Effects of mood state on impulsivity in pathological buying

Abstract

Pathological buying is characterized by irrepressible buying behaviour and its negative consequences. A possible mechanism contributing to its development and maintenance is that buying episodes act as a maladaptive strategy to cope with negative emotions. Accordingly, pathological buying has been repeatedly associated with impulsivity, in particular with the tendency to experience strong reactions under negative affect. Relying on an experimental mood induction procedure, the present study tested in a sample of 100 individuals (a) whether individuals with pathological buying symptoms respond more impulsively in the Go/No-Go Task (as a measure of the behavioural inhibition aspect of impulsivity) and (b) whether this association is more pronounced in a negative mood. While controlling for comorbidities, the results show that pathological buying is associated with faster responses and a larger number of commission errors. Moreover, a significant interaction indicated that the association between pathological buying and performance the Go/No-Go Task was stronger in the negative mood condition. The present study thus shows that that pathological buying is associated with deficits in the behavioural inhibition component of impulsivity. These deficits are most pronounced when mood is negative; in turn, this provides an explanation for the occurrence of excessive buying episodes following negative affect.

Full text

Effects of mood state on impulsivity in pathological buying
Jennifer Nicolai
a,
n
, Stefaniá Darancó
b
, Morten Moshagen
c
a
Cognition and Individual Differences, University of Mannheim, Schloss, EO 254, 68133 Mannheim, Germany
b
University of Glasgow, UK
c
University of Kassel, Germany
article info
Article history:
Received 14 December 2015
Received in revised form
25 July 2016
Accepted 4 August 2016
Available online 4 August 2016
Keywords:
Pathological buying
Compulsive buying
Addictive buying
Mood
Impulsivity
abstract
Pathological buying is characterized by irrepressible buying behaviour and its negative consequences. A
possible mechanism contributing to its development and maintenance is that buying episodes act as a
maladaptive strategy to cope with negative emotions. Accordingly, pathological buying has been re-
peatedly associated with impulsivity, in particular with the tendency to experience strong reactions
under negative affect. Relying on an experimental mood induction procedure, the present study tested in
a sample of 100 individuals (a) whether individuals with pathological buying symptoms respond more
impulsively in the Go/No-Go Task (as a measure of the behavioural inhibition aspect of impulsivity) and
(b) whether this association is more pronounced in a negative mood. While controlling for comorbidities,
the results show that pathological buying is associated with faster responses and a larger number of
commission errors. Moreover, a significant interaction indicated that the association between patholo-
gical buying and performance the Go/No-Go Task was stronger in the negative mood condition. The
present study thus shows that pathological buying is associated with deficits in the behavioural in-
hibition component of impulsivity. These deficits are most pronounced when mood is negative; in turn,
this provides an explanation for the occurrence of excessive buying episodes following negative affect.
&2016 Elsevier Ireland Ltd. All rights reserved.
1. Introduction
Pathological buying is characterized by irrepressible and un-
controllable buying behaviour and its associated negative con-
sequences (Dittmar, 2005). More specifically, it can be defined as:
(1) a recurrent preoccupation with buying and/or irresistible urges
to buy; (2) repetitive buying habits that are difficult to control
(with frequent buying of more than can be afforded, frequent
buying of items that are not needed, or shopping for longer peri-
ods of time than intended associated with an unavoidable urge to
buy); (3) a cause of negative consequences leading to personal
distress and significant social and/or financial problems (Dittmar,
2004;McElroy et al., 1994;Racine et al., 2014). According to a
recent meta-analysis, the prevalence of pathological buying ap-
proximates 5% among adults in the general population (Maraz
et al., 2016). Pathological buying demonstrates high comorbidities
with other Axis I disorders, including mood, anxiety, and sub-
stance use disorders (de Zwaan, 2011;Müller et al., 2010). The
issue of how to classify pathological buying is still under debate
(Grüsser et al., 2007;Hollander and Allen, 2006;Racine et al.,
2014). Propositions in this regard include classifying pathological
buying as an obsessive–compulsive disorder (Hollander et al.,
2011;Hollander and Allen, 2006), mood disorder (Lejoyeux et al.,
1997), behavioural addiction (Lawrence et al., 2014), or impulse
control disorder (Müller et al., 2015a).
Pathological buyers experience a strong and repetitive urge to
purchase goods, associated with growing tensions that can only be
relieved by the act of buying (Christenson et al., 1994;Faber and
Christenson, 1996;McElroy et al., 1994). A number of environ-
mental stimuli are known to trigger buying episodes (such as
colours, sounds, and smells) (Kellett and Bolton, 2009) and it
seems likely that pathological buyers have difficulties to resist
those cues (Trotzke et al., 2014). Correspondingly, evidence relying
on self-report measures suggests that pathological buying is as-
sociated with higher trait-impulsivity, in particular with the ten-
dency to experience strong reactions, frequently under conditions
of negative affect (Black et al., 2012;Lejoyeux et al., 1997;Rose and
Segrist, 2014;Vogt et al., 2015;Williams and Grisham, 2012; but
see Müller et al. (2014)). This, in turn, leads to difficulties to de-
liberately suppress automatized responses (Billieux et al., 2008;
Williams and Grisham, 2011).
Indeed, the experience of negative affect or negative emotions
is often reported as internal antecedent of pathological buying
(Faber and Christenson, 1996;Miltenberger et al., 2003) and in-
dividuals suffering from pathological buying frequently believe
that purchasing items acts as a deterrent for negative mood (Faber
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/psychres
Psychiatry Research
http://dx.doi.org/10.1016/j.psychres.2016.08.009
0165-1781/&2016 Elsevier Ireland Ltd. All rights reserved.
n
Corresponding author.
E-mail address: nicolai@uni-mannheim.de (J. Nicolai).
Psychiatry Research 244 (2016) 351–356

and Christenson, 1996;Kyrios et al., 2013). Studies relying on real-
time assessments have shown that pathological buyers suffer an
increased negative affect prior to a compulsive buying episode,
which is alleviated later on (Miltenberger et al., 2003;Müller et al.,
2012). This experience of negative reinforcement may contribute
to the use of buying in order to cope with negative affect (Faber
and Christenson, 1996). Therefore, individuals with pathological
buying disorder may engage in excessive buying as a maladaptive
self-regulatory mechanism to reduce negative feelings, which is
particularly the case for those who exhibit deficits in emotion
regulation (Williams and Grisham, 2011). According to this mood-
repair hypothesis it can be expected that negative affect leads to
the goal of mood repair which is realized in purchasing behaviour;
consequently, purchasing behaviour functions as a mean to repair
negative mood (Kellett and Bolton, 2009;Williams, 2012). How-
ever, studies that experimentally induced negative affect using a
mood induction procedure failed to support this contention (Vogt
et al., 2014;Williams, 2012), as mood state did not alter the be-
haviour of individuals with pathological buying disorder in com-
puterized buying or shopping related tasks. However, the applied
tasks differed in various important aspects from natural buying
situations (Williams, 2012).
Because of the difficulties to establish a controlled experi-
mental environment that maintains the relevant ecological cues
and rewards in natural buying situations, a more viable approach
may lie in investigating the effect of mood state on specific cog-
nitive processes that are presumably involved in acute buying
episodes. In this context, state-impulsivity and inhibition-related
processes may be of particular importance. It is generally assumed
that (lack of) impulse control can be evident at different steps
during goal selection and goal pursuit, with each step in the se-
lection-action cycle being associated with different cognitive
processes (Cyders and Coskunpinar, 2011;Stahl et al., 2014). The
present study focuses on the behavioural inhibition component of
state-impulsivity (Stahl et al., 2014; called prepotent response
inhibition by Cyders and Coskunpinar (2011)) which refers to the
ability to withhold or stop an already initiated or ongoing re-
sponse. Consequently, the present study evaluated the effect of
mood state using a behavioural task (the Go/No-Go Task) to assess
the behavioural inhibition component of state-impulsivity. In line
with the considerations above, it was expected that (1) pathologi-
cal buying is generally associated with poorer performance on the
Go/No-Go Task and that (2) performance deteriorates most when
experiencing negative mood.
2. Methods
The study has been approved by the ethics committee of the
Psychology Department at the University of Mannheim. All parti-
cipants provided written informed consent by ticking a checkbox
linked to a respective statement.
2.1. Participants
An a-priori power analysis indicated that a sample of size
N¼95 is required to detect a moderate interaction effect (corre-
sponding to a standardized regression coefficient of .25) with a
power of 80% given an alpha error of 5%. Participants were re-
cruited via postings on social networks and by asking members of
self-help groups pertaining to pathological buying to participate.
The study was announced as investigation on buying and cogni-
tion. This led to a convenience sample of 100 (70 female, 28 male,
2“prefer not to say”) individuals. Mean age was 27.83 years
(SD¼12.2; range 18–68). Most of the participants (90%) reported
native or fluent English language skills. The majority of
participants were students (59%) and another 31% of participants
were currently employed or self-employed. Participants com-
pleted the study on an anonymous and voluntary basis without
any compensation.
2.2. Measures
The primary outcome of the present study was the perfor-
mance in the Go/No-Go Task. Questionnaire measures used in-
cluded a scale assessing pathological buying and a set of poten-
tially relevant clinical background variables. The latter measures
were included to allow for the investigation of whether the results
pertaining to pathological buying change when controlling for
comorbid disorders. In addition, background measures included a
scale assessing symptoms of obsessive–compulsive disorder (OCD)
to determine whether individuals with OCD symptoms behave
similar to those with symptoms of pathological buying, thereby
contributing evidence toward the classification of pathological
buying.
Go/No-Go Task. In each trial, participants were shown a con-
sonant (randomly selected from 21 consonants) in the centre of
the screen for a maximum of 1500 ms. The task was to press the
space key as fast as possible as soon as a letter appeared on screen
(go trials), except for an “X”, to which any response should be
withheld (no-go trials). In case of an incorrect response, a red cross
briefly appeared. Letters were presented in white against a black
background. Each trial was preceded by a fixation cross that was
shown for 200 ms. Stimulus onset time was determined at random
to be either 600, 700, 800, or 900 ms. A training block of 10 trials
was followed by a test block comprising 100 trials (70 go and 30
no-go trials). The Go/No-Go Task elicits two types of responses, the
number of commission errors (failure to inhibit a response) in the
no-go trials and the response times for correct responses in the go-
trials. A higher level of impulsivity is evident in a larger number of
commission errors and/or shorter reaction times.
2.2.1. Pathological Buying Screener (PBS)
The PBS (Müller et al., 2015b) is a 13-item screening instrument
that measures pathological buying with the two factors loss of
control/consequences and excessive buying behaviour. The reliability
of the total score as well as of the two subscales proved to be good.
Evidence of incremental validity and convergent validity of the PBS
using the Compulsive Buying Scale (Faber and O’Guinn, 1992) has
been provided.
2.2.2. Positive and Negative Affect Schedule (PANAS)
Mood was assessed by the PANAS (Krohne et al., 1996;Watson
et al., 1988) before and after the mood induction procedure. The
PANAS consists of two 10-item scales that measure Positive Affect
(PA) and Negative Affect (NA). Respondents were asked to rate how
they felt at the present moment on a 5-point Likert scale ranging
from 1 (very slightly or not at all) to 5 (extremely). The PANAS
shows good psychometric properties (Watson et al., 1988).
2.2.3. Mood Disorder Questionnaire (MDQ)
The MDQ (Hirschfeld et al., 2003,2000) is a 13-item self-report
screening instrument for bipolar spectrum disorders that is di-
vided into three parts: Part 1 asks in a dichotomous response (yes/
no) format about lifetime (hypo-)maniac symptoms (hyperactivity,
irritability, sleeping behaviour, concentration, activity levels, and
risky behaviour), Part 2 is about symptom co-occurrence, and Part
3 asks about symptom severity on a four point scale (no problem,
minor problem, moderate problem, serious problem). The sensi-
tivity and specificity have been estimated in a psychiatric popu-
lation (Hirschfeld et al., 2000) and in the general population
(Hirschfeld et al., 2003). In the present study, we used the sum
J. Nicolai et al. / Psychiatry Research 244 (2016) 351–356352

score across all items to measure the severity of mood disorder
symptoms.
2.2.4. Modified Beck Depression Inventory (M-BDI)
A simplified 20 item-version (Schmitt et al., 2003;Schmitt and
Maes, 2000) of the BDI (Beck and Steer,1987) was used. The M-BDI
asks respondents to indicate the frequency of experiencing
symptoms of depression on a 6-point Likert scale ranging from 0
(never) to 5 (almost always), with higher scores indicating higher
levels of depression. The reliability of the M-BDI proved to be
good. Its construct validity and measurement equivalence as
compared to the original BDI have been demonstrated (Schmitt
et al., 2003).
2.2.5. Borderline Symptom List 23 (BSL-23)
The BSL (Bohus et al., 2009) is a 23-item self-report instrument
that measures borderline symptom severity on a five-point Likert
scale ranging from 0 (not at all) to 4 (very strong). The psycho-
metric properties of the BSL-23 were assessed in five different
borderline personality disorder (BPD) patient samples. The BSL has
good internal consistency. The BSL-23 has been shown to ade-
quately discriminate BPD patients from patients with an axis I
diagnosis.
2.2.6. Obsessive Compulsive Inventory (OCI-R)
The OCI-R (Foa et al., 2002) is an 18-item self-report measure
designed to assess symptoms of obsessive–compulsive disorder
(OCD) across six subscales: washing, checking, ordering, obsessing,
hoarding, and neutralizing. Respondents assess the degree to
which they are distressed by OCD symptoms in the past month on
a 5-point scale from 0 (not at all) to 4 (extremely). The OCI-R has
demonstrated excellent psychometric properties in a sample of
patients with OCD, other anxiety disorders, and in non-anxious
individuals (Foa et al., 2002). It has been shown that it differ-
entiates well between people with and without OCD. Foa and
colleagues also found good internal consistency, adequate test–
retest reliability, and evidence of convergent and discriminant
validity.
2.3. Procedures
The study was conducted (in the English language) via the In-
ternet, closely adhering to standards of web-based experimenting
(Reips, 2002). After receiving general information about the study
and providing informed consent, participants completed the PA-
NAS (baseline measurement). Next, participants were randomly
assigned to either a positive mood or a negative mood condition.
Mood induction proceeded by using a subset of the Velten State-
ments (Velten, 1968), accompanied by either cheerful or sad in-
strumental music. Participants were requested to turn on the
audio and were provided the opportunity to check whether the
audio was working. The Velten technique presents a series of self-
referent mood statements such as “I feel enthusiastic and con-
fident now”,“I’m pleased that most people are so friendly to me”,
and “I have a sense of power and vigour”(positive mood condition)
or “I feel rather sluggish now”,“People annoy me; I wish I could be
by myself”, and “Just to stand up would take a big effort”(negative
mood condition). Participants were instructed to read each of the
statements carefully and to try to be open to their meaning. The
effectiveness of the Velten technique in an online context has been
demonstrated (Göritz, 2007), as has the combination of the Velten
technique with music (Westermann et al., 1996). Either 30 positive
or 30 negative Velten statements were presented consecutively for
5–10 s each (with an average of 8.2 s), depending on the length of
the respective statement. In total, the mood induction phase took
approximately 5 min. Immediately after the mood induction,
participants completed the PANAS again (post-mood induction)
and took the Go/No-Go Task. Thereafter, the questionnaire mea-
sures were presented in randomized order. Finally, demographic
background data were collected, participants were debriefed, and
the study closed with a mood-neutralization phase (for the par-
ticipants in the negative mood condition). The study took ap-
proximately 20 min to complete.
2.4. Statistical analyses
To evaluate our hypotheses multiple regression analyses with
the PBS score (as measure of pathological buying), mood condition
(coded "1 for negative and 1 for positive mood), the PBS #mood
interaction, and the remaining measures (as covariates) were
performed. We followed the recommended approach in linear
regression analysis involving main effects and interactions to in-
clude all relevant predictors simultaneously in a single model,
since testing the interaction term requires the presence of the
main effects (e.g., Cohen et al., 2003). The dependent variable was
behavioural impulsivity as measured through the performance in
the Go/No-Go Task. We considered both, the number of commis-
sion errors in the no-go trials and the mean response times in the
go-trials. All variables (except for the mood condition) were
z-standardized prior to the analyses, in order to obtain centred
predictors and standardized regression coefficients that can be
readily compared across predictors that are measured on different
scales. All statistical analyses were performed in R (version 3.0.2; R
Core Team, 2013).
3. Results
Detailed descriptive results are presented in Table 1. According
to the tentative guidelines suggested by Müller et al. (2015b) 36%
and 13% of the sample, respectively, would be diagnosed as pa-
thological buyers using cut-off scores of 2.23 (2 SD above the mean
in a general population sample) and 3.00 (on average, each pro-
blematic behaviour occurs at least “sometimes”), respectively. All
questionnaire measures exhibited good internal consistencies. On
a bivariate level, the PBS showed moderately positive correlations
to the BSL-23, M-BDI, MDQ, and the OCI. However, the PBS was the
only measure that was significantly correlated with performance
in the Go/No-Go Task, both with respect to response times
(r¼".28) and the number of commission errors (r¼.20).
Table 1
Means, standard deviations, and correlations (Cronbach's αEstimate of Internal
Consistency on the Diagonal).
Variable Mean (SD) Correlations
12345
1. PBS 1.99 (0.78) (.91)
2. M-BDI 2.30 (0.71) .44
**
(.91)
3. OCI 1.83 (0.62) .40
**
.44
**
(.88)
4. MDQ 1.56 (0.27) .36
**
.30
**
.29
**
(.83)
5. BSL-23 1.71 (0.71) .30
**
.80
**
.53
**
.32
**
(.95)
GNGT response time 477 (75.1) ".28
**
.03 ".17 ".08 .00
GNGT commission errors 3.17 (2.59) .20
*
".09 .01 .09 ".07
PBS ¼Pathological Buying Screener, M-BDI ¼Modified Beck Depression Inventory,
OCI ¼Obsessive Compulsive Disorder Inventory, MDQ ¼Mood Disorder Ques-
tionnaire, BSL-23¼Borderline Symptom Checklist, GNGT ¼Go/No-Go Task.
*
po.05.
**
po.01.
J. Nicolai et al. / Psychiatry Research 244 (2016) 351–356 353

3.1. Manipulation check
Two linear regressions were performed to evaluate the effec-
tiveness of the mood manipulation by considering the PA and NA
subscales, respectively, of the PANAS as criterion variables. Speci-
fically, the respective PANAS subscale assessed after mood induc-
tion was regressed on mood condition (coded "1 for negative and
1 for positive mood) and the like PANAS subscale measured at
baseline (to control for pre-existing mood differences across con-
ditions). Results show that the mood manipulation yielded sig-
nificant effects on both subscales of the PANAS (PA:
β
¼0.72,
po.01; NA:
β
¼"0.75, po.01). In addition, compared to partici-
pants in the negative mood induction condition, participants in
the positive mood induction condition exhibited smaller values on
the post-mood induction PANAS-NA (M¼1.83, SD¼0.75 vs.
M¼1.41, SD¼0.43; d¼"0.70; t(98)¼3.49, po.01) and higher
values on the PANAS-PA (M¼2.21, SD¼0.85 vs. M¼2.59, SD¼0.95;
Cohen's d¼0.43; t(98)¼2.11, po.05), thereby confirming that the
mood induction was successful. Apart from the PANAS, there was
no effect of mood condition on either of the remaining ques-
tionnaire measures.
3.2. Effect of pathological buying and mood state on state
impulsivity
The multiple regression predicting Go/No-Go Task reaction
times yielded a significant effect of PBS (
β
¼"0.30, po.01), but no
significant effect of mood condition (
β
¼"0.07, p¼.45) and no
significant interaction between PBS and mood condition (
β
¼0.14,
p¼.17). The model explained 10.1% of the variance (po.05). This
pattern indicates that participants with higher values on the PBS
acted more impulsively by responding faster, irrespectively of
mood. This pattern of result did not change when adding the re-
maining variables (BSL-23, M-BDI, MDQ, and OCI) as covariates to
the model: PBS showed a similar effect (
β
¼"0.35, po.01),
whereas no other predictor significantly contributed to the model.
The multiple regression predicting the number of commission
errors in the Go/No-Go Task yielded a significant effect of PBS
(
β
¼0.24, po.05), indicating that participants with higher values
on the PBS reacted more impulsively by making more commission
errors. There was no significant effect of mood condition (
β
¼0.15,
p¼.13). The main effect of PBS was qualified by a significant in-
teraction between PBS and mood condition (
β
¼"0.25, po.05),
showing that mood state moderates the association between PBS
and impulsivity. The multiple R
2
was .12 (po.01). Note that we did
not perform a stepwise regression analysis, but simultaneously
included the relevant predictors in a single model, in line with
contemporary recommendations (Cohen et al., 2003). However,
performing a stepwise regression analysis leads to the same con-
clusions. Predicting the number of errors by the PBS score as the
only predictor yielded a significant R
2
of .04, F(1,98)¼4.2, po.05.
Including the mood condition in the second step did not sig-
nificantly improve the model,
Δ
R
2
¼0.02, F(1,97) ¼2.1, p¼.15. In-
cluding the interaction between PBS and mood condition as a third
step significantly contributed to the prediction of the number of
errors,
Δ
R
2
¼0.06, F(1,96)¼6.6, po.05. Fig. 1 shows the effect of
PBS on the number of commission errors separately for partici-
pants in the positive and negative mood condition. It is evident
that PBS shows virtually no association with the number of com-
mission errors in the positive mood condition (simple slope
β
¼"0.01, p¼.95). By contrast, there was a pronounced positive
association between PBS and the number of commission errors in
the negative mood condition (simple slope
β
¼0.49, po.001).
Thus, the interaction shows that higher (compared to lower) PBS
scores were associated with more impulsive responding when
mood was negative, whereas PBS did not predict impulsivity when
mood was positive. Adding the covariates to the model did not
change the results. Again, PBS (
β
¼0.31, po.01) and the interaction
between PBS and mood condition (
β
¼"0.25, po.05) were the
only significant predictors.
4. Discussion
Pathological buying has been repeatedly associated with defi-
cits in impulse control. A possible mechanism contributing to the
development and maintenance of pathological buying is that
buying acts as a maladaptive strategy to cope with negative affect.
In the present study, we tested (a) whether pathological buying
symptoms are associated with impaired performance in the Go/
No-Go Task as a measure of the behavioural inhibition component
of state-impulsivity and (b) whether this association is more
pronounced in negative mood. In agreement with the first hy-
pothesis, the study showed that higher scores on the PBS were
associated with faster responses and a larger number of commis-
sion errors in the Go/No-Go Task, thus indicating that individuals
exhibiting pathological buying symptoms generally behave more
impulsive. Corroborating the second hypothesis, the results fur-
ther provide evidence for the notion that deficits in impulse
control are most striking when mood is negative, providing a
possible explanation for the occurrence of excessive buying epi-
sodes following negative affect.
In line with related work (de Zwaan, 2011;McElroy et al., 1994;
Müller et al., 2010), the present study revealed high comorbidities
of pathological buying to other disorders. Pathological buying ex-
hibited substantial correlations with symptoms of depression and
mood disorder, but also to OCD, borderline, and mania. Given
these comorbidities, it is interesting to note that both principal
findings of more impulsive responding with more pathological
buying symptoms and stronger deficits in impulse control for
negative mood still hold when controlling for the influence of the
remaining variables. Thus, the results indicate that the suggested
mechanism may indeed be unique to pathological buying. As such,
these results also provide evidence concerning the classification of
Fig. 1. Effect of pathological buying and mood on the number of commission errors
in the Go/No-Go Task.
J. Nicolai et al. / Psychiatry Research 244 (2016) 351–356354

pathological buying, given that OCD was not related to impulsivity.
This suggests that different cognitive mechanisms apply to OCD
and thus questions the categorization of pathological buying as
obsessive-compulsive disorder. Apart from OCD, pathological
buying also shares many similarities with (behavioural) addictions,
including a craving-like urge before engaging in buying, a re-
petitive loss of control, the use of buying to alleviate negative af-
fect, and symptoms similar to withdrawal when not buying.
Likewise, research has consistently demonstrated deficits in im-
pulse control for individuals with (behavioural) addictions (Cos-
kunpinar and Cyders, 2013;Karim and Chaudhri, 2012). Thus, al-
though we did not investigate this issue explicitly in the present
study, the results are closely aligned with the notion that patho-
logical buying resembles (behavioural) addictions (Lawrence et al.,
2014;Racine et al., 2014). However, despite these overlaps, it
should be noted that pathological buying –unlike addictions –
does not seem to alter serotonergic, dopaminergic, or opioid reg-
ulatory systems (Piquet-Pessôa et al., 2014), so that a classification
as an impulse control disorder seems equally plausible (Müller
et al., 2015a).
A related issue is whether pathological buying is associated
with deficits executive functions. Studies investigating perfor-
mance in tasks that seek to measure decision-making under am-
biguity and under risk provided mixed results (Black et al., 2012;
Derbyshire et al., 2014;Trotzke et al., 2015;Voth et al., 2014). If
anything, the available evidence indicates a trend for pathological
buyers to exhibit impairments in situations when ambiguity oc-
curs, but not in situations where the outcome of a decision is
explicit and stable (Trotzke et al., 2015). However, decision-making
is comprised of a number of different cognitive processes that
occur on different levels of the cognitive system. It might be
possible that pathological buying is associated with deficits in
rather specific cognitive processes that may be difficult to isolate
when considering complex decision-making tasks. To the best of
our knowledge, the present study is the first that investigated the
behavioural inhibition component of impulsivity via the Go/No-Go
task. It seems plausible that the observed impairments in this
particular component do not readily generalize to other aspects of
impulsivity or entirely different executive functions.
The results of the present study may also inform approaches to
treatment of individuals suffering from pathological buying.
Treatment programs may support clients in identifying and
managing their reactions to negative affect by promoting affect
regulation and distress tolerance skills.
Some limitations should be considered when interpreting the
results of the present study. First, the study is based on a non-
representative analog sample (instead of comparing individuals
clinically diagnosed as pathological buyers versus healthy con-
trols). Although the use of analog samples is subject to several
shortcomings (Coyne, 1994), most authors conceive pathological
buying as a dimensional phenomenon with normal variations (e.g.,
Vogt et al., 2014), so that analog samples are well suited to gain
insights into the underlying mechanisms distinguishing absence of
problems or subclinical from clinical states (Abramowitz et al.,
2014). A second limitation is that the present study was performed
online, thus giving rise to concerns pertaining to insufficient ex-
perimental control. It is therefore recommended to replicate the
results using in a laboratory setting, which would also allow for
applying more sophisticated –and thus arguably more effective –
methods of mood induction (Hewig et al., 2005). In addition, to
obtain further and more direct support for the mood-repair hy-
pothesis, a replication using buying related cues is recommended.
Moreover, the present study did not include a self-report measure
assessing trait impulsivity. Given that self-report and behavioural-
based measures of impulsivity exhibit only little overlap and
presumably assess different aspects of impulsivity (Cyders and
Coskunpinar, 2011;Stahl et al., 2014), it would be interesting to
examine trait-impulsivity in conjunction with the tasks used
herein. Finally, the presence of disorders has been assessed after
the mood induction and the Go/No-Go task, because certain
questionnaire items could potentially trigger negative emotions
and thus conflict with the mood induction procedure. Although
there were no effects of mood condition on measures of psycho-
logical disorders, a superior approach is to assess the presence of
disorders several days in advance in a separate session.
Despite these limitations, the present study demonstrates
deficits in the behavioural inhibition component of state im-
pulsivity using a behavioural paradigm for individuals with pa-
thological buying symptoms and showed that these deficits are
most pronounced in a state of negative affect. It was further shown
that this mechanism is related to pathological buying, rather than
to comorbid disorders. The results of the present study can thus be
interpreted to provide initial support for the notion that patho-
logical buyers may use buying episodes as a maladaptive self-
regulatory mechanism to reduce negative feelings.
References
Abramowitz, J.S., Fabricant, L.E., Taylor, S., Deacon, B.J., McKay, D., Storch, E.A., 2014.
The relevance of analogue studies for understanding obsessions and compul-
sions. Clin. Psychol. Rev. 34, 206–217.
Beck, A.T., Steer, R.A., 1987. Manual for the Beck Depression Inventory (BDI). The
Psychological Corporation, San Antonio (TX).
Billieux, J., Rochat, L., Rebetez, M.M.L., Van der Linden, M., 2008. Are all facets of
impulsivity related to self-reported compulsive buying behavior? Pers. Individ.
Differ. 44, 1432–1442.
Black, D.W., Shaw, M., McCormick, B., Bayless, J.D., Allen, J., 2012. Neuropsycholo-
gical performance, impulsivity, ADHD symptoms, and novelty seeking in
compulsive buying disorder. Psychiatry Res. 200, 581–587.
Bohus, M., Kleindienst, N., Limberger, M.F., Stieglitz, R.-D., Domsalla, M., Chapman,
A.L., Steil, R., Philipsen, A., Wolf, M., 2009. The short version of the borderline
symptom list (BSL-23): development and initial data on psychometric proper-
ties. Psychopathology 42, 32–39.
Christenson, G.A., Faber, R.J., de Zwaan, M., Raymond, N.C., Specker, S.M., Ekern, M.
D., Mackenzie, T.B., Crosby, R.D., Crow, S.J., Eckert, E.D., 1994. Compulsive
buying: descriptive characteristics and psychiatric comorbidity. J. Clin. Psy-
chiatry 55, 5–11.
Coskunpinar, A., Cyders, M.A., 2013. Impulsivity and substance-related attentional
bias: a meta-analytic review. Drug Alcohol Depend. 133, 1–14.
Cohen, J., Cohen, P., West, S.G., Aiken, L.S., 2003. Applied Multiple Regression/Cor-
relation Analysis in the Behavioral Sciences, 3rd ed Erlbaum, Mahwah.
Coyne, J.C., 1994. Self-reported distress: analog or ersatz depression? Psychol. Bull.
116, 29–45.
Cyders, M.A., Coskunpinar, A., 2011. Measurement of constructs using self-report
and behavioral lab tasks: is there overlap in nomothetic span and construct
representation for impulsivity? Clin. Psychol. Rev. 31, 965–982.
Derbyshire, K.L., Chamberlain, S.R., Odlaug, B.L., Schreiber, L.R., Grant, J.E., 2014.
Neurocognitive functioning in compulsive buying disorder. Ann. Clin. Psy-
chiatry 26, 57–63.
de Zwaan, M., 2011. Psychiatric comorbidity and compulsive buying, Compulsive
Buying: Clinical Foundations and Treatment. Routledge, New York, pp. 87–104.
Dittmar, H., 2005. Compulsive buying–a growing concern? An examination of
gender, age, and endorsement of materialistic values as predictors. Br. J. Psy-
chol. 96, 467–491.
Dittmar, H., 2004. Understanding and diagnosing compulsive buying. In: Coombs,
R.H. (Ed.), Handbook of Addictive Disorders: A Practical Guide to Diagnosis and
Treatment. Wiley, New York, pp. 411–450.
Faber, R.J., Christenson, G.A., 1996. Differences in the mood states experienced by
compulsive buyers and other consumers. Psychol. Mark. 13, 803–819.
Faber, R.J., O’Guinn, T.C., 1992. A clinical screener for compulsive buying. J. Consum.
Res., 459–469.
Foa, E.B., Huppert, J.D., Leiberg, S., Langner, R., Kichic, R., Hajcak, G., Salkovskis, P.M.,
2002. The Obsessive-Compulsive Inventory: development and validation of a
short version. Psychol. Assess. 14, 485–496.
Göritz, A.S., 2007. The induction of mood via the WWW. Motiv. Emot. 31, 35–47.
Grüsser, S.M., Poppelreuter, S., Heinz, A., Albrecht, U., Sass, H., 2007. Verhaltens-
sucht: Eine eigenständige diagnostische Einheit? [Behavioural addiction: an
independent diagnostic category?]. Nervenarzt 78, 997–1002.
Hewig, J., Hagemann, D., Seifert, J., Gollwitzer, M., Naumann, E., Bartussek, D., 2005.
A revised film set for the induction of basic emotions. Cogn. Emot. 19,
1095–1109.
Hirschfeld, R.M.A., Holzer, C., Calabrese, J.R., Weissman, M., Reed, M., Davies, M.,
Frye, M.A., Keck, P., McElroy, S., Lewis, L., Tierce, J., Wagner, K.D., Hazard, E.,
2003. Validity of the mood disorder questionnaire: a general population study.
J. Nicolai et al. / Psychiatry Research 244 (2016) 351–356 355

Am. J. Psychiatry 160, 178–180.
Hirschfeld, R.M.A., Williams, J.B.W., Spitzer, R.L., Calabrese, J.R., Flynn, L., Keck, P.E.,
Lewis, L., McElroy, S.L., Post, R.M., Rapport, D.J., Russell, J.M., Sachs, G.S., Zajecka,
J., 2000. Development and validation of a screening instrument for bipolar
spectrum disorder: the mood disorder questionnaire. Am. J. Psychiatry 157,
1873–1875.
Hollander, E., Allen, A., 2006. Is compulsive buying a real disorder, and is it really
compulsive? Am. J. Psychiatry 163, 1670–1672.
Hollander, E., Zohar, J., Sirovatka, P.J., Regier, D.A., 2011. Obsessive-compulsive
spectrum disorders: Refining the research agenda for DSM-V, 1st ed. American
Psychiatric Pub, Washington, DC.
Karim, R., Chaudhri, P., 2012. Behavioral addictions: an overview. J. Psychoact.
Drugs 44, 5–17.
Kellett, S., Bolton, J.V., 2009. Compulsive buying: a cognitive–behavioural model.
Clin. Psychol. Psychother. 16, 83–99.
Krohne, H.W., Egloff, B., Kohlmann, C.W., Tausch, A., 1996. Investigations with a
German version of the positive and negative affect schedule (PANAS). Diag-
nostica 42, 139–156.
Kyrios, M., McQueen, P., Moulding, R., 2013. Experimental analysis of the relation-
ship between depressed mood and compulsive buying. J. Behav. Ther. Exp.
Psychiatry 44, 194–200.
Lawrence, L.M., Ciorciari, J., Kyrios, M., 2014. Relationships that compulsive buying
has with addiction, obsessive-compulsiveness, hoarding, and depression.
Compr. Psychiatry 55, 1137–1145.
Lejoyeux, M., Tassain, V., Solomon, J., Ades, J., 1997. Study of compulsive buying in
depressed patients. J. Clin. Psychiatry 58, 169–173.
Maraz, A., Griffiths, M.D., Demetrovics, Z., 2016. The prevalence of compulsive
buying: a meta-analysis. Addiction 111, 408–419.
McElroy, S.L., Keck, P.E., Pope, H.G., Smith, J.M., Strakowski, S.M., 1994. Compulsive
buying: a report of 20 cases. J. Clin. Psychiatry 55, 242–248.
Miltenberger, R.G., Redlin, J., Crosby, R., Stickney, M., Mitchell, J., Wonderlich, S.,
Faber, R., Smyth, J., 2003. Direct and retrospective assessment of factors con-
tributing to compulsive buying. J. Behav. Ther. Exp. Psychiatry 34, 1–9.
Müller, A., Claes, L., Georgiadou, E., Möllenkamp, M., Voth, E.M., Faber, R.J., Mitchell,
J.E., de Zwaan, M., 2014. Is compulsive buying related to materialism, depres-
sion or temperament? Findings from a sample of treatment-seeking patients
with CB. Psychiatry Res. 216, 103–107.
Müller, A., Mitchell, J.E., Black, D.W., Crosby, R.D., Berg, K., de Zwaan, M., 2010.
Latent profile analysis and comorbidity in a sample of individuals with com-
pulsive buying disorder. Psychiatry Res. 178, 348–353.
Müller, A., Mitchell, J.E., Crosby, R.D., Cao, L., Johnson, J., Claes, L., de Zwaan, M.,
2012. Mood states preceding and following compulsive buying episodes: an
ecological momentary assessment study. Psychiatry Res. 200, 575–580.
Müller, A., Mitchell, J.E., De Zwaan, M., 2015a. Compulsive buying. Am. J. Addict. 24,
132–137.
Müller, A., Trotzke, P., Mitchell, J.E., de Zwaan, M., Brand, M., 2015b. The patholo-
gical buying screener: development and psychometric properties of a new
screening instrument for the assessment of pathological buying symptoms.
PLoS One 10, e0141094.
Piquet-Pessôa, M., Ferreira, G.M., Melca, I.A., Fontenelle, L.F., 2014. DSM-5 and the
decision not to include sex, shopping or stealing as addictions. Curr. Addict.
Rep. 1, 172–176 .
R Core Team, 2013. R: A Language and Environment for Statistical Computing. R
Foundation ForStatistical Computing, Vienna, Austria.
Racine, E., Kahn, T., Hollander, E., 2014. Compulsive buying disorder, Behavioral
Addictions: Criteria, Evidence, and Treatment. Academic Press, New York,
pp. 285–316.
Reips, U.-D., 2002. Standards for Internet-based experimenting. Exp. Psychol. 49,
243–256.
Rose, P., Segrist, D.J., 2014. Negative and positive urgency may both be risk factors
for compulsive buying. J. Behav. Addict. 3, 128–132.
Schmitt, M., Beckmann, M., Dusi, D., Maes, J., Schiller, A., Schonauer, K., 20 03.
Messgüte des vereinfachten Beck-Depressions-Inventars (BDI-V) [Psychometric
properties of the simplified Beck Depression Inventory (BDI-V)]. Diagnostica 49,
147–156.
Schmitt, M., Maes, J., 2000. Vorschlag zur Vereinfachung des Beck-Depressions-
Inventars (BDI) [A proposition for a simplified Beck Depression Inventory
(BDI)]. Diagnostica 46, 38–46.
Stahl, C., Voss, A., Schmitz, F., Nuszbaum, M., Tüscher, O., Lieb, K., Klauer, K.C., 2014.
Behavioral components of impulsivity. J. Exp. Psychol. Gen. 143, 850–886.
Trotzke, P., Starcke, K., Pedersen, A., Brand, M., 2014. Cue-induced craving in pa-
thological buying: empirical evidence and clinical implications. Psychosom.
Med. 76, 694–700.
Trotzke, P., Starcke, K., Pedersen, A., Müller, A., Brand, M., 2015. Impaired decision
making under ambiguity but not under risk in individuals with pathological
buying-behavioral and psychophysiological evidence. Psychiatry Res. 229,
551–558.
Velten, E., 1968. A laboratory task for induction of mood states. Behav. Res. Ther. 6,
473–482.
Vogt, S., Hunger, A., Pietrowsky, R., Gerlach, A.L., 2015. Impulsivity in consumers
with high compulsive buying propensity. J. Obsessive-Compuls. Relat. Disord. 7,
54–64.
Vogt, S., Hunger, A., Türpe, T., Pietrowsky, R., Gerlach, A.L., 2014. Effects of mood
induction on consumers with vs. without compulsive buying propensity: an
experimental study. Psychiatry Res. 220, 342–347.
Voth, E.M., Claes, L., Georgiadou, E., Selle, J., Trotzke, P., Brand, M., de Zwaan, M.,
Müller, A., 2014. Reactive and regulative temperament in patients with com-
pulsive buying and non-clinical controls measured by self-report and perfor-
mance-based tasks. Compr. Psychiatry 55, 1505–1512.
Watson, D., Clark, L.A., Tellegen, A., 1988. Development and validation of brief
measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol.
54, 1063–1070.
Westermann, R., Spies, K., Stahl, G., Hesse, F.W., 1996. Relative effectiveness and
validity of mood induction procedures: a meta-analysis. Eur. J. Soc. Psychol. 26,
557–580.
Williams, A.D., 2012. Evaluation of the mood repair hypothesis of compulsive
buying. Open J. Psychiatry 2, 83–90.
Williams, A.D., Grisham, J.R., 2012. Impulsivity, emotion regulation, and mindful
attentional focus in compulsive buying. Cogn. Ther. Res. 36, 451–457.
Williams, A.D., Grisham, J.R., 2011. Impulsivity, emotion regulation, and mindful
attentional focus in compulsive buying. Cogn. Ther. Res. 36, 451–457.
J. Nicolai et al. / Psychiatry Research 244 (2016) 351–356356