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Current Addiction Reports (2023) 10:718–736
https://doi.org/10.1007/s40429-023-00512-4
1 3
The Interrelation Between Emotional Impulsivity, Craving,
andSymptoms Severity inBehavioral Addictions andRelated
Conditions: aTheory‑Driven Systematic Review
JoséLópez‑Guerrero1 · JuanF.Navas2 · JoséC.Perales1 · FranciscoJ.Rivero1 · IsmaelMuela1
Accepted: 14 August 2023 / Published online: 16 September 2023
© The Author(s) 2023
Abstract
Purpose of Review Here, we systematically review all available evidence on the triadic relationship between positive and
negative urgency, craving, and severity of symptoms of candidate behavioral addictions.
Recent Findings Current theoretical models attribute a central importance to craving in the chronification and prognosis of
behavioral addictions and other problematic non-substance-related behavioral patterns. Craving, in turn, has been convinc-
ingly shown to be an affect-laden state, and its control can be conceptualized as partially resulting from emotion regulation
mechanisms. However, some gaps remain: first, there is no consensus on the predominantly appetitive or aversive nature of
craving; and, second, although positive and negative urgency have been proposed as proxies to incidental emotion regulation
mechanisms, their direct or indirect role in craving regulation and severity of problematic behaviors is still poorly known.
Summary According to our results, craving emerges as a central construct, partially resulting from emotion dysregulation
as assessed by urgency. The preponderance of positive urgency shown by most studies in this review also reinforces the
view of positive emotions as a ‘trojan horse’ in addictive processes. Negative urgency, in turn, seems to be a complication
factor that could underlie gambling addiction and other related mental health conditions. Most studies, however, are about
gambling behavior, with the few studies in other domains precluding firm conclusions about the differences or similarities
between them.
Keywords Severity· Craving· Positive urgency· Negative urgency· Impulsivity· Behavioral addiction
Introduction
Despite not being explicitly listed as a diagnostic criterion
in current nosologies [1, 2], craving has been attributed a
key role in the etiology of gambling disorder (GD) [3] and
other candidate behavioral addictions [4]. This has caused a
proliferation of craving scales for these conditions [3, 5–7].
Unfortunately, with noteworthy exceptions (e.g., [8]), such
a proliferation has not been accompanied by an analogous
effort to study the etiological mechanisms of craving or its
processual similarities across behavioral domains.
Among the aspects of craving in non-substance addictions
remaining to be clarified, there is no consensus regarding its
predominantly aversive or appetitive nature [9, 10]. If consid-
ered a negative affective state, craving would account for addic-
tive behavior maintenance by virtue of negative reinforcement
(i.e., avoidance or escape; [11, 12]). This aversive state can
be triggered by stress or physiological symptoms, but also by
cues that have previously been associated with the object of
* Ismael Muela
imuela@ugr.es
José López-Guerrero
joselogue@ugr.es
Juan F. Navas
junavas@ucm.es
José C. Perales
jcesar@ugr.es
Francisco J. Rivero
franrivero@ugr.es
1 Department ofExperimental Psychology; Mind, Brain
andBehavior Research Center (CIMCYC), University
ofGranada, Granada, Spain
2 Department ofClinical Psychology, Complutense University
ofMadrid, Campus de Somosaguas, Ctra. de Húmera, S/n,
28223 Pozuelo de Alarcón, Madrid, Spain
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719Current Addiction Reports (2023) 10:718–736
1 3
addiction [13, 14]. Alternatively, some well-supported models
conceptualize craving as a predominantly appetitive state [15].
For instance, the Incentive-Sensitization Theory of addiction
(IST) [16] suggests that reiterative stimulation of the meso-
corticolimbic pathways by addictive agents would increase
the incentive properties of cues related to such agents, turning
them into “motivational magnets” and generating maladaptive
“wanting” that progressively decouples from the pleasure of
consummation, or “liking” [17]. Complementarily, according to
the Elaborated Intrusion Theory of desire (EIT) [18], this state
would be accompanied by reward-related intrusive thoughts and
imagery that would interfere with its control.
Nonetheless, aversive and appetitive components could
coexist in craving states [10, 19]. Moreover, the affective con-
tent of craving may differ from person to person, and may even
change at different stages of addiction, or different contexts [9,
18]. Whatever the case, the emotional or affective nature of
craving is uncontroversial, and hence craving control can be
considered, at least in part, as emotion regulation [20].
Emotion dysregulation is an umbrella term for a range of dif-
ficulties to modulate the valence, intensity, and time course of
emotional or affective states, so that emotions transpire in ways
that hinder progress towards one’s goals, and increase the sus-
ceptibility to some mental health conditions, including addictive
disorders [21–24]. According to recent literature, certain types
of emotion dysregulation are expressed as a proneness to rash
action under the influence of strong positive and negative affect
[25–27]. This proneness –known as urgency or emotion-driven
impulsivity– is a component in the UPPS-P impulsive behavior
model (along with lack of premeditation, lack of perseverance
and sensation seeking [28]), and has two facets (positive and
negative urgency), depending on the valence of the underly-
ing emotional state. Importantly, urgency has been specifically
linked with malfunctioning of automatic or incidental aspects
of emotion regulation [29].
In more direct connection with the aims of the present
study, Chester etal. [30] pioneered the idea that urgency
could be involved in the vulnerability of individuals to
acquire conditioned craving responses in substance use
disorder (SUD), or in the impact of such craving states
on lack of control over addictive behaviors. That idea was
further extended to gambling disorder by Navas etal. [31],
and other candidate behavioral addictions by Perales etal.
[32••]. According to them, urgency would be a risk factor
for addiction by fueling craving. Hence, craving is expected
to mediate the effect of urgency on addictive behaviors.
Complementarily, urgency could also impact addic-
tive behaviors independently of craving. Actually, some
evidence exists that urgency could underlie problematic
behaviors that are not in the core of behavioral addiction
but could be comorbid with it, and could increase its sever-
ity and ensuing harms [31, 32••, 33, 34•].
Aims andScope ofthePresent Review
Beyond the mere correlations between urgency, craving, and
addictive behavior, there are important gaps in the literature
that need to be addressed. First, it remains under-investigated
whether positive or negative urgency plays a larger role in crav-
ing and the severity of addictive behaviors. And second, con-
ditional associations between constructs could cast light on the
etiology of craving and behavioral addictions. Effects of urgency
on addictive behaviors that survive after statistically control-
ling for craving would reveal a direct impact of urgency on the
severity of behavioral addiction that is not mediated by craving
regulation mechanisms. Complementarily, mediation analyses
involving urgency, craving, and severity of addictive behaviors
would clarify the form of the joint contribution of craving and
urgency to behavioral addictions.
Our review will thus include behavioral addictions currently
acknowledged by current psychiatric classifications, namely
GD and IGD, as well as other conditions not involving the use
of substances with substantial support in the literature for its
potential future inclusion in the category of behavioral addic-
tions. Depending on the methodological approach and the type
of results provided, studies will be classified in the following
categories. Level 1 studies will include those assessing bivariate
correlations between the variables of interest. Level 2 studies
will include regression and conceptually similar analyses (e.g.,
hierarchical and multilevel modeling) that pitch craving against
urgency measures as predictors of behavioral addiction sever-
ity measures, and urgencies against each other as predictors of
craving. These studies may provide information on the relative
weights of the associations of positive and negative urgency with
craving, and thus help clarify the appetitive/aversive nature of
craving in the realm of behavioral addictions. Complementarily,
they could reveal whether urgency can contribute to severity
by ways that are not related to craving control. Finally, Level 3
studies are causality-informed ones, including prospective or
longitudinal research, and studies using structural-equation mod-
eling or path analysis techniques. Assuming causal precedence
of traits over transient states, reported links can clarify whether
urgency predicts symptoms directly, or indirectly (via craving).
Again, a direct path would imply that urgency can affect gam-
bling/gaming problems independently of craving. The indirect
path, in turn, could be interpreted as evidence that people with
high urgency scores experience stronger cravings, that is, that
urgency contributes to the emergence of craving awareness.
Method
This systematic review was conducted following the PRISMA
guidelines [35]. The flowchart (Fig.1) illustrates the process
followed during the search, screening, and item selection
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720 Current Addiction Reports (2023) 10:718–736
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phases. In addition, the entire workflow was pre-registered in
Prospero on January 1st, 2023, and can be accessed through the
following link: https:// www. crd. york. ac. uk/ prosp ero/ displ ay_
record. php? Recor dID= 386907. The only substantial deviation
from the protocol was the substitution of the Cochrane Collabo-
ration risk-of-bias assessment tool (as this is aimed at clinical
studies, and not really appropriate in our case).
Eligibility Criteria
To be included in the review, studies had to meet the following
inclusion criteria: (IC1) to be a peer-reviewed primary study;
(IC2) to explicitly measure urgency, behavioral addiction symp-
toms severity, and craving-related measures with validated instru-
ments (i.e., self-reports instruments), or behavioral or neurophysi-
ological measures of reactivity to realistic craving-triggering
cues; and (IC3) to have been carried out with participants regu-
larly engaged in gambling, video gaming, or other non-substance,
potentially addictive activity, proposed as such in the literature,
included or not in currently dominant psychiatric classifications.
Recovered items were excluded if they met the following
exclusion criteria: (EC1) impossibility to retrieve the full-
text manuscript; (EC2) not being a primary study (i.e., any
kind of review or monograph), or not to be a peer-reviewed
report (i.e., dissertations, posters, commentaries, books and
book chapters, essays, andcorrigendaorerrata); and (EC3)
not being written in English, Spanish, French or Portuguese.
Finally, we contacted the corresponding authors of those
studies that met the inclusion criteria, but in which reported
analyses could not provide information of interest for the
purpose of the systematic review. The inclusion or exclusion
of these articles depended on whether or not the authors
provided the requested information on analyses or data.
Search Strategy andInformation Sources
Four electronic bibliographic databases (PubMed, ProQuest,
Scopus and Web of Science) were examined for eligible
studies. Search algorithms are disclosed in Sect.1 of the
Appendix.
The search was conducted on January 11th, 2023.
Complementarily, a backward and forward citation anal-
ysis was conducted to uncover the most relevant previ-
ous and derivative works that were missed in the initial
search and that could serve as eligible records for the
goals of the study. The searches were rerun on March
3rd, 2023 to check if any new documents had surfaced
since January 11th.
Selection Process
The first, fourth and last authors independently conducted
the automatic term-based search. After removing duplicate
records, the title and abstract of the remaining papers were
screened in order to check for inclusion criteria. In case the
title and abstract did not provide sufficient information to
apply the inclusion criteria, the article was retrieved and
assessed entirely. To ensure the three authors were totally
independent carrying out their task of deciding whether or
not to select an article, each of them made an independent
Records identified through
database searching:
(n = 76)
PUBMED = 10
SCOPUS = 14
WEB OF SCIENCE = 28
PROQUEST = 24
Records removed before
screening:
Duplicate records (n =44)
Records screened (title and
abstract):
(n = 32)
Recordsexcluded
(n =14)
Reportssought for retrieval
(n =18)
Reportsnot retrieved
(n =0)
Reports assessed for eligibility
(n =18)
Reportsexcluded:
Not a primary study(n =5)
Absence of any measure of
interest (n =5)
Not written in English,
French, Portuguese or
Spanish languages(n =3)
Recordsidentified from:
Citation searching(n =6)
In-press literature (n = 2)
Reportsassessed for eligibility
(n =8)Reportsexcluded:
Absence of any measure of
interest (n = 3)
Identification of studies via databases and registersIdentification of studiesvia other methods
noitacifitnedI
gnineercS
dedulcnI
Reportssought for retrieval
(n =8)
Reportsnot retrieved
(n =0)
Studies included in review
(n = 5, from databases and
registers)
(n = 5, from other methods)
Fig. 1 PRISMA flowchart for article selection
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721Current Addiction Reports (2023) 10:718–736
1 3
judgment for each retrieved record. Inter-rater disagree-
ments regarding the inclusion of the studies were solved by
discussion. In case a difference remained unresolved, the
third author was brought into the discussion until consen-
sus was reached. Subsequently, once a set of studies had
been retained, a backward and forward citation analysis was
conducted to uncover relevant studies that were missed in
the initial search. Any study known by these means to be in
early stages of the publication process (under review or in
press) was considered and assessed using the same eligibil-
ity criteria.
Data Collection Process
Table1 shows a summary of the main features and con-
clusions of the selected articles. As noted earlier, in case
a selected paper recorded the variables of interest, but the
authors had not provided the relationship between them in
the original paper, corresponding authors were directly con-
tacted by e-mail. In order to remain as undemanding as pos-
sible, we only asked for information on correlations between
the variables of interest, or for access to the raw scores in
these measures to perform the necessary analyses ourselves.
Statistical Analyses
Results directly reported in the original studies were comple-
mented with regression and mediation analyses performed
on complete datasets when these were openly accessible
[37], when provided on demand by the original authors
[41–43], or belonged to studies by our own team [33, 34•,
39]. For the sake of systematicity, we report comparable
analyses across samples.
First, raw correlations between constructs of interest were
collected and, when necessary, recalculated as r coefficients
(i.e., when they were reported in the original articles using
correlation indices other that r). Correlation coefficients as
originally reported are however available in Sect.2 in the
Appendix. Secondly, we regressed craving upon positive
and negative urgency (with age and gender as covariates
when these were available). Third, we regressed behavioral
addiction symptoms severity on craving, positive urgency
and negative urgency, with the same potential confounders
when available. Finally, we ran mediation analyses on the
same datasets with positive and negative urgency as input
variables, craving as mediator, and severity as output vari-
ables. Age and gender were included as background con-
founders when possible (as well as sample source in the
analysis conducted on the video gamers dataset). In all cases,
analyses were run with the default parameters in the JASP
statistical analysis package 0.17.1 [44]. Unfortunately, these
analyses cannot be publicly shared as we do not hold rights
over part of the data. Still, original databases are publicly
accessible in the case of four studies [33, 34•, 37, 39].
Study Quality andSensitivity
General quality of all studies, including risk of bias and
internal validity, was independently assessed by two review-
ers. The methodological details of the tool used, and the
procedure followed are fully disclosed in Sect.3 of the
Appendix. The final quality categorization is shown in the
rightmost column of Table1. All studies present a fair or
good level of quality. They were independently rated by the
first and last authors, resulting in a good agreement between
the two experts (κ = 0.730) in the first round. Disagreement
was resolved by discussion and consensus.
Additionally we assessed sensitivity for correlational and
regression analyses. For correlation analyses we computed
the minimum detectable correlation (calculated as r), so that,
for the actual sample size in each study, it can be easily
assessed whether the study was underpowered to declare as
significant the observed correlation reported. For regression
analyses, we report the minimum detectable non-corrected
model R2, namely, the amount of variance explained by the
whole set of predictors that was detectable with the cur-
rent sample size for each regression analysis and dataset.
The procedure followed, and the results of these sensitivity
analyses are disclosed in Sect.4 of the Appendix.
Results
Study Selection
The automatic term-based search conducted independently
by the three authors resulted in the retrieval of 76 studies,
32 of which remained after removing duplicate records.
27 articles were excluded after applying eligibility crite-
ria. Therefore, a final set of 5 studies were retained after
the full-search procedure [36–40]. The backward and for-
ward citation analysis added 3 items to the previous search
[41–43]. Finally, as described in the "Selection Process"
section, 2 records known to be in the process of publica-
tion, and meeting the inclusion criteria, were also included
[33, 34•].1The authors of one of the selected papers did
not respond to our request, so, in terms of evaluation and
discussion, 9 records containing 10 samples were finally
included in this systematic review.
1 Although these studies were recovered from gray literature when
the search was conducted, both of them are now published.
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722 Current Addiction Reports (2023) 10:718–736
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Table 1 Descriptive information of the selected articles
Study NParticipants Severity index Urgency index Craving index Behavioral disorder Type of study Main findings Quality
assessment
Schulte etal. (2021) [36] 46 26 OO
20 FA
YFAS 2.0 UPPS-P FCI Food Addiction Level 1 Higher emotional dysregula-
tion, cravings and impulsivity
are found in overweight indi-
viduals who are also affected
by food addiction
Fair
Cornil etal. (2021) [37] 38
38
38 Gm
38 Gm
PGSI S-UPPS-P g-CEQ Gambling Level 1 Methods with and without
mental imagery are successful
in reducing craving induced
in the laboratory
Good
Shirk etal. (2021) [38] 172 172 UPo PPUS UPPS-P PCQ Problematic Pornography
Use
Level 2 Problematic pornography use
is associated with psychiatric
comorbidities, frequency of
use and craving
Fair
Quintero etal. (2020) [39] 70 65 Ge
5 NG
SOGS UPPS-P GCS Gambling Level 2 Negative urgency is a complex
construct. It was found to
predict higher craving scores
and craving, in turn, predicted
more severity
Good
Albein-Urios etal. (2014) [40] 26 26 GD SCID UPPS-P WCQ Gambling Level 1 The groups generated in a
latent class analysis showed
differences in impulsivity that
did not appear in groups with
conventional diagnoses
Fair
Cornil etal. (2019) [41] 274 274 Gf PGSI S-UPPS-P g-CEQ Gambling Level 1 The new scale based on the
Elaborated Intrusion Theory
of desire (g-CEQ) can be
used to measure gambling
craving in clinical and
research contexts
Fair
Kim etal. (2021) [42] 213 213 Gc PGSI S-UPPS-P GACS Gambling Level 1 Offering tangible rewards in
social casino games may
increase participation in these
games, but not necessarily the
decision to gamble with real
money
Fair
Canale etal. (2019) [43] 165
256
165Gy
256Gy
PGSI S-UPPS-P GACS Gambling Level 1 The French Gambling Craving
Scale (GACS) has good psy-
chometric properties, which
justifies its use in research
and clinical work
Fair
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723Current Addiction Reports (2023) 10:718–736
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Study Characteristics andData Availability
Table1 shows the characteristics of the 10 initial studies. Of
these, 6 were initially classified into Level 1 category [36, 37,
40–43], 2 as Level 2 [38, 39], and 2 as Level 3 [33, 34•, 37, 41,
42]; three others performed correlation analyses between the
variables of interest for us and shared their results [36, 40, 43];
and the remaining 3 other studies belong to our own team [33,
34•, 39], so we had direct access to all data. As noted earlier,
the necessary data or analyses never became available for one
of the studies, so it is not included in further analyses.
We therefore ended up with 9 studies that fitted into the Level
1 category, 2 into Level 2, and 2 into Level 3. After contacting
the authors, we ended up with 6 studies for which we had the
necessary information to conduct Level 2 and Level 3 analyses.
Unfortunately, these studies were not representative of the diver-
sity of potential behavioral addictions (1 study on food addic-
tion; 1 study on video gaming; 7 studies on gambling).
Level 1 Analyses
Correlations between constructs of interest across studies are dis-
played in Table2. Correlations that were not originally reported
as r coefficients have been recalculated to allow comparability
and pooling of effects across studies. Correlations as originally
reported (specifying the correlation index used) are available in
Sect.2 the Appendix accompanying this manuscript.
To make interpretation easier, these correlations have
been meta-analyzed across studies. Pooled effects and
confidence intervals for all studies (9 datasets), as well as
separately for gambling only (7 datasets) are reported in the
two bottom lines of Table2. The statistical features of these
meta-analyses are detailed in Sect.5 of the Appendix.
Findings fromCorrelation Analyses Between Urgency
andSeverity
The correlational analyses reported here correspond to 9
datasets from 8 studies (the authors of one of the stud-
ies were only able to share the results of the correlations
between urgency and craving, as the gambling severity
variable was categorical, and no quantitative severity
measure was available). Symptoms severity and positive
and negative urgency were positively correlated in almost
all cases [33, 34•, 41–43]. The only exceptions were (a)
Quintero etal.'s study [39], where gambling severity was
not significantly correlated with negative urgency; (b) the
two samples from [37], in which negative and positive
urgency correlated positively with gambling severity, but
without reaching significance; and (c) the study on food
addiction [36], where a significant positive correlation
was found between negative urgency and severity, but not
between positive urgency and severity.
Table 1 (continued)
Study NParticipants Severity index Urgency index Craving index Behavioral disorder Type of study Main findings Quality
assessment
Muela etal. (2023) [33] 81 81 Gm SOGS
PGSI
UPPS-P GACS Gambling Level 3 Positive urgency, as a trait
indicating emotional dys-
regulation, predicts craving
and severity in a sample of
problem gamblers
Good
Rivero etal. (2023) [34•] 232
222
232 SfVGp
222 EfVGp
IGD9 S-UPPS-P CVG Gaming Level 3 Dysregulation of positive affect
influences the onset and
control of craving. Craving,
in turn, emerges as a central
feature in gaming severity
Fair
OO Overweight or Obesity; FA Food Addiction; YFAS 2.0 Yale Food Addiction Scale 2.0; UPPS-P Impulsive Behavior Scale (59 items); FCI Food Craving Inventory; Gm Gamblers at least
once a month; PGSI Problem Gambling Severity Index; S-UPPS-P Short UPPS-P Impulsive Behavior Scale (20 items); g-CEQ gambling Craving Experience Questionnaire; UPo Users of
Pornography; PPUS Pornography Use Scale; PCQ Pornography Craving Questionnaire; Ge Gamblers who had ever gambled; NG Non-Gamblers; SOGS South Oaks Gambling Screen; GCS
Gambling Craving Scale developed for the study; GD Gambling Disorders; SCID Structured Clinical Interview for DSM-IV Disorders-Clinician Version; WCQ Weiss Craving Questionnaire; Gf
Gamblers at least a few times a year; Gc Gamblers who gambled and played social casino games; GACS Gambling Craving Scale; Gy Gamblers who had gambled at least once in the past year;
SfVGp Spanish frequent Video Game players; EfVGp Ecuadorian frequent Video Game players; IGD9 Internet Gaming Disorder Scale; CVG Craving for Video Games
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724 Current Addiction Reports (2023) 10:718–736
1 3
Pooled effects show a slightly stronger correlation
between positive urgency and severity than between nega-
tive urgency and severity, a difference that seems slightly
larger for gambling studies than for the whole set of stud-
ies. This discrepancy seems to be due to the fact that
Schulte etal.’s food addiction study shows a difference
in a direction opposite to the other studies, with negative
urgency more strongly correlated with severity than posi-
tive urgency.
Findings fromCorrelation Analyses Between Urgency
andCraving
The correlational analyses reported here correspond to
10 datasets from 9 studies. For the 7 gambling studies (8
datasets in total), results were not totally consistent. In 4 of
the datasets, the relationship between positive urgency and
craving was higher than the one between craving and nega-
tive urgency, with 3 of these relationships being statistically
significant (this pattern of results was the same for the data-
set of video gamers). In the remaining 4 datasets, we found
3 statistically significant relationships between negative
urgency and craving. Finally, the study on food addiction
showed a statistically significant and positive relationship for
negative urgency and craving, but not for positive urgency.
As it happened with urgency-severity correlations, pooled
effects show a slightly stronger correlation with craving for
positive than for negative urgency. The magnitude of that
difference was similar for gambling studies and the whole
set of studies. However, Rivero etal.’s video gaming study
Table 2 Results of the correlations between the variables of interest and pooled effects (meta-analysis)
For the fourth study [40], we provide information regarding craving as measured with the Weiss Craving Scale, and with a visual analogue scale
(VAS), respectively. Similarly, for the fifth study [41], we provide information regarding craving as measured with the gambling Craving Experi-
ence Questionnaire for Frequency (g-CEQ-F), and with the Gambling Craving Scale (GACS), respectively. NU negative urgency; PU positive
urgency. Results in bold indicate statistically significant results. * p < .05, ** p < .01, *** p < .001. Note: The original values reported in each of
these studies (differing in the specific correlation index used) can be found in Sect.2 of the Appendix
Study Samples Severity-NU Severity-PU Severity-Craving NU-PU Craving-NU Craving-PU
Schulte etal.
(2021) [36]
S1 .502*** 0.165 .429* .636*** .333* .165
Cornil etal.
(2021) [37]
S1 .115 .242 .752*** .586*** .240 .278
S2 .178 .266 .485** .478** .269 .186
Quintero etal.
(2020) [39]
S1 .160 .269* .609*** .425*** .254* .448***
Albein-Urios etal.
(2014) [40]
S1 - - - .814*** .695**/.662** .266/.286
Cornil etal.
(2019) [41]
S1 .179** .221*** .650***/.408*** .573*** .128*/.241*** .104/.136*
Kim etal. (2021)
[42]
S1 .395*** .471*** .468*** .697*** .247*** .312***
Canale etal.
(2019) [43]
S1 .259*** .228** .556*** .595*** .307*** .270***
Muela etal.
(2023) [33]
S1 .387*** .415*** .501*** .507*** .224* .512***
Rivero etal.
(2023) [34•]
S1 .198*** .265*** .579*** .543*** .111* .252***
Pooled effects [CI] for all
studies
.272 [.191, .352] .297 [.219, .375] .537 [.467, .608] .580 [.525,
.636]
.227 [.163, .291] .289 [.204, .375]
Heterogeneity Q statistic 17.501* 16.370* 21.163** 16.218* 8.240 18.483*
I254.47% 52.30% 64.85% 49.95% 27.39% 60.30%
Tau2.0073 (.0072) .0064 (.0067) .0067 (.0056) .0031 (.0033) .0024 (.0043) .0091 (.0082)
Publication bias Egger’s test -.881 -.656 -.299 -1.246 1.248 -.051
Pooled effects [CI] for gam-
bling studies
.264 [.175, .354] .314 [.218, .409] .538 [.449, .626] .580 [.509,
.651]
.256 [.194, .318] .309 [.201, .417]
Heterogeneity Q statistic 10.711 14.074* 18.349** 13.170* .718 17.287**
I245.09% 54.61% 67.59% 54.55% 0% 64.70%
Tau2.0060 (.0080) .0083 (.0093) .0091 (.0081) .0044 (.0051) 0 (.0037) .0127 (.0120)
Publication bias Egger’s test -1.014 -.589 .372 -2.109* -.047) .032
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725Current Addiction Reports (2023) 10:718–736
1 3
and Schulte etal.’s food addiction study showed differences
in opposite directions, with the former showing a clearly
stronger correlation for positive urgency and the latter show-
ing a stronger correlation for negative urgency. Among gam-
bling studies, results are mixed.
Findings from Correlation Analyses Between Crav‑
ing and Severity, and Between Positive and Negative
Urgency As expected, in all datasets where it was possible
to assess the relationship between craving and severity (9
datasets from 8 studies), the results showed a strong posi-
tive relationship. The same can be said of the relationship
between the two urgency facets (10 datasets from 9 studies).
Pooled effects reflect this consistency, supporting the previ-
ously presented proposals that craving strongly contributes
to severity of behavioral addictions, and that positive and
negative urgency probably reflect different facets of a com-
mon construct.
Level 2 Analyses
In most cases, age and sex/gender were included in analyses
as control covariates. This was not the case for the regres-
sion analyses conducted on two specific datasets. In one of
them [34•], data source was also included as covariate, and
in the other [42] these variables were not available. These
regressions (as well as the mediation analyses shown later)
were not meta-analyzed due to the small number of studies
available, and to the heterogeneity arising from the added
non-systematicity of covariate control and target behavio-
ral domain, which would have probably rendered pooled
effects misleading. In the following subsections we report
the standardized regression coefficient (β), the t statistic,
and the observed p value for each significant predictor. R2
values correspond to each complete regression model such
effects belong to, including the theoretically relevant pre-
dictors and the covariates (when included in the model).
Detailed results from all regression models are disclosed
in Sect.6 of the Appendix.
Findings fromRegression Analysis ofCraving Over Positive
andNegative Urgency
Regression results showed some degree of consistency
between them and with the previously reported correlations.
In 4 datasets [33, 34•, 39, 42], only positive urgency was posi-
tively and independently associated with craving (β = 0.530,
t = 4.626, p < 0.001, R2 = 0.275; β = 0.145, t = 2.993, p = 0.003,
R2 = 0.297; β = 0.379, t = 3.214, p = 0.002, R2 = 0.282;
β = 0.271, t = 3.250, p = 0.001, R2 = 0.099). In 1 dataset [41]
negative urgency was associated with craving, when meas-
ured by the Gambling Craving Scale (GACS, [45]; β = 0.236,
t = 3.228, p = 0.001, R2 = 0.060), whereas positive urgency was
not. There were no significant associations between urgency
and craving in the 2 datasets from [37], nor in the one [41]
in which craving was measured by the frequency form of the
gambling Craving Experience Questionnaire (g-CEQ-F). In
other words, the previously shown privileged association
between positive urgency and craving (over the one between
negative urgency and craving) for the gambling and video
gaming studies seems to emerge more clearly when positive
and negative urgency are pitched against each other. The only
dataset showing the opposite pattern [41] is the one for which
the model had the smallest predictive power, as measured by
R2.
Findings fromRegression Analysis ofSeverity overPositive
andNegative Urgency, andCraving
Here the results were mixed. In 2 datasets [41, 42], gambling
severity was positively associated with positive urgency
(β = 0.174, t = 2.611, p = 0.010, R2 = 0.207; β = 0.285,
t = 3.896, p < 0.001, R2 = 0.342) and craving (β = 0.392,
t = 6.984, p < 0.001, R2 = 0.207; β = 0.352, t = 6.534,
p < 0.001, R2 = 0.342). This pattern of results was the same
when craving was measured by the g-CEQ-F in the first
[41] of these two datasets (β = 0.130, t = 2.370, p = 0.018
for positive urgency; β = 0.652, t = 14.127, p < 0.001 for
craving; R2 = 0.463). In 2 datasets [33, 34•] β = 0.252,
t = 2.377, p = 0.020, R2 = 0.381; β = 0.109, t = 2.409,
p = 0.016, R2 = 0.365) and craving (β = 0.435, t = 4.074,
p < 0.001, R2 = 0.381; β = 0.499, t = 11.093, p < 0.001,
R2 = 0.365). And, in the 3 remaining datasets [37, 39] only
craving was positively associated with gambling sever-
ity (β = 0.712, t = 5.708, p < 0.001, R2 = 0.592; β = 0.455,
t = 2.925, p = 0.006, R2 = 0.285; β = 0.637, t = 5.465,
p < 0.001, R2 = 0.376) whereas urgency was not. In all cases,
the strength of the association of gambling severity with
craving was larger than with (positive or negative) urgency.
Level 3 Analyses
As noted earlier, in these analyses craving was modelled
as a partial mediator of the effects of positive and negative
urgency on symptoms severity, under the assumption that
basic emotion regulation dysfunction (as measured by urgen-
cies) makes vulnerable individuals experience stronger crav-
ings and these translate into more severe behavioral prob-
lems. At this level, we did not consider the studies in which
results showed no significant correlations between urgencies
and severity to begin with (i.e., both datasets from [37]).
In one of the remaining datasets [41], there was a sig-
nificant direct effect of positive urgency on the severity
score (β = 0.081, z = 2.640, p = 0.008). The direct effect of
negative urgency on severity was not significant (β = 0.070,
z = -0.123, p = 0.902), but its indirect effect via craving was
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
726 Current Addiction Reports (2023) 10:718–736
1 3
significant (β = 0.032, z = 2.958, p = 0.003). The indirect
effect of positive urgency was not significant (β = 0.034,
z = -0.069, p = 0.945). The total effect was significant only
for positive urgency (β = 0.088, z = 2.401, p = 0.016), but not
for negative urgency (β = 0.075, z = 1.163, p = 0.245).
In a second dataset [42], a strong direct effect of posi-
tive urgency on severity (β = 0.464, z = 3.927, p < 0.001)
and an indirect effect of also positive urgency via craving
(β = 0.209, z = 2.928, p = 0.003) were found. The direct
effect of negative urgency on severity (β = 0.448, z = 1.531,
p = 0.126) and the indirect effect via craving (β = 0.185,
z = 0.696, p = 0.486) were not significant. Again, total
effects were only significant for positive urgency (β = 0.492,
z = 4.950, p < 0.001), but not for negative urgency (β = 0.484,
z = 1.683, p = 0.092).
In a third dataset [33], negative urgency (β = 0.434,
z = 2.470, p = 0.014) but not positive urgency (β = 0.626,
z = 0.660, p = 0.509) had a significant direct effect on sever-
ity. However, positive urgency had an indirect effect via
craving (β = 0.392, z = 3.168, p = 0.002) whereas negative
urgency did not (β = 0.205, z = -0.393, p = 0.694). Both nega-
tive (β = 0.479, z = 2.069, p = 0.039) and positive (β = 0.611,
z = 2.079, p = 0.007) urgency yielded significant total effects.
A fourth dataset [34•] yielded the same pattern of results.
Negative urgency (β = 0.129, z = 2.427, p = 0.015) but not
positive urgency (β = 0.164, z = 1.478, p = 0.178) showed a
significant direct effect on video gaming severity. For indi-
rect effects, it was positive urgency (β = 0.088, z = 2.909,
p = 0.004) but not negative urgency (β = 0.068, z = 0.553,
p = 0.581) the impulsivity dimension that had an effect on
severity via craving. Total effects resulted statistically sig-
nificant for both positive (β = 0.183, z = 2.605, p = 0.009) and
negative urgency (β = 0.146, z = 2.407, p = 0.016).
In a fifth dataset [39], we only found an indirect effect of
positive urgency on the severity score via craving (β = 0.390,
z = 2.880, p = 0.004), but not for negative urgency or the rest
of effects.
Discussion
The aim of this review was to explore the available evidence
on the triadic relationship between urgency, craving and
severity of behavioral addiction symptoms, and to assess
its compatibility with current theoretical approaches to the
etiology of craving and its role in non-substance addictive
processes.
Ten studies that met the inclusion criteria were identified
through a systematic literature search. Relevant information
was accessible for 9 of the studies, so these 9 considered
for analysis and discussion. 7 of these studies were about
disordered or problematic gambling, 1 about food addiction,
and 1 about problematic use of video games. By itself, this
scarcity of studies reflects that the conjoint role of urgency
and craving in non-substance problematic behaviors is an
under-researched topic, especially in behavioral domains
other than gambling.
The studies taken into consideration present a fair or good
level of quality, so their general validity seems not to be
compromised. All of them used self-report measures, and
most of them did not perform power or sensitivity analyses
to calculate the necessary sample size (see Sect.3 of the
Appendix for an item-by-item assessment of study quality).
Our a posteriori quality and sensitivity analyses show, how-
ever, that limited power or differences in quality are probably
not affecting the interpretability of results. In general, better
powered, good quality studies did not yield results that look
substantially different from those with smaller samples or a
fair quality level (although the possibility to use these qual-
ity indices as moderators is precluded by the small number
of studies available). This is probably due to the fact that
the triadic urgency-craving-severity relationships were not
the focus of these studies. That is, although these constructs
were measured, their significance or relative strength were
not central to test the focal hypothesis of most studies, so
there was not a clear incentive to incur questionable research
practices or publication bias.
Taken together, the correlational results show a clear
three-way association between the constructs of interest.
However, the association between craving and severity of
symptoms stands out as the strongest and most systemati-
cally replicated one. This association was robust, positive,
and significant in all analyses under scrutiny, and thus also
after pooling, which reveals the crucial role of craving in the
etiology of behavioral addictions. The central position of
craving for the prediction of gambling-related symptoms and
other patterns of problematic behavior suggests that craving
should be considered a core symptom of behavioral addic-
tion, and should be included in its diagnosis and definition,
in line with recent theoretical proposals [3, 46, 47••].
Among the other correlations, the ones between sever-
ity and urgency dimensions were relatively consistent
among them and with pooled correlations, with positive
urgency correlating with severity more strongly than nega-
tive urgency in most cases. 4 of the 7 gambling datasets
showed a significant positive correlation of both urgency
dimensions with gambling severity, and the same result
was found in video game players. In the 3 remaining gam-
bling studies, 2 found no significant urgency-severity
associations, and 1 found a positive relationship between
positive urgency and severity. In contrast, in the food
addiction sample, it was negative urgency (instead of
positive urgency) the dimension significantly associated
with severity. So, this study is the clearest exception to
the general trend. Although this could be attributable to
the different behavioral domain under scrutiny, it is soon
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727Current Addiction Reports (2023) 10:718–736
1 3
to derive any conclusions in this direction. Still, a promis-
ing line of future research would be to directly attempt a
corroboration of this difference by directly comparing dif-
ferent domains of problematic behavior in a single study.
On the contrary, the correlations between craving and
urgency dimensions were less consistent, making it diffi-
cult to draw strong conclusions from correlation analyses
alone. Fortunately, regressions partly clarified the mean-
ing of these correlations. The most salient result was that,
once craving was controlled for, the associations between
urgencies and severity were substantially attenuated.
Seemingly, a substantial part of the effect of positive and
negative urgency on severity is explained away by crav-
ing. This is compatible with the abovementioned idea that
craving is a core component of behavioral addictions, but
also with the one that the influence of urgency on severity
is channeled by the emergence of craving states.
Whether positive or negative urgency plays a stronger
role in craving emergence is, however, still uncertain,
although evidence seems to be more consistent for positive
than for negative urgency, which could indicate that regu-
lation of positive affect is more relevant for craving control
than regulation of negative affect. The origin of existing
differences in regression results across studies remains,
however, unclear. As noted earlier, these differences do not
seem to be determined by sensitivity or study quality. Ten-
tatively, it is possible that the relative role of positive and
negative affect regulation in craving emergence depends
on sample characteristics not taken into consideration in
the present review, as gaming/gambling preferences or
general sensitivity to reward and punishment.
Results from mediational analyses were mostly com-
patible with this view. 4 of the 5 datasets analyzed at
this level yielded a significant indirect effect of positive
urgency on symptoms severity, via craving. This indirect
effect is congruent with the proposal that craving consists
in part of appetitive or affectively positive components,
and that positive urgency impacts on the emergence or
regulation of such components. In other words, individu-
als with a tendency to lose control under positive affec-
tive states would experience more acute craving states in
the presence of reward-related cues, which in turn, would
interfere with attempts to control their potentially addic-
tive behavior [15, 17, 20].
In two datasets negative urgency was a significant direct
predictor of severity independently of craving. This finding
supports the models proposing that negative urgency can
be conceptualized as a common transdiagnostic factor in
externalizing behavior problems characterized by emotional
dysregulation [26, 27, 31]. High urgency in these individu-
als would manifest as a higher risk of comorbidities and
behavioral complications beyond lack of control over the
specific problematic activity. Importantly, however, the two
studies showing this effect are the one on video gaming
[34•], which also has the largest sample size in our review,
and only one on gambling [33], which is among the few ones
assessed as presenting the highest quality level. The latter
is also atypical in the sense that its sample was relatively
young, and consisted of mostly poker players and sport bet-
tors, which makes it more similar to the characteristic video
gamer sample. Although, again, it is soon to draw any con-
clusions, further research on the possibility that this pattern
(with negative urgency having a direct effect on severity,
and positive urgency having an indirect effect via craving)
is more characteristic of populations with these features or
playing preferences is warranted.
In summary, from the bulk of results it can be concluded
that (a) craving is associated with all other constructs under
assessment, which reinforces its centrality, and the idea that
it is an affective state and, as such, is sensitive to malfunc-
tioning of emotion regulation processes. (b) Positive and
negative urgency tend to independently correlate with crav-
ing for the activity in question, with positive urgency gen-
erally showing a stronger and more consistent association
with craving than negative urgency. This seems to imply
that aversive and appetitive states can coexist in craving, but
also that appetitive components probably play a more central
role, at least in the populations and activities assessed in the
present review. And finally, (c) the tight relations between
positive urgency and craving, on the one hand, and craving
and severity of symptoms, on the other, are combined in a
positive urgency-craving-severity chain. In contrast, nega-
tive urgency does not participate in that link to the same
degree, and frequently exerts a direct effect on severity that
could reflect the kind of complications that contribute to
the co-occurrence of some behavioral addictions (especially
gambling disorder) with other mental health conditions and
addictive behaviors (e.g., substance use disorders).
Limitations
These conclusions are however subject to a number of
considerations. First, the samples in the present review
are majoritarily convenience samples in which partici-
pants with clinically significant problems are underrepre-
sented. That could account for the prevalence of positive
over negative urgency in predicting craving, as it has been
proposed that the relative weight of positively and nega-
tively valenced components of craving could change as
the addictive process progresses, and problems become
more severe [48].
Second, apart from the severity range, there are other
features that could also limit the generalizability of
results. Most importantly, a number of studies have shown
that gamblers preferring high arousal, skill-based games,
such as sport betting or poker, are, on average, more
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
728 Current Addiction Reports (2023) 10:718–736
1 3
sensitive to reward than those preferring low arousal,
pure chance games as slot machines or scratch cards [49].
Although, to the best of our knowledge, it has never been
directly tested, the preponderance of positive motives
in skill-based games could make dysregulation of posi-
tive affect more important for gamblers preferring these
games, whereas dysregulation of negative affect would be
more consequential for gamblers preferring pure chance
games. Well-powered studies testing patterns of relations
across samples differing in severity or game preferences,
but using the same methods and measures, are long due.
Third, there are some exceptions to the general pattern
of relations found. The most noteworthy of them was the
finding of a direct effect of positive urgency on severity
in one of the gambling datasets [42]. This finding con-
verges with the pattern found in another gambling dataset,
in which a direct effect of positive urgency on severity,
and an indirect effect of negative urgency via craving were
observed [41]. In other words, at least in some cases, posi-
tive urgency could also have an influence on the develop-
ment of addictive behaviors independently of craving.
Fourth, and more generally, the scarcity of studies in
domains other than gambling that have used the three
measures of interest precludes drawing any conclusions
about potential differences between behavioral addictions.
The pattern of relations in the gaming study seems rather
similar to the prevailing one in gambling studies, whereas
the only study on food addiction diverges from that pat-
tern. More research is needed to know whether these simi-
larities and differences are more than mere coincidences.
Finally, it is important to note that different studies
often use different severity and craving scales. Although
severity scales are generally founded on a common diag-
nostic criteria approach, that is not the case for craving.
Actually, the definition of craving and the underlying
model can substantially differ across scales, with some
scales attributing more importance to the feelings expe-
rienced during craving, and others to the cognitive ele-
ments of attentional capture and elaboration. Tentatively,
that could explain why studies with the g-CEQ-F [41],
developed from the EIT model, seem to yield results dif-
ferent from those using other scales.
Conclusion
This review is the first to globally assess the pattern of rela-
tionships between urgency, craving, and severity of symp-
toms in bona fide or putative behavioral addictions. The
review has been successful in showing quite a congruent
picture of the role of craving and emotional impulsivity in
gambling addiction, in which craving emerges as a central
construct, partially resulting from emotion dysregulation as
assessed by urgency. The preponderance of positive urgency
shown by most gambling studies in this review also rein-
forces the view of positive emotions as a ‘trojan horse’ in
addictive processes [15]. Negative urgency, in turn, seems to
be a complication factor that could underlie gambling addic-
tion and other related mental health conditions.
For other putative behavioral addictions (only prob-
lematic gaming and food addiction) the available evidence
is clearly insufficient to draw firm conclusions, but this
review shows that our logic can be extended beyond gam-
bling. This review should inspire future attempts to estab-
lish the role of urgency and craving in these and other
candidate addictions without repeating the same mistakes,
making comparisons across samples and domains pos-
sible from the start, and prioritizing transparency and
reproducibility of results.
APPENDIX
Section1: Search Specifications perDatabase
All searches were conducted on January 11th and March 3th,
2023.
MEDLINE (via PUBMED: 1985‑Present)
• Fields: Title + abstract
• Limits: none
• Algorithm as per data base: (urgency[Title/Abstract] OR
UPPS*[Title/Abstract]) AND (craving[Title/Abstract]
OR "attentional capture"[Title/Abstract] OR "cue
reactivity"[Title/Abstract] OR urge[Title/Abstract] OR
urges[Title/Abstract]) AND ("gambling problems"[Title/
Abstract] OR "gambling disorder"[Title/Abstract] OR
"pathological gambling"[Title/Abstract] OR "prob-
lematic gambling"[Title/Abstract] OR "disordered
gambling"[Title/Abstract] OR "problem gambling"[Title/
Abstract] OR "gambling addiction"[Title/Abstract]
OR "gaming problems"[Title/Abstract] OR "gaming
disorder"[Title/Abstract] OR "disordered gaming"[Title/
Abstract] OR "disordered video gaming"[Title/Abstract]
OR "IGD"[Title/Abstract] OR "gaming addiction"[Title/
Abstract] OR "problematic gaming"[Title/Abstract] OR
"problematic video gaming"[Title/Abstract] OR "com-
pulsive overeating"[Title/Abstract] OR "compulsive
eating"[Title/Abstract] OR "eating addiction"[Title/
Abstract] OR hyperphagia[Title/Abstract] OR "binge
eating"[Title/Abstract] OR "uncontrolled eating"[Title/
Abstract] OR "food addiction"[Title/Abstract] OR
"internet use disorder"[Title/Abstract] OR "IUD"[Title/
Abstract] OR "internet addiction"[Title/Abstract]
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
729Current Addiction Reports (2023) 10:718–736
1 3
OR "love addiction"[Title/Abstract] OR "emotional
dependence"[Title/Abstract] OR smartphone[Title/
Abstract] OR "social media"[Title/Abstract] OR
"problem spending"[Title/Abstract] OR "com-
pulsive buying"[Title/Abstract] OR "compulsive
shop*"[Title/Abstract] OR workahol*[Title/Abstract]
OR "work addiction"[Title/Abstract] OR "compul-
sive sexual behavior*"[Title/Abstract] OR "compul-
sive sexual disorder"[Title/Abstract] OR "CSD"[Title/
Abstract] OR "compulsive sexual behavio*"[Title/
Abstract] OR "pornography use"[Title/Abstract]
OR "exercise addiction"[Title/Abstract] OR "com-
pulsive exercis*"[Title/Abstract] OR "compulsive
exercis*"[Title/Abstract])
• N = 10
Scopus (via Scopus; 1788‑Present)
• Fields: Title + Abstract
• Limits: none
• Algorithm as per database nomenclature: ( ( TITLE ( (
urgency OR upps*) AND ( craving OR "attentional cap-
ture" OR "cue reactivity" OR urge OR urges) AND ( "gam-
bling problems" OR "gambling disorder" OR "pathological
gambling" OR "problematic gambling" OR "disordered
gambling" OR "problem gambling" OR "gambling addic-
tion" OR "gaming problems" OR "gaming disorder" OR
"disordered gaming" OR "disordered video gaming" OR
"IGD" OR "gaming addiction" OR "problematic gaming"
OR "problematic video gaming" OR "compulsive overeat-
ing" OR "compulsive eating" OR "eating addiction" OR
hyperphagia OR "binge eating" OR "uncontrolled eating"
OR "food addiction" OR "internet use disorder" OR "IUD"
OR "internet addiction" OR "love addiction" OR "emotional
dependence" OR smartphone OR "social media" OR "prob-
lem spending" OR "compulsive buying" OR "compulsive
shop*" OR workahol* OR "work addiction" OR "compul-
sive sexual behavior*" OR "compulsive sexual disorder" OR
"CSD" OR "compulsive sexual behavio*" OR "pornography
use" OR "exercise addiction" OR "compulsive exercis*")))
OR ( ABS ( ( urgency OR upps*) AND ( craving OR "atten-
tional capture" OR "cue reactivity" OR urge OR urges) AND
( "gambling problems" OR "gambling disorder" OR "patho-
logical gambling" OR "problematic gambling" OR "disor-
dered gambling" OR "problem gambling" OR "gambling
addiction" OR "gaming problems" OR "gaming disorder"
OR "disordered gaming" OR "disordered video gaming" OR
"IGD" OR "gaming addiction" OR "problematic gaming"
OR "problematic video gaming" OR "compulsive overeat-
ing" OR "compulsive eating" OR "eating addiction" OR
hyperphagia OR "binge eating" OR "uncontrolled eating"
OR "food addiction" OR "internet use disorder" OR "IUD"
OR "internet addiction" OR "love addiction" OR "emotional
dependence" OR smartphone OR "social media" OR "prob-
lem spending" OR "compulsive buying" OR "compulsive
shop*" OR workahol* OR "work addiction" OR "compul-
sive sexual behavior*" OR "compulsive sexual disorder" OR
"CSD" OR "compulsive sexual behavio*" OR "pornography
use" OR "exercise addiction" OR "compulsive exercis*"))))
• N = 14
Web ofScience Core Collection (via Web ofScience;
‑Present)
• Fields: Title + Abstract
• Limits: Core Collection of Web of Science
• Algorithm per data base: (TI = ((urgency OR UPPS*) AND
(craving OR “attentional capture” OR “cue reactivity” OR
urge OR urges) AND (“gambling problems” OR “gam-
bling disorder” OR “pathological gambling” or “problem-
atic gambling” OR “disordered gambling” or “problem
gambling” OR “gambling addiction” OR “gaming prob-
lems” OR “gaming disorder” OR “disordered gaming”
OR “disordered video gaming” OR “IGD” OR “gaming
addiction” OR “problematic gaming” or “problematic
video gaming” OR “compulsive overeating” OR “compul-
sive eating” OR “eating addiction” OR hyperphagia OR
“binge eating” OR “uncontrolled eating” OR “food addic-
tion” OR “internet use disorder” OR “IUD” OR “internet
addiction” OR “love addiction” OR “emotional depend-
ence” OR smartphone OR “social media” OR “problem
spending” OR “compulsive buying” OR “compulsive
shop*” OR workahol* OR “work addiction” OR “compul-
sive sexual behavior*” OR “compulsive sexual disorder”
OR “CSD” OR “compulsive sexual behavio*” OR “por-
nography use” OR “exercise addiction” OR “compulsive
exercis*”))) OR AB = ((urgency OR UPPS*) AND (craving
OR “attentional capture” OR “cue reactivity” OR urge OR
urges) AND (“gambling problems” OR “gambling disor-
der” OR “pathological gambling” or “problematic gam-
bling” OR “disordered gambling” or “problem gambling”
OR “gambling addiction” OR “gaming problems” OR
“gaming disorder” OR “disordered gaming” OR “disor-
dered video gaming” OR “IGD” OR “gaming addiction”
OR “problematic gaming” or “problematic video gaming”
OR “compulsive overeating” OR “compulsive eating” OR
“eating addiction” OR hyperphagia OR “binge eating”
OR “uncontrolled eating” OR “food addiction” OR “inter-
net use disorder” OR “IUD” OR “internet addiction” OR
“love addiction” OR “emotional dependence” OR smart-
phone OR “social media” OR “problem spending” OR
“compulsive buying” OR “compulsive shop*” OR worka-
hol* OR “work addiction” OR “compulsive sexual behav-
ior*” OR “compulsive sexual disorder” OR “CSD” OR
“compulsive sexual behavio*” OR “pornography use” OR
“exercise addiction” OR “compulsive exercis*”))
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
730 Current Addiction Reports (2023) 10:718–736
1 3
• N = 28
ProQuest (via ProQuest; ‑Present)
• Fields: Title + Abstract
• Limits: none
• Algorithm as per data base: title((urgency OR UPPS*)
AND (craving OR "attentional capture" OR "cue reactiv-
ity" OR urge OR urges) AND ("gambling problems" OR
"gambling disorder" OR "pathological gambling" OR
"problematic gambling" OR "disordered gambling" OR
"problem gambling" OR "gambling addiction" OR "gam-
ing problems" OR "gaming disorder" OR "disordered
gaming" OR "disordered video gaming" OR "IGD" OR
"gaming addiction" OR "problematic gaming" OR "prob-
lematic video gaming" OR "compulsive overeating" OR
"compulsive eating" OR "eating addiction" OR hyper-
phagia OR "binge eating" OR "uncontrolled eating" OR
"food addiction" OR "internet use disorder" OR "IUD"
OR "internet addiction" OR "love addiction" OR "emo-
tional dependence" OR smartphone OR "social media" OR
"problem spending" OR "compulsive buying" OR "com-
pulsive shop*" OR workahol* OR "work addiction" OR
"compulsive sexual behavior*" OR "compulsive sexual
disorder" OR "CSD" OR "compulsive sexual behavio*"
OR "pornography use" OR "exercise addiction" OR "com-
pulsive exercis*")) OR abstract((urgency OR UPPS*) AND
(craving OR "attentional capture" OR "cue reactivity" OR
urge OR urges) AND ("gambling problems" OR "gambling
disorder" OR "pathological gambling" OR "problematic
gambling" OR "disordered gambling" OR "problem gam-
bling" OR "gambling addiction" OR "gaming problems"
OR "gaming disorder" OR "disordered gaming" OR "dis-
ordered video gaming" OR "IGD" OR "gaming addiction"
OR "problematic gaming" OR "problematic video gaming"
OR "compulsive overeating" OR "compulsive eating" OR
"eating addiction" OR hyperphagia OR "binge eating" OR
"uncontrolled eating" OR "food addiction" OR "internet
use disorder" OR "IUD" OR "internet addiction" OR "love
addiction" OR "emotional dependence" OR smartphone
OR "social media" OR "problem spending" OR "compul-
sive buying" OR "compulsive shop*" OR workahol* OR
"work addiction" OR "compulsive sexual behavior*" OR
"compulsive sexual disorder" OR "CSD" OR "compulsive
sexual behavio*" OR "pornography use" OR "exercise
addiction" OR "compulsive exercis*"))
• N = 24
Section2: Correlation Coefficients asReported
intheOriginal Studies
In the main text, and in order to allow for comparability, all
correlation coefficients between constructs of interest were
recalculated as Pearson’s r. For the sake of transparency, the
correlation coefficients reported in the original studies (i.e.,
before transforming them into Pearson’s r coefficients) are
reported in Table3of this Appendix.
Section3: Quality Assessment
The National Heart, Lung and Blood Institute (NHLBI) study
quality assessment tool [51] was used in order to assess the
risk of bias and internal validity of the articles included in
the systematic review. Taking into consideration the differ-
ent nature of the selected studies, two different versions of
this tool (i.e. two different templates) were used: (1) Quality
Assessment Tool for Observational Cohort and Cross-Sec-
tional Studies, and (2) Quality Assessment Tool for Before-
After (Pre-Post) Studies With No Control Group. Each ver-
sion of the NHLBI study quality assessment tool comprises
between 12 and 14 questions, carefully crafted to aid review-
ers in evaluating fundamental aspects of the studies and test-
ing potential flaws concerning study methods and outcomes.
The authors in charge of reviewing the quality of the
articles may select "yes," "no" or “other” (i.e. “cannot
determine”, “not applicable”, “nor reported") options in
response to each question of the corresponding template.
Subsequently, the reviewers must assign a final rating of
“good”, “fair” or “poor” based on a critical overall assess-
ment of the characteristics that they consider more relevant.
The tool offers a guide to help in this process.
In this work, the first and last authors independently
assessed the quality of each article included in the system-
atic review. Importantly, as none of the selected articles were
cohort studies, some of the questions (Q9, Q11 and Q14) of the
second template (Quality Assessment Tool for Observational
Cohort and Cross-Sectional Studies) were adapted to be used
with cross-sectional studies. Following this, inter-judges agree-
ment was calculated for each study separately (for responses
across items), and for the final assessment (across studies)
using Cohen's Kappa for categorical variables. Analyses were
run using the rater agreement module provided by the JASP
statistical analysis package 0.17.1 [44]. Total agreement was
reached by discussion at the end of the process.
Table4in this Appendix shows the responses given by
the reviewers across items and studies, after resolving disa-
greements by discussion and consensus. Kappa values in the
rightmost column of the table refer to responses given by the
two reviewers before discussion.
Of the ten studies, three were assessed as presenting good
quality [33, 37, 39], and seven as presenting fair quality [34•, 36,
38, 40–43]. For the cross-sectional studies [33, 34•, 36, 38–40],
the main weaknesses of those ranked as having fair quality were
(a) not carrying out a priori sample size estimations or power
analyses, and (b) the exclusive use of self-report input and output
variables. For pre-post studies [37, 41, 43], in all the cases, the
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731Current Addiction Reports (2023) 10:718–736
1 3
two authors considered that the participants in the study were
not representative of those who would be eligible for a possible
intervention in the general or clinical population.
Section4: Sensitivity/Power Analyses
These analyses were conducted using Gpower version 3.1.9.7
[52], and results are shown in Table5 of this Appendix.
For correlations, we ran a two-tail sensitivity analysis with
an 5% alpha level and 80% power, and the sample size of each
study. This yielded the minimal detectable correlation coef-
ficient for each study, which can be compared with observed
correlations, as reported in Table2 of the main manuscript.
Similarly, for regressions, we computed the minimal
detectable model’s R2. Apart from setting alpha and desired
power levels at 5% and 80%, the number of predictors in
each study (including control covariates) was also taken into
consideration. These R2 values can be compared with those
reported in the Results section of the main manuscript and
in Sect.6 of this Appendix (Table6).
Section5: Meta‑analyses
To provide an overview of the relative strengths of the asso-
ciations between the variables of interest, we proceeded
to run 6 meta-analyses with all datasets for which we had
correlational data (9 datasets), and other 6 restricted to gam-
bling studies (7 datasets). First, the sample size and r cor-
relation coefficients were extracted for each dataset and pair
of variables, recomputing correlations that were originally
reported as Spearman’s Rho or Kendall’s Tau (see Table2 in
the main manuscript and Table3 in this Appendix).
For each meta-analyisis, a random effects model was fit-
ted to the data using the MAJOR statistical module for Jam-
ovi (version 2.2.5; [53]). The following settings were used:
raw correlation was selected as outcome measure; hetero-
geneity (Tau2) was estimated using the restricted maximum
likelihood estimator (RMLE); the Q statistic, which assesses
the extent of variation caused by sampling error, and the I2
test, which evaluates the proportion of observed variance
reflecting an actual difference in effect sizes, were computed;
and the potential publication bias was tested using the Egg-
er’s test. Pooled effects are reported in the bottom rows of
Table2 in the main manuscript.
Section6: Full report ofregression analyses
Finally, here we disclose the results of all regression analy-
ses, regardless significance of the models or the individual
predictors in such models. Results can be found in Table6
and Table7.
Table 3 Results of the correlations coefficients as originally reported between the variables of interest
Note: For the fourth study [40], we provide information when craving was measured with the Weiss Craving Scale and with a visual analogue
scale (VAS), respectively. Similarly, for the fifth study [41], we provide information when craving was measured with the gambling Craving
Experience Questionnaire for Frequency (g-CEQ-F) and with the Gambling Craving Scale (GACS), again, respectively. NU: negative urgency;
PU positive urgency. Results written in bold are statistically significant. * p < .05, ** p < .01, *** p < .001. Note: For one of the studies [40], the
authors recommended the use of Pearson's correlation coefficient for the correlation between positive and negative urgency, and Spearman's cor-
relation coefficient for the correlation with craving (since the latter was not normally distributed)
Study Samples Correlation’s coef-
ficient used
Severity—NU Severity—PU Severity—Craving NU-PU Craving—NU Craving—PU
Schulte etal. (2021)
[36]
S1 Pearson'sr.502*** .165 .429* .636*** .333* .165
Cornil etal. (2021)
[37]
S1 Kendall's τ.051 .197 .561*** .514*** .104 .201
S2 Kendall's τ.103 .23 .288* .344** .151 .128
Quintero etal. (2020)
[39]
S1 Spearman'sρ.183 .244* .640*** .387*** .280* .420***
Albein-Urios etal.
(2014) [40]
S1 Pearson'sr /
Spearman'sρ- - - .814*** .471/.534* .278/.379
Cornil etal. (2019)
[41]
S1 Spearman'sρ .162** .243*** .553***/.380*** .552*** .097/.288*** .051/.111
Kim etal. (2021) [42] S1 Pearson'sr.395*** .471*** .468*** .697*** .247*** .312***
Canale etal. (2019)
[43]
S1 Pearson'sr.259*** .228** .556*** .595*** .307*** .270***
Muela etal. (2023)
[33]
S1 Pearson'sr.387*** .415*** .501*** .507*** .224* .512***
Rivero etal. (2023)
[34•]
S1 Pearson'sr.198*** .265*** .579*** .543*** .111* .252***
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732 Current Addiction Reports (2023) 10:718–736
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Table 4 Results of the study quality assessment through the NHLBI tool after full agreement
NA: not applicable; NR: not reported. Note: The complete questions can be found on the NHLBI website via this link: https:// www. nhlbi. nih. gov/ health- topics/ study- quali ty- asses sment- tools.
Boxes Q1 through Q14 show the item ratings after full agreement between the two authors rating each study. The last column on the right shows the Cohen's Weighted Kappa value resulting
from the inter-judges agreement after two of the authors independently rated the items in each of the studies (this is, before full agreement).This table was adapted from Westlake etal. [50]
Studies Type of design NHLBI assessment questions Total yes Total no Other Rate Cohen’s Kappa
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14
Schulte etal. (2021) [36] Cross-sectional Yes Yes NA Yes No NA NA NA Yes NA Yes NA NA No 5 2 NA Fair 0.960
Cornil etal. (2021) [37] Pre-post Yes Yes No Yes Yes Yes Yes NR NA Ye s Yes NA - - 8 1 NA, NR Good 1.000
Shirk etal. (2021) [38] Cross-sectional Yes Yes NA No No NA NA NA Yes NA Ye s NA NA No 4 3 NA Fair 1.000
Quintero etal. (2020) [39] Cross-sectional Yes Yes NA No Yes NA NA NA Yes NA Yes NA NA Yes 6 1 NA Good 0.963
Albein-Urios etal. (2014) [40] Cross-sectional Yes No NA Yes Yes NA NA NA Yes NA Yes NA NA Yes 6 1 NA Fair 0.960
Cornil etal. (2019) [41] Pre-post Yes No No Yes No Yes Ye s NR NA Yes No NA - - 5 4 NA, NR Fair 0.813
Kim etal. (2021) [42] Experimental Yes No NA No Yes NA NA NA Yes No Yes NR Ye s Yes 6 3 NA, NR Fair 1.000
Canale etal. (2019) [43] Pre-post Yes No No Yes No Yes Yes NR NA Yes No NA - - 5 4 NA, NR Fair 0.714
Muela etal. (2023) [33] Cross-sectional Ye s Yes NA Yes Yes NA NA NA Yes NA Yes NA NA Yes 7 0 NA Good 1.000
Rivero etal. (2023) [34•] Cross-sectional Yes Ye s NA Yes Yes NA NA NA No NA Yes NA NA Ye s 6 1 NA Fair 1.000
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733Current Addiction Reports (2023) 10:718–736
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Table 5 Minimum detectable
effect sizes for correlation and
regression analyses
Study NMinimum detectable effect
size for correlations (ρ)
Minimum detectable effect size
for linear regressions (model’s R2)
Schulte etal. (2021) [36] 46 0.389 -
Cornil etal. (2021) [37] 38
38
0.423 0.18
Shirk etal. (2021) [38] 172 0.21 -
Quintero etal. (2020) [39] 70 0.322 0.104
Albein-Urios etal. (2014) [40] 26 0.497 -
Cornil etal. (2019) [41] 274 0.167 0.028
Kim etal. (2021) [42] 213 0.189 0.036
Canale etal. (2019) [43] 165 0.214 -
Muela etal. (2023) [33] 81 0.301 0.09
Rivero etal. (2023) [34•] 454 0.116 0.017
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734 Current Addiction Reports (2023) 10:718–736
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Table 6 Results of regression analyses of craving over positive and negative urgency
NU Negative Urgency; PU Positive Urgency; β standardized beta coefficient. Results in bold are statistically significant. *p < .05, **p < .01, ***p < .001
Studies Cornil etal. 2021 (1) Cornil etal. 2021 (2) Quintero etal. 2020 Cornil etal. 2019 Kim etal. 2021 Muela etal. 2023 Rivero etal. 2023
Predic-
tors β t p β t p β t p β t p β t p β t p β t p
NU 0.172 0.841 0.406 0.221 1.097 0.281 0.106 0.906 0.368 0.143 1.956 0.052 0.058 0.696 0.487 − 0.043 − 0.382 0.703 0.026 0.55 0.583
PU 0.228 1.158 0.255 0.071 0.37 0.714 0.379 3.214 0.002 0.064 0.886 0.376 0.271 3.250 0.001 0.53 4.626 < .001 0.145 2.993 0.003
Age -0.19 1.177 0.248 0.013 0.076 0.94 − 0.191 − 1.728 0.089 0.134 2.198 0.029 --- − 0.010 − 0.102 0.919 − 0.058 − 1.440 0.151
Sex - 1.475 0.15 - − 0.163 0.871 - − 2.350 0.022 - − 2.799 0.005 - - - - 1.091 0.279 - − 6.365 < .001
Source - - - - - - - - - - - - - - - - - - - 6.354 < .001
Full
model R2 = 0.181 R2= 0.078 R2 = 0.282*** R2 = 0.058*** R2 = 0.099*** R2 = 0.275*** R2 = 0.297***
Table 7 Results of regression analysis of severity over positive and negative urgency, and craving
NU Negative Urgency; PU Positive Urgency; β standardized beta coefficient. Results in bold are statistically significant. *p < .05, **p < .01, ***p < .001
Studies Cornil etal. 2021 (1) Cornil etal. 2021 (2) Quintero etal. 2020 Cornil etal. 2019 Kim etal. 2021 Muela etal. 2023 Rivero etal. 2023
Predic-
tors β t p β t p β t p β t p β t p β t p β t p
UN − 0.095 − 0.643 0.525 − 0.070 − 0.385 0.703 − 0.001 − 0.013 0.99 − 0.009 − 0.164 0.87 0.109 1.519 0.13 0.252 2.377 0.02 0.109 2.409 0.016
UP 0.127 0.885 0.383 0.195 1.136 0.264 − 0.009 − 0.075 0.94 0.13 2.370 0.018 0.285 3.896 < .001 0.077 0.635 0.527 0.062 1.338 0.182
Craving 0.712 5.708 < .001 0.455 2.925 0.006 0.637 5.465 < .001 0.652 14.127 < .001 0.352 6.534 < .001 0.435 4074 < .001 0.499 11.093 < .001
Age 0.06 − 0.509 0.614 0.127 0.825 0.415 0.052 0.495 0.622 − 0.133 − 2.853 0.005 - - - 0.003 0.032 0.974 0.003 0.081 0.936
Sex - 0.908 0.371 − 0.120 0.905 - 0.684 0.496 - 0.581 0.562 - - - - − 2.365 0.021 - − 1.536 0.125
Source - - - - - - - - - - - - - - - - - - - 1.030 0.304
Full
model
R2 = 0.592*** R2 = 0.285* R2 = 0.376*** R2 = 0.463*** R2 = 0.342*** R2 = 0.381*** R2 = 0.365***
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735Current Addiction Reports (2023) 10:718–736
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Authors’ Contribution Except for the last author (IM), who is the
corresponding author and general coordinator of this work, the rest
of authors are ordered alphabetically and contributed equally to this
work. The draft of the manuscript was revised and approved by all the
authors.
Funding Funding for open access publishing: Universidad de Gra-
nada/CBUA. Work by JLG, JFN, JCP, FJR and IM is supported by
a R&D project (Proyecto I + D + i), funded by the Spanish Research
Agency (Agencia Española de Investigación), Spanish Ministry
of Science and Innovation (Ministerio de Ciencia e Innovación)
(MCIN/AEI/https:// doi. org/ 10. 13039/ 50110 00110 33), with reference
PID2020-116535GB-I00. IM’s work is supported by an individual
research grant (PRE2018-085150, Ministerio de Ciencia, Innovación
y Universidades). JLG's work is supported by and individual research
grant (PRE2021-100665, Ministerio de Ciencia e Innovación). FJR’s
work is supported by an individual research grant (FPU21/00462, Min-
isterio de Ciencia e Innovación).
Declarations
Human and Animal Rights and Informed Consent This article does not
contain any studies with human or animal subjects. Therefore, there
was no informed consent.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
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otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
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need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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