
interference score, which is useful in determining the indi -
vidual’s cognitive flexibility, creativity and reaction to cogni-
tive pressures. This score is computed according to the fol-
lowing formula: #CW – ([#W ×#C] ÷[#W + #C]). Higher
scores in this index suggest better cognitive inhibition (better
interference control).
The Trail Making Test, parts A and B (TMT),46 is an easily
administered test of visual conceptual and visuomotor track-
ing involving motor speed, attention and the ability to alter-
nate between cognitive categories (set-shifting). This test con-
sists of 2 parts. Part A is a page with 25 numbered circles
randomly arranged. Participants are instructed to draw lines
between the circles in increasing sequential order until they
reach the circle labelled “end.” Part B is a page with circles
containing the letters A through L and 13 numbered circles
intermixed and randomly arranged. Participants are in-
structed to connect the circles by drawing lines alternating
between numbers and letters in sequential order, until they
reach the circle labelled “end.” If individuals make mistakes,
the mistakes are quickly brought to their attention, and they
continue from the last correct circle. The test takes about
5–10 minutes to complete. Scores are the amount of time
taken to complete each part. To control for individual differ-
ences in motor speed, we generated a score based on the sub-
traction of time to complete part A from time to complete
part B. Higher scores suggested set-shifting difficulties.
The Iowa Gambling Task (IGT), versions ABCD and
EFGH,17 is a computerized test measuring sensitivity to re-
ward (i.e., to what extent large immediate gain outweighs
even larger future loss; ABCD version) and sensitivity to pun-
ishment (i.e., to what extent immediate punishment out-
weighs high reward; EFGH version). It seems that patients
with ventromedial prefrontal lesions perform poorly on both
versions.17 Participants receive standard instructions and are
informed that the aim of the game is to win as much money as
possible. In the ABCD version, 4 decks of cards are presented
on the computer screen. The participant has to pick cards after
which the amount of money the participant has won or lost is
depicted on the computer screen. Winning or losing money is
indicated by a green bar that increases or decreases. The game
consists of 100 trials. The ABCD version is focused on re-
wards. Decks A and B are associated with great immediate
reward but even greater future punishment. These are known
as the disadvantageous decks. Decks C and D give lesser
rewards but also lesser losses, so they result in a net gain in
the long run. The layout and structure of the EFGH version is
very similar. Instructions are the same, but this version is
focused on punishment. Decks E and G are associated with
great immediate punishment but even greater future reward.
Decks F and H are associated with lesser punishments but
also much lesser rewards, so they are the dis advantageous
decks. Information about advantageous/ disadvantageous
decks is not given to the participant; they have to infer this in-
formation based on feedback. The 100 trials of each version
are divided into 5 equal blocks. The final score reflects the
number of cards selected from advantageous decks minus
disadvantageous decks for each block (ABCD version: [C+D]
– [A+B]; EFGH version: [E+G] – [F+H]). We counterbalanced
the order of administration of both versions, which were also
administered in different sessions.
The Controlled Oral Word Association Test47 is also known
as the FAS test of verbal fluency in reference to the letters
F-A-S, which are used for word generation. Its purpose is the
spontaneous production of words beginning with a given let-
ter or of a given class within a limited amount of time (verbal
association fluency). It measures the individual’s ability to
spontaneously produce words pertaining to a specific pho -
nemic category. This test presumably reflects both preserva-
tion of word knowledge and ability to self-initiate verbal out-
put48 (i.e., executive functioning). The participant is asked to
produce as many words as possible beginning with a given
letter in 1 minute. Proper nouns, repetitions and variations
are inadmissible. In Spanish, the letters P-M-R are used in-
stead of F-A-S.49 The score is the sum of all admissible words
for the 3 letters.
The Backward Digits Span task50 of the Wechsler Memory
Scale, third edition, requires the examiner to verbally pre-
sent digits at a rate of 1 per second. The participant is asked
to repeat the list of digits after the examiner has completed
delivering it. The forward test requires the participant to re-
peat the digits verbatim. The backward test requires the
participant to repeat the digits in reverse order. The number
of digits increases by 1 until the participant consecutively
fails 2 trials of the same digit span length. Performance on
the backward digit span task measures verbal working
memory by requiring internal manipulation of mnemonic
representations of verbal information in the absence of ex-
ternal cues.51Given our focus on executive functions, we
used the digit span length in the backward version (back-
ward digits span [BDS]).
The Corsi blocks task52 apparatus consists of a set of 9 iden-
tical blocks irregularly positioned on a plastic board. The ex-
perimenter points to a series of blocks at a rate of 1 block per
second. Subsequently, the participant is required to point to
the same blocks in their order of presentation (forward) or in
the reversed order (backward). The length of the block se-
quences increases until recall is no longer correct. The Corsi
blocks task involves visuospatial and executive resources by
requiring backward recall of the path presentations in the
task. Upon presentation of a series of block positions, a repre-
sentation of the path is constructed and maintained in visuo -
spatial working memory. If the sequence has to be repro-
duced in reverse order, executive control is required.53 For the
present study, we analyzed the blocks span in the backward
version (backward blocks span [BBS]).
Treatment outcome
Dropout
Milton and colleagues54 and Robson and Edwards55 defined
dropout as terminating treatment before completing the pre-
determined treatment program (see below) that was ad -
ministered. This was coded as a binary variable (dropout/
nondropout). We used the number of treatment sessions at-
tended to analyze dropout from a continuous perspective.
Relapse
Ledgerwood and Petry56 defined relapse as the presence of
any episode of gambling during treatment associated with a
subjective sense of loss of control over gambling. This vari-
able was quantified for all patients who started treatment (in-
cluding those who dropped out during treatment). Relapse
was coded as a binary variable (relapse/nonrelapse) and con-
tinuously (number of relapses during treatment).
Procedures
We first assessed patients with a semistructured face-to-
face interview as part of the usual protocol in our unit. This
in terview includes the assessment of substance abuse/
dependence and is usually performed by psychologists or
psychiatrists (minimum 10 yr of specialization in pathologic
gambling). Exclusion criteria for the current study were iden-
tified at this time. The patients who agreed to participate in
the study provided written, informed consent after receiving
written and oral explanation of the procedures.
Patients completed the TCI-R during a second session. The
Álvarez-Moya et al.
168 J Psychiatry Neurosci 2011;36(3)
Neurocognition, impulsivity and treatment outcome in pathologic gambling
J Psychiatry Neurosci 2011;36(3) 169
neurocognitive assessment was then administered by an ex-
perienced neuropsychologist during 2 sessions of 45 minutes’
duration before starting treatment. We also administered the
Wechsler Adult Intelligence Scale, third edition (WAIS-III)57
vocabulary subtest as a measure of estimated intelligence.45
Treatment consisted of a cognitive–behavioural outpatient
group therapy (CBT) based on a standardized protocol.58 It
consisted of 16 weekly outpatient sessions (90 min each) with
a total of 10–14 patients per group. The main objective of the
treatment was training patients to put into practice CBT
strategies to achieve full and definitive abstinence from gam-
bling. Techniques used were psychoeducation on the dis -
order, stimulus control, response prevention, cognitive re-
structuring, reinforcement and self-reinforcement, skills
training and relapse prevention techniques. The therapist
recorded dropouts and relapses based on patients’ oral re-
ports and written diaries and relatives’ confirmation.
Statistical analysis
We performed all statistical analyses with SPSS version 15.0.1
for Windows. We compared background characteristics (age,
education, WAIS-III vocabulary score, duration of gambling
problem and SOGS total score, sex, marital status, employ-
ment, use of medication) of patients who dropped out versus
those who did not, and individuals who relapsed versus
those who did not, using analysis of variance (ANOVA) for
quantitative variables and the χ2test for qualitative variables.
The association between self-report measures of impulsiv-
ity (TCI-R novelty-seeking subscales) and neurocognitive
measures of decision-making and executive functioning was
assessed through linear regression models. Considering the
natural direction of the relation between endophenotypes
and external phenotypes, we used neurocognitive and
decision-making measures as independent explanatory vari-
ables, and TCI-R novelty-seeking subscales were used as de-
pendent variables. We generated 4 models (1 for each sub-
scale) by entering all independent variables in 1 block. All
4 models were adjusted for age, sex and score in the WAIS-III
vocabulary subtest (entered in block 2).
We measured the association between neurocognitive,
decision-making and self-report measures on the one hand
and treatment outcome on the other through logistic and
linear regression models. We assessed 4 models: 2 logistic re-
gression models for categorically coded dropout and relapse
and 2 linear regression models for number of treatment ses-
sions attended and number of relapses, respectively. The in-
dependent measures were entered as a block to explore the
relative contribution of each predictor to treatment outcome.
Results
Patients
We assessed a total of 115 patients, but 27 (23.5%) rejected
starting treatment. The final sample consisted of 88 patients
with pathologic gambling (8% were women), with a mean
age of 36.7 years (standard devision [SD] 11.1 yr). The mean
score on the SOGS41 was 10.3 (SD 2.7). The patients had a
mean of 10.7 (SD 3.2) years of education, 83.5% were em-
ployed, 52.9% were married, 34.1% were single and the re-
maining 13% were separated or divorced. Most participants
(91.7%) were mainly slot-machine gamblers and 23.1% had
several gambling problems, including slot machines, bingo,
casino, lotteries and cards. The mean duration of the gam-
bling problem was 5.6 (SD 5.7) years. Only 17.4% of patients
were taking psychiatric medication, primarily antidepres-
sants: 75.0% selective serotonin reuptake inhibitors (SSRIs)
and 37.5% benzodiazepines.
In relation to patients who started treatment, Student t
tests revealed that those who rejected treatment exhibited
higher levels of TCI-R extravagance (NS3; t90.9 = 5.0, p< 0.001)
and a slightly higher percentage of non per sev er ative errors
in the WCST (t108 = 2.0, p= 0.048).
The treatment outcome groups were as follows: 45 patients
showed no dropout or relapse, 12 patients had a relapse,
20 patients had dropout and 7 patients showed both relapse
and dropout during treatment (we missed information about
relapse from 4 patients who had dropouts). Table 1 shows
the main sociodemographic and clinical characteristics per
group. We identified no statistically significant group differ-
ences in any of the variables presented in Table 1.
Relation between self-report measures of impulsivity and
neurocognitive measures
Table 2 shows the result of bivariate correlations between
self-report and neurocognitive measures. Although several
correlations were significant at a 0.05 level, no statistically
significant correlations were observed after Bonferroni cor-
rection, which was set up at a 0.001 level.
Regarding the association analysis, only the adjusted model
for the NS3 subscale (extravagance) was statistically significant
(F13,67 = 2.26, p= 0.015). Specifically, the IGT-ABCD net score
was negatively associated with the NS3 score (B = –0.057, stan-
dard error = 0.026, β= –0.245, t= –2.17, p= 0.033). No other
neurocognitive index was statistically associated with the NS3
score. No other model was statistically significant (NS1,
p= 0.27; NS2, p= 0.13; NS4, p= 0.37). These results remained
after excluding medicated patients from the sample.
Effect of neurocognitive and self-report measures on
treatment outcome
Table 3 shows means and standard deviations of personality
and neurocognitive measures according to the presence of
dropout or relapse.
Dropout
The result of the logistic regression analysis for dropouts is
shown in Table 4. Dropout during treatment was signifi-
cantly predicted by high NS2 (impulsiveness) and low NS4
(disorderliness) scores, as well as lower number of blocks
recalled at the BBS. High NS1 (exploratory excitability) and
lower number of advantageous choices in the IGT-EFGH pre-
dicted dropouts at a trend level. The model was statistically
significant (χ214 = 34.71, p= 0.002) and explained a moderate
to high percentage of variance in dropouts (Nagelkerke
R2= 0.647). No differences in these results were observed af-
ter adjustment for age and sex. The exclusion of medicated
patients yielded the same pattern of effects, but the TCI-R
NS4 subscale lost statistical significance (p= 0.19).
Regarding the linear regression analysis for number of
treatment sessions attended, the model was not statistically
significant (F14,23 = 1.165, p= 0.36). This result remained after
excluding medicated patients from the analysis.
Relapse
The logistic regression model for relapse did not achieve sta-
tistical significance (χ214 = 14.21, p= 0.43). The linear regression
model for number of relapses also failed to achieve statistical
significance (F14,14 = 0.847, p= 0.62). These results remained
after we excluded medicated patients from the analyses.
Discussion
The present study focused on the relations between neuro -
cognitive measures (executive functioning and decision-
making), self-report measures of impulsivity and treatment
outcome in pathologic gambling.
Relation between self-report measures of impulsivity and
neurocognitive measures
We observed that individuals with pathologic gambling who
had high levels of TCI-R novelty-seeking extravagance (i.e.,
unwary, overspending individuals who were outrageous in
relation to money, energy and feelings) showed higher sensi-
tivity to reward. Other authors have also found a relation be-
tween some aspects of impulsivity and sensitivity to reward,
as measured by the IGT.59–61 We can conclude from these
Álvarez-Moya et al.
170 J Psychiatry Neurosci 2011;36(3)
Table 2: Pearson product-moment correlations between self-report (TCI-R novelty-seeking subscales) and neurocognitive measures
WCST % errors IGT net score
TCI-R subscale COWAT
SCWT
interf. BDS BBS
TMT B-A
difference
WCST
categories Pers. Nonpers. ABCD EFGH
Exploratory excitability
r0.020 0.013 0.002 0.206 –0.030 –0. 062 –0.097 0.138 0.095 0.061
pvalue 0.83 0.89 0.99 0.035 0.76 0.54 0.33 0.17 0.35 0.52
Impulsiveness
r0.056 0.171 0.061 0.131 0.028 0.118 –0. 284 0.160 0.050 0.070
pvalue 0.54 0.07 0.54 0.18 0.7 8 0.24 0.004 0.11 0.62 0.47
Extravagance
r0.049 0.010 0.128 –0.014 0.037 –0.226 0.165 0.272 –0.232 –0.019
pvalue 0.60 0.92 0.19 0.89 0.7 1 0.023 0.10 0.006 0.0 19 0.85
Disorderliness
r–0.048 0.152 0.003 0.099 0.047 –0.026 –0.098 0.142 –0.192 0.044
pvalue 0.61 0.10 0.98 0.32 0.64 0.79 0.33 0.16 0.06 0.65
BBS = Backward Blocks Span;52 BDS = Backward Digits Span;50 COWAT = Controlled Oral Word Association Test;47 IGT = Iowa Gambling Task;17 Nonpers. = nonperseverative;
Pers. = perseverative; SCWT interf. = Stroop Colours and Words Test Interference;44 TCI-R = Temperament and Character Inventory-Revised;31,42 TMT = Trail Making Test;46 WCST %
errors = Wisconsin Car d Sorting Test43 % of errors.
Table 1: Sociodemographic and clinical characteri stics of the treatment outcome groups of patients with
pathologic gambling
Group; mean (SD)*
Characteristic No relapse, no
dropout, n= 45 Relapse, n= 12 Dropout, n= 20
Relapse and
dropout, n= 7
Age, y r 37.4 (10.8) 40.1 (12.2) 32.1 (6.7) 36.3 (14.4)
Sex, male:female 2:43 1:11 2:18 2:5
Education, yr 10.6 (2.7) 11.8 (3.3) 10.7 (4.1) 10.9 (3.7)
WAIS-III vocabulary
subtest score 34.9 (8.4) 38.2 (9.8) 36.0(7.4) 33.7 (10.0)
Marital status, %
Single 27.9 45.5 40.0 28.6
Married 58.1 45.5 50.0 42.8
Divorced 14.0 9.0 10.0 28.6
Employed, % 83.7 90.9 85.0 85.7
Duration of pathologic
gambling, yr 6.3 (6.4) 6.7 (5.2) 4.6 (5.6) 3.6 (1.7)
Medicated, % 10.5 22.2 23.1 25.0
SOGS score 9.9 (2.6) 10.5 (2.6) 9.8(2.9) 12.4 (2.7)
*Unless otherwise indicated.
SD = standard deviation; SOGS = South Oaks Gambling Screen;41 WAIS-III = Wechsler Adult Intelligence Scale, third edition.57
Neurocognition, impulsivity and treatment outcome in pathologic gambling
J Psychiatry Neurosci 2011;36(3) 171
studies that particularly poor planning is associated with
high sensitivity to reward. High scores in the TCI-R novelty-
seeking extravagance subscale indicate lack of both caution
and farsighted behaviour, which can be related to poor plan-
ning abilities. Our results add support to the literature in this
regard. We can hypothesize that the extravagance subscale
is the most related to cognitive impulsivity or reward-
discounting (i.e., the preference for smaller, immediate re-
wards over larger, delayed rewards), which is associated
with IGT-ABCD performance.62 High scores in the TCI-R
novelty-seeking extravagance subscale have also been related
to low baseline cerebral availability of the type 1 cannabinoid
receptor (CB1R) in healthy volunteers,63 hypercortisolemia in
depressed patients64 and a higher level of tobacco dependence.65
Unlike other studies,16,66 we found no association between
other aspects of self-reported impulsivity, such as novelty-
seeking impulsiveness and exploratory excitability, and
neuro cognitive measures. We must take into account that the
studies measuring the association between impulsivity (as a
whole) and neurocognition use different samples and instru-
ments to assess these concepts, so the comparison across
studies may be difficult. In fact, we know of no studies
Table 3: Personality (TCI-R novelty-seeking subscal es) and neurocognitive measures according to dropout
and relapse
Outcome; mean (SD)
Dropout Relapse
Measure No, n= 57 Yes, n= 31 No, n= 65 Yes, n= 19
TCI-R subscale
Exploratory excitability 29.1 (4.7) 29.7 (5.1) 29.6 (4.8) 28.9 (4.8)
Impulsiveness 24.5 (4.7) 26.3 (5.0) 24.4 (4.8) 27.9 (4.3)
Extravagance 31.0 (6.0) 33.5 (6.5) 31.3 (6.2) 33.5 (6.7)
Disorderliness 20.8 (4.9) 20.1 (4.2) 20.2 (4.9) 21.2 (3.7)
COWAT 40.9 (13.3) 35.8 (10.4) 39.6 (12.0) 38.9 (14.8)
SCWT interference –0.3 (11.2) –1.5 (11.6) –1.3 (11.2) 0.3 (10.3)
BDS 6.5 (2.3) 5.7 (1.8) 6.4 (2.2) 6.0 (2.1)
BBS 7.5 (1.8) 6.5 (2.2) 7.5 (1.8) 6.8 (2.1)
TMT B-A difference 48. 7 (43.8) 66.5 (51.3) 51.5 (43.8) 53.6 (43.7)
WCST categories 4.1 (2.0) 4.7 (1.6) 4.3 (1.9) 4.5 (1.9)
WCST % perseverative errors 21.1 (14.3) 18.5 (10.8) 20.4 (13.8) 17.5 (10.1)
WCST % nonperseverative errors 14.2 (8.1) 14.3 (7.5) 13.9 (7.8) 15.5 (8.1)
IGT-ABCD net score 3.1 (22.9) –4.2 (28.7) 1.8 (24.7) –2.1 (27.2)
IGT-EFGH net score 6.0 (26.7) 0.6 (24.8) 4.5 (28.6) 5.2 (19.6)
BBS = Backward Blocks Span;52BDS = Backward Digits Span;50COWAT = Controlled Oral Word Association Test;47IGT = Iowa
Gambling Task;17 SCWT = Stroop Colo urs and Words Test;44 TCI-R = Temperament and Character Inventory-Revised;31,42 TMT = Trail
Making Test;46 WCST = Wisconsin Card Sorting Test.43
Table 4: Logistic regression analysis for dropouts (enter method)
Measure B
Standard
error Wald
Degrees of
freedom pvalue OR (95% CI)
TCI-R subscale
Exploratory excitability 0.293 0.172 2.905 1 0.09 1.341 (0.957–1.879)
Impulsiveness 0.346 0.171 4.089 1 0.043 1.413 (1.011–1.977)
Extravagance –0.010 0.092 0.012 1 0.91 0.990 (0.827–1.185)
Disorderliness –0.375 0.161 5.432 1 0.020 0.688 (0.502–0.942)
COWAT 0.943 0.679 1.929 1 0.16 2.569 (0.678–9.726)
SCWT interference –0.081 0.100 0.661 1 0.42 0.922 (0.758–1.121)
BDS 0.025 0.109 0.052 1 0.82 1.0 25 (0.828–1.270)
BBS –0.057 0.048 1.383 1 0.24 0.945 (0.860–1.039)
TMT B-A difference 0.032 0.054 0.342 1 0.56 1.032 (0.929–1.147)
WCST categories < 0.001 0.012 0.001 1 0.97 1.000 (0.977–1.025)
WCST % pers. errors –0.453 0.343 1.744 1 0.19 0.636 (0.325–1.245)
WCST % nonpers. errors –0.615 0.304 4.084 1 0.043 0.541 (0.298–0.982)
IGT-ABCD net score –0.025 0.020 1.549 1 0.21 0.976 (0.939–1.014)
IGT-EFGH net score –0.039 0.021 3.499 1 0.06 0.962 (0.924–1.002)
Constant –4.627 8.022 0.333 1 0.56 0.010 —
BBS = Backward Blocks Span;52BDS = Backward Digits Span;50CI = confidence interval; COWAT = Controlled Oral Word Association Test;47
IGT = Iowa Gambling Task;17nonpers.= nonperseverative; OR = odds ratio; pers. = perseverative;SCWT = Stroop Coloursand Words Test;44
TCI-R = Temperamentand Character Inventory-Revised;31,42 TMT= Trail Making Test;46 WCST = WisconsinCard Sorting Test.43
assessing the relation between the TCI-R novelty-seeking
subscales and neurocognitive function. Even so, other in -
vestigations have also failed to find associations between
sensation -seeking (represented by exploratory excitability in
the present study) and decision-making in other samples
with addictive behaviours such as cigarette smokers67 or
under graduate students.59 In the same line, Zermatten and
colleagues59 assessed the relation between the UPPS Impul-
sive Behaviour Scale68(measuring urgency, premeditation, per-
severance and sensation-seeking) and the IGT-ABCD in under-
graduate students, and they only found an association between
lack of premeditation (which would be close to the novelty-
seeking extravagance subscale) and poor decision-making.
Effect of neurocognitive and self-report measures on
treatment outcome
Relapse
In contrast to the study by Goudriaan and colleagues,35 who
found that neurocognitive measures, more than self-report
measures, were the most predictive of relapse in pathologic
gambling, no self-report measure of impulsivity or neurocog-
nitive measures were predictive of relapse (both from a cat -
egorical or a continuous approach) in the present study. This
finding suggests that self-reported impulsivity, executive
functioning and decision-making do not mediate relapse
during treatment in pathologic gambling, so other factors,
such as other personality traits, psychopathological status
and motivation at the beginning and during treatment,
should be explored.
In addition, contrary to what should be expected, some sta-
tistically nonsignificant trends (Table 3) suggested that those
who relapsed during treatment tended to have better cognitive
inhibition and lower perseverative tendencies. This means that
relapse during treatment could not be attributed to poor
neuro cognitive performance. These are preliminary and non-
significant results that need corroboration in future studies.
The lack of agreement between the present results and
those of Goudriaan and colleagues may reflect the use of dif-
ferent self-report measures in both studies, as well as the fact
that Goudriaan and colleagues measured relapse at 1-year
follow-up, whereas in the present study this measure was
taken during treatment. This might suggest that the pro -
cesses controlling vulnerability to relapse are different during
treatment and follow-up. Whereas risk of relapse would not
be related to self-reported impulsivity or neuro cognitive
function during treatment, the long-term maintenance of ab-
stinence would require the intervention of neurocognitive/
endophenotypical markers, such as perseveration for reward
and disinhibition.
Finally, we should consider that sample-specific factors
such as a small sample size or the main presence of slot-
machine gamblers may have masked the present results.
Dropout
We found that dropout during treatment (from a categorical
point of view) was predicted by both self-report measures and
neurocognitive variables. High TCI-R impulsiveness was pre-
dictive of dropouts. High TCI-R exploratory excitability also
predicted dropout at a trend level. These results suggest
that especially rash impulsiveness and, to a lesser degree,
sensation - seeking are involved in risk for dropout in patho-
logic gambling, whereas no impulsivity trait has an influence
on relapse. In addition, low TCI-R disorderliness (i.e., strict
regimentation, organization, rigidity and overcontrol), which
correlates negatively with impulsivity, also predicted drop out.
The latter finding may be related to an excessive sense of
guilty (frequently described in pathologic gambling69) or false
beliefs about treatment or the therapist that yield emotions,
including apathy, discouragement and shame, that finally lead
patients with pathologic gambling to drop out of treatment.70
From another point of view, Vassileva and colleagues61 ob-
served that high scores in antisocial personality were associ-
ated with better IGT-ABCD performance (reflecting sensitivity
to reward from a neuro cognitive perspective) in substance-
dependent individuals, suggesting that this trait was related to
better cognitive impulse control. High TCI-R disorderliness
scores are associated with antisocial traits, which in the present
study (similar to the study by Vassileva and colleagues61) were
associated with lower risk of dropout. Along these lines, Gullo
and Dawe71 stated that impulsivity also has positive aspects
(see Dickman72 and Caci and colleagues73 for the concept of
functional v. dysfunctional impulsivity). However, we must
take into account that the relation between low disorderliness
and dropout in the present study lost statistical significance af-
ter we excluded medicated patients from the sample, so the as-
sociation between this trait and dropout might be circum-
scribed to special characteristics of patients taking medica tion.
Moreover, poor spatial working memory (suggestive of ex-
ecutive dysfunction) was associated with greater risk of
dropout. Working memory deficits have also been reported
in people with gambling problems.74 The present results sug-
gest that this deficit may confer higher risk for dropout
among those who seek treatment.
Poor IGT-EFGH performance was also associated with
higher risk of dropout at a trend level, suggesting that those
individuals who drop out of treatment tend to show an in-
creased sensitivity to punishment and, in turn, an insensitivity
to the future consequences of their actions/decisions.3,17 This
finding suggests that individuals with pathologic gambling
do not consider the future consequences of their actions when
they decide to give up treatment, suggesting ventro medial
prefrontal cortex dysfunction.75 Therefore, rash impulsiveness,
sensation-seeking and strict regimentation, as well as poor
spatial working memory and increased sensitivity to punish-
ment, should be a target for additional specific interventions
in pathologic gambling to enhance therapeutic adherence.
Finally, no association between the neurocognitive and
self-report measures assessed and number of treatment ses-
sions attended was identified. There are no studies about the
relation between neurocognitive function and number of
treatment sessions attended in pathologic gambling. Regard-
ing the relation between self-reported impulsivity and num-
ber of treatment sessions attended, no studies have been pub-
lished in the field of pathologic gambling. However, this
association was studied by Patkar and colleagues76 in a
Álvarez-Moya et al.
172 J Psychiatry Neurosci 2011;36(3)
Neurocognition, impulsivity and treatment outcome in pathologic gambling
J Psychiatry Neurosci 2011;36(3) 173
sample of cocaine-dependent patients attending a 12-week,
intensive outpatient treatment program, and they also failed
to find an association between self-reported impulsivity and
the number of treatment sessions attended. Therefore, more
studies are needed in this respect.
To our knowledge, no other studies have examined the as-
sociation between neuropsychological functions and dropout
rates in pathologic gambling, so more research is needed to
corroborate these findings.
Limitations
The present results must be assessed in the context of several
limitations. First, most participants were slot-machine gam-
blers, and all of them were seeking treatment for this problem.
This may affect the generalizability of our findings. Second,
no follow-up data were available to confirm the maintenance
of findings. Third, no control group was included, so we can-
not conclude that the deficits that we observed are specific for
pathologic gambling. Finally, the missing sample (i.e., indi-
viduals who were recruited and assessed in the pretreatment
stage but who chose not to begin treatment) differed from the
final sample in some meas ures of personality and executive
functioning, so the final sample might have been biased to-
ward a “healthier” group of people with pathologic gambling.
Conclusion
In sum, the present results suggest an association between
overspending behaviour (extravagance in the present study)
and sensitivity to reward in pathologic gambling. Treatment
outcome, specifically dropout, was predicted by personality
measures suggestive of deficits in self-regulation, (i.e., impul-
siveness, understood as unreflective and careless behaviour)
and (at a trend level) sensation-seeking, as well as by strict
regimentation. Poor spatial working memory, suggesting ex-
ecutive dysfunction and sensitivity to punishment, reflecting
insensitivity to the future, were also predictive of dropout. As
far as we know, this is the first study that analyzes the effect
of neurocognitive and self-report measures of impulsivity and
self-regulatory deficits on treatment outcome measures of
both dropout and relapse, as well as the first study that meas -
ures the effect of sensitivity to punishment (from a neurocog-
nitive perspective) on treatment outcome. Very few studies
have explored the relation between executive functioning and
decision-making on the one hand, and self-report measures of
impulsivity on the other, in pathologic gambling. As a person-
ality trait, impulsivity may be difficult to modify. However,
several studies suggest that “trait- oriented” interventions may
optimize treatment effects in several mental disorders.77 Apart
from pharmacological interventions,78 psychological interven-
tions to modify impulsivity may include techniques to iden-
tify the impulse before acting, consider consequences and re-
flect on solutions. In addition, psychological interventions
may be shorter and more intensive with motivational compo-
nents to diminish the risk of dropout. Impulsivity in other
mental disorders has also been addressed with Linehan’s Dia -
lectical Behaviour Therapy.79 Although preliminary, these re-
sults may encourage future specific interventions addressed
to diminish the risk of dropout during psychological treat-
ment for pathologic gambling.
Acknowledgements: Dr. Álvarez-Moya was supported by a Juan de
la Cierva fellowship (Ministry of Science and Innovation, Spanish gov-
ernment; Ref. 1048). Financial support for this study was partially re-
ceived from the Spanish Fondo de Investigación Sanitaria (PI081573;
PI081714). CIBER is an initiative of Instituto de Salud Carlos III.
Competing interests:None declared.
Contributors: Drs. Álvarez-Moya, Ochoa, Jiménez-Murcia and Fer-
nández-Aranda designed the study. Drs. Álvarez-Moya, Ochoa, Ay-
mamí, Gómez-Peña, Santamaría and Moragas acquired the data,
which Drs. Álvarez-Moya, Bove and Menchón analyzed. Drs. Ál-
varez-Moya, Ochoa, Jiménez-Murcia, Santamaría and Moragas wrote
the article, which Drs. Jiménez-Murcia, Aymamí, Gómez-Peña, Fer-
nández-Aranda, Bove and Menchón critically reviewed. All authors
approved publication of the article.
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Treating
schizophrenia
and bipolar
disorder
is not easy.
We’re here to help.
1
Schizophrenia: ZELDOX is indicated for the treatment of
schizophrenia and related psychotic disorders. The prescriber should
consider the greater capacity of ZELDOX to prolong the QT/QT
c
interval compared to other antipsychotic drugs. The effi cacy of
ZELDOX was established in short-term (4- and 6-week) controlled
trials of schizophrenic inpatients. ZELDOX has been shown to be
effective in maintaining clinical improvement during long-term
therapy (1 year). The physician who elects to use ZELDOX for
extended periods should periodically re-evaluate the long-term
usefulness of the drug for the individual patient. Bipolar disorder:
ZELDOX is indicated for the treatment of acute manic or mixed
episodes associated with bipolar disorder. The prescriber should
consider the greater capacity of ZELDOX to prolong the QT/QT
c
interval compared to other antipsychotic drugs. The effi cacy of
ZELDOX in acute mania was established in 2 placebo-controlled,
double-blind, 3-week studies which compared ZELDOX with placebo,
and one double-blind, 12-week (3-week placebo-controlled, active
comparator acute phase and 9-week active comparator phase) study
which compared ZELDOX to haloperidol and placebo, in patients
meeting DSM-IV criteria for Bipolar I Disorder. The effectiveness of
ZELDOX for longer-term use and for prophylactic use in mania has not
been systematically evaluated in controlled clinical trials. Therefore,
physicians who elect to use ZELDOX for extended periods should
periodically re-evaluate the long-term risks and benefi ts of the drug
for the individual patient.
ZELDOX is not indicated in elderly patients with dementia. Caution
should be used when treating geriatric patients with ZELDOX. The
safety and effi cacy of ZELDOX in children under the age of 18 have
not been established.
In short-term, placebo-controlled schizophrenia clinical trials of a
duration of up to 6 weeks, the most commonly observed adverse
events associated with the use of ZELDOX (incidence of 5% or
greater) and observed at a rate on ZELDOX at least twice that of
placebo were somnolence (14% vs. 7%), extrapyramidal symptoms
(14% vs. 8%), and respiratory tract infections (8% vs. 3%).
In short-term, placebo-controlled bipolar mania clinical trials, the
most commonly observed adverse events associated with the use of
ZELDOX (incidence of 5% or greater) and observed at a rate on
ZELDOX at least twice that of placebo were somnolence (22.8% vs.
8.5%), akathisia (12.9% vs. 4.5%), extrapyramidal syndrome (13.6%
vs. 4.9%), dizziness (10.7% vs. 4.0%) and dystonia (7.0% vs. 1.3%).
Because of ZELDOX’s dose-related prolongation of the QT interval
and the known association of fatal arrhythmias with QT prolongation
by some other drugs, ZELDOX is contraindicated in patients with:
known history of QT prolongation (including congenital long QT
syndrome); recent acute myocardial infarction; or uncompensated
heart failure. Pharmacokinetic/pharmacodynamic studies between
ZELDOX and other drugs that prolong the QT interval have not been
performed. An additive effect of ZELDOX and other drugs that
prolong the QT interval cannot be excluded. Therefore, ZELDOX
should not be given with dofetilide, sotalol, quinidine, other Class
Ia and III anti-arrhythmias, mesoridazine, thioridazine, chlorpromazine,
droperidol, pimozide, sparfloxacin, gatifloxacin, moxifloxacin,
halofantrine, mefl oquine, pentamidine, arsenic trioxide, levomethadyl
acetate, dolasetron mesylate, probucol or tacrolimus. ZELDOX is also
contraindicated with drugs that have demonstrated QT prolongation
as one of their pharmacodynamic effects and have this effect
described in their respective Product Monograph as a contraindication
or a warning. ZELDOX is contraindicated in patients who are
hypersensitive to ziprasidone or to any ingredient in the formulation
or component of the container.
Serious Warnings and Precautions
Increased Mortality in Elderly Patients with Dementia
Elderly patients with dementia treated with atypical
antipsychotic drugs are at an incr eased risk of death
compared to placebo. Analyses of 13 placebo-controlled
trials with various antipsychotic s (modal duration
of 10 weeks) in these patients showed a mean 1.6-fold
increase in the death rate in the drug-treated patient s.
Although the causes of death were varied, most
of the deaths appeared to be either cardiovascular
(e.g., heart failure, sudden deat h) or infectious
(e.g., pneum onia) in nature.
TM Pfi zer Inc., used under license
ZELDOX
®
Pfi zer Products Inc., Pfi zer Canada Inc., licensee
©
2011 Pfi zer Canada Inc., Kirkland, Quebec H9J 2M5
See
S
pres
res
crib
rib
ing
i
summ
m
ary
ry
ary
ary
on pa
ge
2
208
J Psychiatry Neurosci 2011;36(3)
