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Purpose of Review The playing of videogames has become an everyday occurrence among many adolescents and emerging adults. However, gaming can be problematic and potentially addictive and problematic gamers can experience co-occurring behavioral or substance use-related problems. The aims of the present review were to (i) determine the co-occurrence of potentially addictive behaviors with problematic and disordered gaming, and (ii) elucidate the potential risk factors in the development and maintenance of co-occurrence within disordered gaming. Recent Findings The main findings demonstrated that there are few empirical studies (N = 20) examining (i) co-occurrence of gaming disorder with other addictive behaviors; (ii) longitudinal risk of disordered gaming with co-occurring addictive behaviors; and (iii) mechanisms of co-occurrence in disordered gaming with co-occurring potentially addictive behaviors. Results suggest that disordered gaming can co-occur with a variety of other addictive behaviors (e.g., alcohol use disorder or addictive use of social media), and that research into the co-occurrence of addictive behaviors and substance use is increasing. Summary Based on this systematic review, findings suggest that gamers engage in a number of potentially addictive behaviors and substance use which can have detrimental effects on health and wellbeing. While a majority of the reviewed studies consider prevalence rates from a range of geographical locations, there are fewer papers which investigate individual and environmental risk factors.
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A Systematic Review of the Co-occurrence of Gaming Disorder
and Other Potentially Addictive Behaviors
Tyrone L. Burleigh
&Mark D. Griffiths
&Alex Sumich
&Vasileios Stavropoulos
&Daria J. Kuss
#The Author(s) 2019
Purpose of Review The playing of videogames has become an everyday occurrence among many adolescents and emerging
adults. However, gaming can be problematic and potentially addictive and problematic gamers can experience co-occurring
behavioral or substance use-related problems. The aims of the present review were to (i) determine the co-occurrence of
potentially addictive behaviors with problematic and disordered gaming, and (ii) elucidate the potential risk factors in the
development and maintenance of co-occurrence within disordered gaming.
Recent Findings The main findings demonstrated that there are few empirical studies (N= 20) examining (i) co-occurrence of
gaming disorder with other addictive behaviors; (ii) longitudinal risk of disordered gaming with co-occurring addictive behav-
iors; and (iii) mechanisms of co-occurrence in disordered gaming with co-occurring potentially addictive behaviors. Results
suggest that disordered gaming can co-occur with a variety of other addictive behaviors (e.g., alcohol use disorder or addictive
use of social media), and that research into the co-occurrence of addictive behaviors and substance use is increasing.
Summary Based on this systematic review, findings suggest that gamers engage in a number of potentially addictive behaviors
and substance use which can have detrimental effects on health and wellbeing. While a majority of the reviewed studies consider
prevalence rates from a range of geographical locations, there are fewer papers which investigate individual and environmental
risk factors.
Keywords Gaming disorder .Internet gaming disorder .Comorbidity .Video game addiction .Problematic gaming .Substance
use .Systematic review .Co-occurrence
Research has begun to investigate the negative consequences
of problematic video gaming in an effort to improve screen-
ing, assessment, definition, and treatment of the disorder [1].
Such work has contributed to the American Psychiatric
Association (APA) [2] including Internet Gaming Disorder
(IGD) as a form of behavioral addiction (warranting further
investigation) in the latest (fifth) edition of the Diagnostic and
Statistical Manual of Mental Disorders (DSM-5) in
Section 3(Emerging measures and models). The World
Health Organization [3] has also recognized gaming disor-
der(GD) as an official disorder with addiction like properties
in the eleventh revision of the International Classification of
Diseases (ICD-11).
Prior to the inclusion of GD in the DSM-5 and ICD-11,
several other terms were used to describe problematic video
gaming including videogame addiction, pathological video
gaming, gaming use disorder, and gaming use dependency
[47]. Further confusing the issue, online problematic gaming
has also been included within the umbrella terms of internet
addiction, problematic internet use, and pathological internet
use [810]. However, the internet addiction umbrella term
encompasses several other problematic online activities, such
as online gambling, online sex, social media use, and online
shopping [11]. In order to maintain consistency throughout the
present review, the term disordered gamingwill be used to
This article is part of the Topical Collection on Technology Addiction
*Tyrone L. Burleigh
International Gaming Research Unit, Psychology Department,
Nottingham Trent University, Nottingham NG1 4FQ, UK
Department of Psychology, Nottingham Trent University,
Nottingham, UK
Cairnmillar Institute, Hawthorn East, Melbourne, Australia
Current Addiction Reports (2019) 6:383401
Published online: 7
September 2019
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describe a range of similar and/or overlapping addictive, com-
pulsive, and/or problematic gaming behaviors. When refer-
ring to clinically defined cases, the term GDwill be used,
in line with DSM-5 and ICD-11. Furthermore, in relation to
other potentially addictive behaviors, the term problematic
will be used to describe subclinical conditions that do not fully
meet all the criteria in the DSM-5 or ICD-11 (e.g., problematic
gambling), while the term disorderedwill be used to de-
scribe clinical conditions that meet the requisite criteria in
the DSM-5 and ICD-11.
There has been a growing body of research suggesting that
disordered gaming is associated with a number of other mental
health disorders, such as depression [12], anxiety [11], prob-
lematic substance use [13], and personality disorders [14].
However, an understudied area in this field is the co-
occurrence of disordered gaming with other potentially addic-
tive substances and behaviors. Within the present review, co-
occurrence refers to when two or more potentially addictive
behaviors (behavioral and/or substance) are engaged in con-
currently. For example, in a systematic review on the preva-
lence of eleven different types of addictions, it was estimated
that approximately 10% of adults with internet addiction may
experience another concurrent problematic behavior or sub-
stance use (e.g., alcohol use or dependence or gambling ad-
diction [15]).
Evidence supports the co-occurrence of addiction for both
substances and behaviors (i.e., the presence of a behavioral
addiction increases the propensity for addiction to develop for
other behaviors). Indeed, this may create a cycle of reciprocity,
wherein mutual exacerbation occurs between two or more
problematic behaviors [1618]. Moreover, those who do ex-
perience co-occurring problematic and addictive behaviors are
at higher risk of poor mental health (e.g., depression) and
physical health [1820].
In addition, co-occurring problematic behaviors interact to
exacerbate clinical symptoms, which can complicate accurate
assessment and treatment of other psychiatric disorders [21].
Likewise, disordered gaming may mask problematic sub-
stance use which could hinder diagnostic assessment.
Alternatively, disordered gaming may exacerbate problematic
substance use, causing symptoms of both to alternate which
can impact treatment efficacy [22]. This highlights that the
assessment and treatment of GD should have a broader focus
by not only considering the presenting primary problematic
behavior or substance use and symptoms, but also any poten-
tial co-occurring addictive behaviors or substance use, which
may enforce a cycle of reciprocity.
Consequently, clinicians need to be aware of how poten-
tially addictive behaviors impact or enforce various aspects of
a primary problematic behavior (e.g., disordered gaming), and
be aware of how co-occurring addictions may impact the on-
set, course, and outcomes of interventions. Previous literature
has demonstrated that the prevalence of co-occurring
addictions can be high [15], suggesting that studies which
consider addiction as only comprising one specific behavior
may be limited in ecological invalidity because individuals
have more complex and varied histories of disordered behav-
iors and co-occurrence [17].
Although there has been one previous comprehensive re-
view investigating the co-occurrence of eleven behavioral and
substance addictions, this mainly evaluated US studies, did
not examine disordered gaming, and was written almost a
decade ago [15]. Furthermore, this review was limited to clin-
ical measures in relation to co-occurrence, and did not consid-
er any proxy measures (e.g., time spent engaging in the activ-
ity as an indication of problematic or disordered behavior).
Consequently, given the large increase in research examining
disordered gaming in the past decade, there is a need for a
contemporary systematic review examining the co-
occurrence of GD with other potentially addictive behaviors.
While several studies have considered the impact of co-
occurrence of neurodevelopmental and mood disorders on
the onset, course, and maintenance of GD [23], there is limited
integrative research examining addiction comorbidities.
Furthermore, failure to integrate treatments which consider
co-occurring addictions may lead to a ping pong effect,
wherein an individual may bounce back and forth between
problematic or disordered behaviors and/or substance use
and treatment programs [24].
There are several studies within the behavioral and sub-
stance addiction literature that support the efficacy and bene-
fits of treating co-occurring addictions concurrently [24,25].
Therefore, in order to integrate contemporary research, it is
important to conduct a systematic review highlighting extant
findings concerning the co-occurrence of addictive behaviors,
which specifically considers problematic and disordered gam-
ing and not the often-used broader construct of internet ad-
diction.This may aid in the development of effective models
that identify and aid clinicians to treat disordered gaming
alongside other co-occurring addictive behaviors.
The primary goal of the present study was to review em-
pirical research over the past decade, providing up-to-date
information that considers the impact of addiction to other
behaviors on GD, and to provide recommendations for future
research. More specifically, the aims of the present review
were to (i) determine the co-occurrence of potentially addic-
tive behaviors with problematic and disordered gaming, and
to (ii) elucidate the potential risk factors in the development
and maintenance of co-occurrence within GD.
A systematic review was employed to examine the co-
occurrence of potentially addictive behaviors with disordered
gaming. While disordered gaming has been conflated with
Curr Addict Rep (2019) 6:383401
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internet addiction in the past, it is important to note that only
papers that considered assessed gaming and/or gaming disor-
der (i.e., problematic gaming) were considered. A systematic
review contains key elements, such as an overview of the
literature, summary of the findings, dissemination of out-
comes, and identification of gaps in the literature [26]. The
present review utilized a five-stage model of conducting a
rigorous systematic review, which included (i) identifying
the research question, (ii) identifying relevant studies, (iii)
study selection, (iv) dissemination of outcomes, and (v) sum-
marizing and reporting the results [26].
The inclusion criteria for the present review were as fol-
lows: (i) empirical studies containing primary data, (ii) studies
that assessed the co-occurrence of and potential cross-addic-
tionor addiction hoppingwithin the problematic or disor-
dered gaming literature; (iii) studies published in peer-
reviewed journals, (iv) written in English, and (v) published
within the past decade. ProQuest, Scopus,andWeb o f S ci enc e
were searched, including the following databases:
PsychARTICLES, PsychINFO, Scopus, Web of Science Core
Collection, and MEDLINE. The search included a number of
terms related to disordered gaming that have been used over
the past decade. In addition to this, several terms were devel-
oped to explore cross-addiction and co-occurrence in the be-
havioral addiction literature, which led to the following search
strategy: (patholog* OR problem* OR addict* OR compul-
sive OR dependen* OR disorder* OR excess*) AND (video
gam* OR computergam* OR internet gam* OR online gam*)
AND (cross addictionOR addiction hoppingOR expres-
sion hoppingOR substitution hypothesisOR switching
hypothesisOR co-occur*OR comorbid* OR dual diag-
nosis). Each studys title, abstract, and paper content were
screened for eligibility. The full texts of potentially relevant
studies were retrieved and screened for eligibility.
A total of 4160 papers were identified in the initial search.
The ProQuest database contained 2507 papers
(PsychARTICLES n = 1749; PsychINFO n = 799); Scopus
contained 1271 papers; and Web of Science contained 341
papers. Duplicate studies were removed, leaving a total of
3915 papers. These papers had their journal of publication,
titles, and abstracts screened, resulting in the exclusion of
3845 papers that were not relevant to the present review, leav-
ing a total of 70 papers, which were eligible for further review.
Of these, 54 were excluded as they were not written in English
(n= 3), did not asses disordered gaming (n=1
5), did not as-
sess cross-addiction or co-occurrence (n=16),didnotconsid-
er disordered gaming in conjunction with another behavioral
or substance addiction/disorder (n=17), or were review pa-
pers (n= 3). The remaining 16 papers were considered eligible
for further analysis as they met all the inclusion criteria.
Furthermore, four additional relevant papers were included
from the reference lists of the identified papers, bringing the
total to 20 papers. The present paper followed the Preferred
Reporting Items for Systematic Reviews and Meta-Analyses
guidelines (PRISMA statement; Moher, Liberati, Tetzlaff,
Altman, & the PRISMA Group, 2009), which includes the
use of a PRISMA flow diagram (see Fig. 1).
The 20 papers that met the inclusion criteria were divided into
specific categories. A total of 16 papers were considered as
papers that had assessed co-occurrence prevalence of prob-
lematic or disordered gaming with other addictive behaviors
and had explored their commonalities with various related
and/or unrelated risk and/or protective factors. Of these 16
papers, ten were categorized as prevalence of co-occurrence
in GD and other potentially addictive behaviors.The papers
within this category each featured validated psychometric
measures which provided an indication of severity risk for
disordered gaming and other potentially addictive behaviors.
The other six papers that assessed prevalence were catego-
rized as proxy indicators of GD prevalence and other poten-
tially addictive behaviors.Unlike the papers in the first cate-
gory, these papers did not use psychometric measures as a tool
to assess severity for both problematic or disordered gaming
and the co-occurring problematic or disordered behavior and/
or substance use. Instead, these studies assessed the frequency
of the behavior (e.g., sexual activity; how many times have
you engaged in sexual activity in the last week?) or the con-
sumption of substance (e.g., number of alcoholic drinks;
How many alcoholic drinkshave you had inthe past week?)
as an indicator of use and assessment. The remaining four
papers were categorized as assessing the etiology of disor-
dered gaming and other potentially addictive behaviors.
These papers investigated specific relationships between GD
and the mechanisms which may contribute to the understand-
ing of the development, maintenance, or exacerbation of GDs
with other potentially addictive behaviors (e.g., coping strate-
gies and personality factors).
Prevalence of Gaming Disorder Co-occurrence
with Other Addictive Behaviors
Of the ten studies examining prevalence [10,2735], six ex-
amined adult populations (e.g., general populations), three
examined adolescent populations (e.g., middle school stu-
dents; see Table 1), and one examined both adolescents and
adults. Six [2730,32,35] of these studies focused on the co-
occurrence of GD with problematic substance use (i.e., nico-
tine and cannabis use) and alcohol use. While there has been
some exploration of other potentially addictive behaviors,
such as buying, phone use, eating, gambling, exercise, sexual
behavior, and social media use, these were usually a part of a
larger investigation of substance use or disordered substance
Curr Addict Rep (2019) 6:383401 385
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use, which did not consider disordered gaming as the primary
focus. Consequently, their findings lack nuanced consider-
ation of disordered gaming and the wider implications within
the gaming studies field. Four studies [10,31,34,80]inves-
tigated the co-occurrence of GD with other technological
addictions(e.g., social media addiction and internet
Prevalence was investigated in eight geographical loca-
tions, including Norway (n=2) [33,35], Hungary (n=1)
[10], Netherlands (n=1) [28], the USA (n=2) [27,32],
Italy (n=1)[34], Germany (n=1) [29], South Korea (n=1)
[30], and Portugal (n=1)[31]. Sample sizes ranged from 128
to 21,053 participants. However, the type of surveyed popu-
lations was relatively narrow, with the majority of the studies
considering school students (n= 5), and to a lesser degree the
general population (n= 3) (see Table 1).
Six studies investigated the prevalence of problematic or
disordered gaming within adult populations. Lee et al. [27]
investigated the relationship between attention-deficit hyper-
activity disorder (ADHD), cigarette smoking, problematic
gaming, and the frequency of playing videogames in an online
American adult sample (N= 2801). Their results suggested
that ADHD, cigarette smoking, and frequency of playing
videogames had a significant impact on problematic gaming.
This finding was consistent with previous studies, such as
Ream et al.sstudy[32], who found a significant correlation
with nicotine, alcohol, caffeine, cannabis use, and problematic
videogame use in a large American sample of adult gamers
(N= 2885). Furthermore, among gamers, 64% used caffeine
and 41% of those caffeine users had consumed caffeine while
gaming; 26% of their sample used nicotine and 61% of
smokers had smoked cigarettes while gaming; 34% of partic-
ipants consumed alcohol, and 38% of those had drank alcohol
while gaming; and 5.6% of their sample smoked cannabis and
80% of those had smoked cannabis while gaming.
Similarly, Na et al. [30] surveyed South Korean adults (N=
1819) online, and found that 21% experienced both problem-
atic alcohol use (i.e., scoring over 20 on the Korean version of
Alcohol Use Disorders Identification test [AUDIT-K]) and
problematic gaming. This group also had higher cigarette
smoking rates (44.8%) than participants in the problematic
alcohol group (31.6%) or problematic gaming group (26%),
which is consistent with the American sample above.
Furthermore, their results indicated that those participants
who reported both drinking alcohol and gaming demonstrated
higher scores on psychometric tests (which indicated poorer
mental health outcomes) than any other group (i.e., control,
alcohol group, and gaming group), lending support to the
notion that co-occurring substance use and activities and po-
tentially addictive behaviors are associated with maladaptive
clinical outcomes [30].
Müller et al. [29] investigated exercise dependence (EXD)
in a German sample of participants attending a fitness center
(N= 128). Their results found that out of the ten males (7.8%)
who were at risk of developing EXD, two experienced prob-
lematic gaming. One participant was at risk of an eating
Fig. 1 Flow diagram of paper
selection process for the
systematic review
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Table 1 Prevalence rates of co-occurrence of problematic and disordered gaming using psychometric measures
Paper Aims Sample Behavior/
Instruments Results/outcomes
et al., 2016
To investigate the associations between
disordered use of technologies and
comorbid psychiatric disorders
Norwegian Population;
n= 23,533 (M= 35.8;
SD = 13.3) 17 to
88 years of age.
Site (SNS)
Bergen Facebook Addiction Scale [37]
(BFAS; 6 item); Game Addiction Scale for
Adolescents [38](GASA; 7 item);The
Adult ADHD Self-Report Scale [39]
(ASRS-Version 1.1; 18 items); The
Inventory-Revised [40] (OCI-R; 18 item);
Hospital Anxiety and Depression Scale
[41] (HADS; 14 item)
- There was a weak interrelationship between
SNS addiction and disordered gaming
- Results suggest that internet use disorder as
a unified concept is not warranted as there
are enough differences and motivations
between SNS addiction and disordered
gaming to warrant separate classifications
Erevik et al.,
2019 [42]
To investigate the levels of problems
associated with gaming/gaming
investment and problematic alcohol use.
Norwegian university
student population;
n= 5217 (M= 25.8)
- Problematic
- Problematic
Alcohol use
Gaming Addiction Scale for Adolescents
[38](GASA; 7 item); Alcohol Use
Disorder Identification Test [43](AUDIT;
10 item); Mini-International Personality
Item Pool [44] (Mini-IPIP; 20 item);
Hopskins Symptoms Checklist [45]
(HSCL-25; 25 item)
- Low level gaming and problematic alcohol
use co-occur
- High levels of gaming act as a protective
factor for problematic alcohol use
Kiraly et al.,
2014 [10]
To examine the interrelation and the overlap
between problematic internet use (PIU)
and problematic online gaming (POG) in
terms of sex, school achievement, time
spent using the Internet and/or online
gaming, psychological well-being, and
preferred online activities.
Hungarian nationally
representative sample
of adolescent gamers;
N= 2073 (M= 16.4,
SD = 0.87)
- Problematic
Internet Use
- Problematic
Online Gaming
Problematic Online Gaming Questionnaire
Short-Form [46](POGQ-SF; 12 item);
adapted Internet Use Questionnaire [47]
(PIUQ-6; 6 items); short-form Center of
Epidemiological Studies Depression
Scale [48] (CES-D; 6 item); Rosenbergs
Self-Esteem Scale [49] (RSES; 10 items)
problematic gaming; 8.8% experienced
problematic internet use; and 6.7%
experienced both problematic gaming and
problematic internet use
- Internet use was a common activity among
adolescents; online gaming was engaged
in by a much smaller group
- POG and PIU appear to be two
conceptually different behaviors, thus
providing evidence that Internet addiction
and IGD are separate nosological entities
Lee et al., 2018
To explore the relationship of various
correlates of problematic and disordered
Adult Sample, n= 2801;
1857 years
(M= 22.43,
SD = 4.70)
- Internet
Playing (PVP)
Internet Addiction Scale [50](20 items);
Problem Videogame Playing Scale [51](8
items); ConnersAdult ADHD Rating
Scale-Self-Report [52](26items);
Smoking Behavior and Video Game Use
(2 items)
- ADHD symptomatology, smoking
behavior, and the amount of video game
use have a significant impact on PVP
- For every additional cigarette smoked, an
individuals problematic gaming score
increased by 0.022 (p< .05).
- Smoking and PVP had a significant
positive correlation
Mérelle et al.,
2017 [28]
To identify which health related problems
are most important for adolescents that are
at risk for problematic gaming or social
media use.
Dutch Adolescent
Sample; n= 21,053
(M= 14.4, SD =1.3).
- Smoking
- Alcohol
- Cannabis
- Problematic
Problematic Video-gaming Use [53](6
items); Problematic Social Media Use
[54](6 items); General Health [55](1
item); Strengths and Difficulties
Questionnaire [56] (25 items); Life Events
(2 items); Lifestyle Questionnaire [5759]
(13 items); Substance Use (4 items)
- Smoking is strongly associated with
Problematic Video Gaming
- A substantial number of adolescents
reported some (addictive) problems with
gaming (5.7%) or social media use (9.1%)
- There is a weak association with substance
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Tab l e 1 (continued)
Paper Aims Sample Behavior/
Instruments Results/outcomes
Monacis et al.,
2017 [34]
To investigate the extent to which identity
styles and attachment orientations account
for three types of disordered online
Italian Students; n= 712
(M= 21.63;
SD = 3.90).
Split into two groups:
Adolescent (n= 267;
M= 18.22,
SD = 1.04) and
Adults (n= 445;
M= 23.67,
SD = 3.55)
- Internet
-Internet Gaming
Italian Internet Addiction Test [50,60](IAT;
20 items); Internet Gaming Disorder
Scale-Short Form [61,62](IGDS9-SF; 9
items); Bergen Social Media Addiction
Scale [37](BSMAS; 6 items); Revised
Identity Style Inventory [63] (ISI-5; 36
items); Attachment Style Questionnaire
- Internet addiction, online gaming
addiction, and social media addiction
were interrelated and predicted by
common underlying risk factors
- Online gaming addiction was associated
with two identity risk factors:
informational and diffuse-avoidant
identity style.
Müller et al.,
2015 [29]
To assess how many participants were at risk
for Exercise Dependence (EXD) and if the
rates differ by gender. Also, to explore the
correlations between symptoms of EXD
and various correlates and the differences
in behavior in men and women.
German Sample;
n= 128; 18 years and
over (M= 26.5,
SD =6.7)
- Eating Disorder
- Pathological
- Hypersexual
- Alcohol Use
- Pathological
video gaming
Exercise Dependence Scale [65,66](21
items); Eating Disorder Examination
Questionnaire [67,68](28 items);
Compulsive Buying Scale [69,70](7
items); Assessment of Pathological
Computer-Gaming [71](15 items);
Hypersexual Behavior Inventory [72,73]
(15 item); Alcohol Use Disorders
Identification Test [43,74](10 items)
10.9% reported eating disorder pathology,
2.3% pathological buying, 3.1%
hypersexual behavior, and none of the
participants suffered from pathological
video gaming
- EXD symptoms were positively correlated
with both eating disorder pathology and
pathological buying, but not with
pathological video gaming
- Eating Disorder pathology was found to be
positively correlated with pathological
video gaming
Na et al., 2017
To investigate videogame usage patterns and
clinical characteristics of Internet Gaming
Disorder (IGD), Alcohol Use Disorder
(AUD), and their comorbid status within a
South Korean Adults
n= 1819; 20s40s
- Alcohol (AUD)
- Internet Gaming
DSM-5 Internet Gaming Disorder Criteria
(9 items); Alcohol Use Disorders
Identification Test [75](10 items);
Dickman Impulsivity Scale [76](23
items); Brief Self-Control Scale [77](13
items); Symptom Check-List 90
Items-Revised [78] (23 items [Depression
13 items, and Anxiety 10 items]);
Behavioral Inhibition System/Behavioral
Approach System Scale [79](20items)
- 14.1% of participants presented with
problematic gaming
- 37.9% of participants presented with
problematic alcohol use
- 21.2% of participants experienced both
problematic alcohol use and internet game
- The Comorbid group had higher smoking
rates (44.8%) compared to the alcohol
group (31.6%) or problematic gaming
group (26%)
- The comorbid group had significantly
higher AUDIT-K scores than that of the
AUD group
Pontes, 2017
To investigate the interplay between SNS
addiction and IGD and to ascertain how
they can uniquely and distinctively
contribute to increasing psychiatric
distress when accounting for potential
effects stemming from sociodemographic
and technology-related variables.
Middle School
Portuguese Sample
n= 700; 1018 years
(M= 13.02,
SD = 1.64)
Sites Addiction
- Internet Gaming
Disorder (IGD)
Bergen Facebook Addiction Scale [80](6
items); Internet Gaming Disorder
Short-Form [62](9 items); Depression,
Anxiety, and Stress Scale [81](21items)
- SNS can exacerbate the symptoms of IGD
- IGD can exacerbate the symptoms of SNS
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disorder and at risk of problematic gaming, while the other
had problematic alcohol use and problematic gaming, and at-
risk pathological buying. While this example is not statistical-
ly significant, it does illustrate that problematic gaming can
co-occur with other potentially addictive behaviors.
Moreover, the research indicates that problematic or disor-
dered gaming does not always co-occur with problematic sub-
stance use.
In a Norwegian university sample (N= 5217), Erevik et al.
[35] reported that 44.9% of participants who had low engage-
ment in gaming were more likely to experience the co-
occurrence of problematic alcohol use than those who did
not play video games (46.1%; however, this difference be-
came non-significant when controlling for demographic vari-
ables, personality, and mental health), while the 4% of partic-
ipants who experienced high levels of videogame engagement
were found to be less likely to experience problematic alcohol
use. A larger Norwegian online survey by Andreassen et al.
[36] sampled 25,533 participants and found that 7% experi-
enced problematic gaming and 13.5% experienced problem-
atic social media use. Furthermore, there was a positive asso-
ciation between symptoms of problematic gaming and prob-
lematic social media use, demonstrating common risk factors
(e.g., impulsive personality, comorbid psychopathology) and
the potential for co-occurrence. This finding was corroborated
in a study by Monacis et al. [34] which considered the com-
monalities in shared identity styles in co-occurring online be-
haviors. In their sample of university students (N=445)aged
over 20 years, they found that social media addiction and GD
shared common identity styles (i.e., informational and diffuse-
avoidant), further demonstrating the potential for these prob-
lematic behaviors to co-occur.
However, disordered gaming and problematic substance
use are not limited to the adult population. Similar results have
been found in adolescent populations. For example, in a large
survey of 21,053 Dutch adolescents by Mérelle et al. [28],
5.7% of the sample reported some problematic gaming
(5.7%) and 9.1% reported problematic social media use.
Smoking cigarettes was strongly associated with problematic
gaming. Although their results suggested a high co-
occurrence of problematic social media use and smoking cig-
arettes with problematic gaming, there was a weak association
with other substance use.
Pontes [31] investigated how disordered gaming and social
media addiction uniquely contributed to psychological dis-
tress, and how these behaviors exacerbate distress when they
co-occurred in a population of Portuguese middle school stu-
dents (N= 700). The results demonstrated thatboth disordered
gaming and social media addiction can exacerbate the symp-
toms of each other when they co-occur and contribute to de-
terioration of psychological health as indicated by increased
scores on depression, anxiety, and stress scales. In Király
et al.s nationally representative study [10], of 2073
Tab l e 1 (continued)
Paper Aims Sample Behavior/
Instruments Results/outcomes
Ream et al.,
2011 [32]
To investigate if videogame engagement
while using substances contributes to
substance abuse problems
American Sample
n= 2885; Over
18 years and over
(M= 40.4, SD = 15.7)
- Alcohol
- Cannabis
- Problem
National Survey of Drug Use-based
questionnaire (46 items); Consumer
Involvement in Video Games; Problem
Video Game Play [51](10 items)
- Problem Play significantly correlated to
problematic: Caffeine, Tabaco, alcohol,
cannabis use. Males consumed more
caffeine and alcohol, while females
consumed more nicotine
- There is a potential for drug interaction
between self-reinforcing behaviors and
addictive substances, with implications
for the development of problem use.
- Statistical models suggested that gaming an
enthusiastic hobby (i.e., video game play
frequency, enjoyment, and consumer
involvement) could potentially be a third
variable that was associated with
co-occurring use of caffeine, nicotine, and
alcohol and problematic gaming
Items in italics represent relevant measure
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adolescents, 4.3% experienced problematic gaming, 8.8% ex-
perienced problematic internet use, and 6.7% experienced
both problematic videogame use and internet use. Their re-
sults demonstrated an overlap in problematic internet use and
problematic gaming but verified that these are two distinct
problematic behaviors that have the potential to co-occur with
one another, and which may lead to the exacerbation of prob-
lematic internet use and/or problematic gaming [31].
Proxy Indicators of Prevalence of Gaming Disorder and Other
Potentially Addictive Behaviors
Other studies have focused on prevalence of disordered gam-
ing and other potentially addictive behaviors using proxy in-
dicators (e.g., using number of alcoholic drinks consumed per
day or per week to assess severity of alcohol use). Of the six
studies that assessed proxy measures of potentially addictive
behaviors [42,8287](Table2), two studies [84,99]exam-
ined general adult populations (e.g., national surveys) using
proxy indictors of problematic use, two [85,86]considered
both adolescents and adults, while the latter two [82,87]ex-
amined adolescent populations (e.g., secondary school stu-
dents). A total of five of six studies [8284,86,87] using
proxy measures investigated alcohol use and substance use,
while four considered smoking cigarettes [82,84,86,87], and
one investigated gambling [85]. The geographical locations
also varied with papers based in the USA (n=2) [83,87],
Italy (n=1) [82], Canada (n=1) [84], the Czech Republic
(n=1)[86], and France (n=1)[85].
In regard to prevalence within the adolescent populations,
two studies showed a positive correlation between the fre-
quency of video game use and substance use, demonstrating
a strong association [82,87]. More specifically, Gallimberti
et al. [82] found in their adolescent sample (N= 1156) that
16.4% experienced problematic gaming, and within this co-
hort, 41.2% had smoked cannabis, 23.2% had consumed an
energy drink (i.e., caffeine), 21.7% had smoked a cigarette
(i.e., nicotine), and 21.3% had drank alcohol (in their lifetime),
demonstrating an association between gaming and use of
these substances.
Van Roo i j e t al. [87] also suggested that higher scores on the
Video Game Addiction Test (VGAT; which assesses problem-
atic videogame use) indicated an increase in frequency of sub-
stance use. Their research showed that 36.4% of online gamers
in their sample (n= 8478) consumed alcohol, 34% smoked
cigarettes, and 44.6% smoked cannabis. This is in line with
studies that exclusively used psychometric measures to asses
use and severity of other potential addictions. A similar trend
was found in a large sample of Czech online gamers (N= 3952)
[86] which investigated gamers and the influence of psychoac-
tive substances. They found that while gaming, caffeine was the
most frequently used substance (74.2%), followed by alcohol
(40.4%), nicotine (25.3%), and illicit substances (14.5%).
Similarly, Konkolÿ Thege et al. [84] surveyed 6000 adults
and found that those who experienced problematic gaming
(2.1%), 1.2% experienced problematic alcohol use, while
31.1% experienced problematic nicotine use, and 13.5% ex-
perienced problematic cannabis use. This was calculated using
a single self-report question Thinking back over your life,
have you ever personally had a problem with [problematic
behavior or substance use]?with 3 possible responses
No,”“Yes, but not in the past 12 months,and Yes, in the
past 12 months.Using this question, the researchers also
considered potentially addictive behaviors that co-occur with
disordered gaming. Their results suggested that 37.2% of their
participants had experienced the co-occurrence of problematic
work, 36.6% had experienced problematic eating behaviors
(i.e., eating too little or too much), 14.1% had experienced
problematic sex (i.e., excessive sexual behavior), and 12.3%
had experienced problematic gambling. The latter finding was
in line with a study by McBride et al. [85], which reported that
11.4% of disordered gamers within in their sample experi-
enced problem gambling, and which is consistent within the
wider literature [100,101]. Finally, a study by Ivory et al. [83]
on US college students (n= 533) suggested that gaming was
not significantly associated with nicotine or substance use.
However, taken as a whole, the aforementioned studies tend
to indicate that disordered gaming appears to frequently co-
occur alongside problematic substance use, and there are com-
plex associations between the co-occurring problematic sub-
stance use and potential behavioral addictions.
Assessing the Etiology of Gaming Disorder and Co-occurring
Potentially Addictive Behaviors
Four [7,33,102,103] out of the 20 eligible studies identified
for review were classified as etiological papers and defined as
papers that attempted to explore the underlying mechanisms
that may contribute to co-occurrence of GD with other poten-
tially addictive behaviors and possible etiological pathways
(see Table 3). These papers also have diverse geographical
locations, including Norway [33], Spain [7], Australia [102],
and Germany [103].
Dysfunctional coping strategies have been used to explore
how underlying cognitive mechanisms contribute to the de-
velopment and maintenance of co-occurring behavioral and
substance addictions and understand etiology. Schneider
et al. [102] utilized the Brief COPE [126] to assess different
subdomains of coping styles (i.e., a range of cognitive and
behavioral responses that are utilized in stressful situations)
[127]. They surveyed 823 Australian high school students
(M= 14.3, SD = 1.4) and found that coping may play a pivotal
role when considering co-occurring risk behaviors. They
highlighted a tendency toward denial and behavioral disen-
gagement coping styleswhich were positively correlated
with substance usewithin those who scored higher on
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Table 2 Prevalence rates of co-occurrence problematic anddisorderedgamingusing proxy indicators
Paper Aims Sample Behavior/
Instruments Results/outcomes
Gallimberti et al.,
2016 [82]
The aim of the study was to investigate the
association between problematic gaming and
substance abuse in children and young
Italian Students;
n= 1156
(M= 12.03,
SD =1.03)
- Alcohol
- Cannabis
- Problematic Use
of Video Games
Pinocchio Survey (136 items - Family, Peer,
Personality, and behavior domain factors
[which included Smoking, Alcohol, Energy
Drink [Caffeine], and Cannabis);
Problematic Use of Video Games scale [88]
(adapted from the DSM-5; 6 items)
- Smoking (nicotine & cannabis), alcohol, and
energy drink consumption are associated with
Ivory et al., 2017
To explore the potential role videogames may
have on the unique health risk environment of
college and university campuses. To
predictions of the risk, incapacitation, and
inconsequential approaches to the possible role
of video games
US college
over; M=25.02,
SD =5.67)
- Alcohol
- Substance use
- Disordered eating
- Weekly
videogame use
Adapted and amalgamated version of the
National College Health Risk Behavior
Survey and the National College Health
Assessment (24 items)
- Video game play was largely unrelated to
disordered exercise, nicotine, and other
- Video game play was related to higher weight,
but reduced rates of disordered eating
Konkolÿ Thege
et al., 2016 [84]
To describe the prevalence of single versus
multiple addiction problems in a large
representative sample and to identify distinct
subgroups of people experiencing problematic
or disordered behaviors.
General Canadian
over; M=44.5,
SD =15.1)
- Alcohol
- Marijuana
- Eating
- Shopping
Alberta Addiction Survey [89](10 items);
Personal Wellbeing Index (8 Items)
- 29.8% reported a problem use with one
substance or behavior; 13.1% reported
co-occurrence of two; 7.9% reported the
co-occurrence of three or more.
- Excessive video game playing frequently
co-occurred with smoking, excessive eating
and work
- The highest co-occurring problem behaviors to
the lowest (n= 127): Work (37.2%), eating
(36.6%), nicotine (31.1%), sex (14.1%),
cannabis (13.5%), gambling (12.3%),
shopping (4.9%), alcohol (1.2%), cocaine
McBride et al.,
2017 [85]
To examine commonalities between gambling
behavior and problematic gambling among
video game players and between video game
playing and addicted playing among gamblers
French Canadian
Student Sample;
(1624 years
old; M= 18.69,
SD =1,41)
- Game Addiction
Gambling Activities Questionnaire [90](12
Video Game Activities questionnaire (12
items); Problem Gambling [91](12 items);
Gaming Addiction Scale [38](21 items)
- Video gaming was associated with gambling
- 11.4% (4) of addicted gamers (n= 35)
experienced problem gambling
Škařupová et al.,
2018 [86]
To explore levels and patterns of online gaming
while under the influence of various substances
Czech Online
(1159 years)
- Alcohol
- Psychoactive
- Illicit drugs
- Online Gaming
Addiction Engagement Questionnaire [92,93]
(24 items);
Drug use while gaming (2 items)
Caffeine was the most commonly co-occurring
substance used by 74.2%, followed by alcohol
40.4%, nicotine 25.3%, and 14.5% used illicit
substances while gaming
- Substance use was positively associated with
intensity of gaming and both addiction and
van Rooij et al.,
2014 [87]
The current study explored the nature of
problematic video gaming (PVG) and the
association with game type, psychosocial
health, and substance use
Aggregated census
data. Secondary
School sample;
- Cannabis
- Alcohol
- Problematic Video
Video Game Addiction Test [94](14 item);
Psychoactive Substance Use/Non-Use;
Self-Esteem Scale [95](10items);
Loneliness Scale [96] (10 items); Depressive
Mood List [97] (6 items);
Revised Social Anxiety Scale for Children [98]
(Subscales: Social Avoidance & Distress [6
items] and Social Avoidance & Distress in
educational Performance (1 item)
- Higher scores on PVG indicated higher use of
nicotine, alcohol and cannabis
Items in italics represent relevant measures
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Table 3 Cross-sectional papers assessing the etiology of disordered gaming
Study Aims Sample Behavior/
Instruments Results/outcomes
Andreassen et al.,
2013 [33]
To investigate behavioral addictions
and how they relate to the main
dimensions of the five-factor
model of personality
n = 218
(M= 20.7 years;
SD =3)
- Facebook
- Mobile Phone
- Compulsive
- Study
Bergen Facebook Addiction Scale [37](BFAS; 6 items);
Game Addiction Scale for Adolescents [38](GASA; 7
items); Youngs Diagnostic Questionnaire [50](YDQ; 8
items); The Exercise Addiction Inventory [104](EAI; 6
items); Mobile Phone Addiction Index [105](MPAI; 8
items); Compulsive Buying Scale [69](CBS; 13 items);
Study Addiction Scale [106](7 items; adapted from the
Bergan Work Addiction Scale); Revised NEO Five-Factor
Inventory-Revised [107] (60 items)
- Conscientiousness was negatively
associated with video game
- Conscientiousness seems to be a
protective factor for unproductive
behavioral addictions (i.e., Facebook
use, video gaming, Internet use,
compulsive buying)
- The distinction between unproductive
and productive behavioral addictions
bears some resemblance to the
distinction between impulsive
control disorders and OCD
Estévez et al.,
2017 [7]
To examine the relationship of
emotional regulation and
attachment, with disordered
substance use, disordered
behaviors in adolescents and
emerging adults
Spanish high
school students;
n= 472
(M= 15.6,
SD =1.33)
Internet Use
- Alcohol
- Substance
Difficulties in Emotion Regulation Scale [108,109](28
items); Inventory of Parent and Peer Attachment [110,111]
(Mother: 16 items Father: 16 items; Peer: 16 items);
Multicage CAD-4 [112](Alcohol [4 items] & Substance
Abuse [4 items] Subscales); Problematic Internet Use [113]
(10 items); Video Game-related Experience Questionnaire
[114](17 items); South Oaks Gambling Screen for
Adolescents [115](12 items)
- Emotional regulation is predictive of
all addictive behaviors
- Attachment is predictive of
non-substance-related addictions
- Males scored significantly higher in
gambling disorder and videogame
Schneider et al.,
2017 [102]
To investigate Internet gaming
disorder (IGD) in relation to
coping, including emotion- and
problem-focused coping styles
Australian Students
1219 years;
n= 823
(M= 14.2,
SD =1.4)
- Internet
- Substance
Internet Gaming Activities Survey; Internet Gaming Disorder
Checklist [116](12 items); Brief COPE [117](28 items)
- IGD was significantly correlated with
denial and behavioral disengagement
coping strategies
- Age was positively associated with
substance use coping
Walther et al.,
2012 [103]
To investigate co-occurrence and
shared personality characteristics
of problematic computer gaming,
problematic gambling and
substance use
German Students:
1225 years;
- Problematic
- Problematic
- Alcohol,
nicotine, and
cannabis use
Substance Use Frequencies (3 items); South Oaks Gambling
Screen - Revised for Adolescents [115](12 items); Video
Game Dependency Scale [118](10 items); Personality
Factors [119](Each original scale was reduced to 4 items);
Adapted Depression scale; Inventory of Impulsivity, Risk
Behavior and Empathy [120]; Personality Questionnaire;
Scale for General Self-Efficacy [120]; Scale for
self-efficacy in Social Situations [120]; Social Anxiety
Scale for Children Revised [121]; Rating Scale for
Attention-Deficit/Hyperactivity Disorder [122]; Rating
Scale for Oppositional Defiant/Conduct Disorders [122];
Loneliness Scale [123]; Rosenberg-Self-Esteem Scale
[124]; Satisfaction with Various Domains of Life [125]
- Alcohol, nicotine, and cannabis were
all positively correlated
- Problematic gambling and
problematic gaming were positively
- Problematic gaming co-occurred with
cannabis use
- Problematic gambling co-occurred
with alcohol, nicotine, and cannabis
- High impulsivity was associated with
all five addictive behaviors
Items in italics represent relevant measures
Curr Addict Rep (2019) 6:383401
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disordered gaming, suggesting that adolescents may employ
avoidant coping strategies.
In a sample of 472 Spanish students (aged 1321 years),
Estévez et al. [7] assessed the relationship between emotional
regulation and attachment in several addictive behaviors, in-
cluding disordered gaming. The study found that attachment
style was predictive of behavioral addictions, but not sub-
stance addictions. Poor peer attachment predicted gaming
and gambling disorders, and poor maternal attachment pre-
dicted problematic internet use.
With regard to personality, Andreassen et al. [36]found
that social media addiction, internet addiction, and disor-
dered gaming were all negatively associated with consci-
entiousness among a small sample of Norwegian universi-
ty students (n= 218). Walther, Morgenstern and
Hanewinkel [103] also proposed that co-occurrence be-
tween substance and behavioral addictions could be ex-
plained via personality traits. Their results indicated that
impulsivity and social anxiety were associated with sub-
stance users, gamblers, and gamers. The high impulsive-
ness trait (i.e., doing things without thinking them through)
characterized individuals who engage in problematic sub-
stance use, problematic gambling, and problematic gam-
ing. However, while low social anxiety was predictive of
problematic substance use and problematic gambling, the
reverse was true for problematic gaming, where those with
high social anxiety were at higher risk for problematic
gaming behavior. It should also be noted that social anxiety
has been associated with dysfunctional coping strategies (
[102], which in turn has been implicated in addiction [128,
129]. Furthermore, the researchers noted that while prob-
lematic substance users have high co-occurrence to other
addictions, each addiction to one substance showed asso-
ciations with personality traits (i.e., high impulsivity and
high extraversion) and mental health problems (e.g., high
depression, low social anxiety). Problem gamers showed
overlap in some of these traits (i.e., impulsivity and social
anxiety) with problematic gamblers.
The aim of the present paper was to review and describe the
literature on co-occurrence within the field of gaming disorder
(GD) published over the past decade. The review considered
the prevalence rates in empirical studies that investigated the
potential co-occurrence of potential behavioral addictions
and/or substance use in those with GD. It also described the
use of psychometrically validated assessment instruments and
proxy measures in assessing prevalence rates, as well as the
etiological studies that investigated the development and
maintenance of co-occurrence of potentially addictive behav-
iors among those with GD.
Ten papers considered GD and a co-occurring potential
behavioral addictions and/or substance use and employed val-
idated psychometric measures to assess the prevalence, fre-
quency, and severity of the behaviors studied. Six papers in-
vestigated adult populations [27,29,30,32,36,130], four
papers investigated adolescents [10,28,31], and one consid-
ered both [34].
Ream et al. [32] investigated a North American sample and
found that of those who consume psychoactive substances
(e.g., nicotine and/or coffee) also engaged in concurrent use
of gaming. The surveyed literature also suggested that
smoking nicotine or drinking alcohol can have an impact on
problematic gaming scores [27,30]. The broader literature
suggests an overlap between various substance and behavioral
addictions, suggesting it is a relatively common occurrence
[15] among adults. Collectively, the reviewed literature also
demonstrates that adults who play video games engage in
concurrent use of psychoactive substances, which may result
in co-occurring problematic use and engagement in potential-
ly addictive behaviors.
The surveyed literature on adolescents also reflects a range
of prevalence rates. In a nationally representative Hungarian
sample, it was shown that 4.3% experienced problematic gam-
ing, 8.8% experienced problematic internet use, and 6.7%
experienced both problematic gaming and internet use [84].
Andreassen et al.s[36] results suggest that 7% of Norwegian
adults reported problematic gaming. A similar result was
found among a Dutch sample, which reported 5.7% of their
sample experienced some problematic gaming and 9.1% re-
ported problematic social media use, both of which were
strongly associated with nicotine consumption [28]. Pontes
[31] had a similar finding in Portuguese middle school stu-
dents, which suggested that the co-occurrence of problematic
gaming and problematic social media use can lead to the de-
terioration of psychological health more so than either prob-
lematic behavior on its own. The studies also suggest that
disordered gaming shares underlying risk factors (e.g., identi-
ty styles [34]) with problematic social media use and internet
addition, suggesting that co-occurring problematic behaviors
may share common identity styles, which act as risk factors in
the co-occurrence of problematic online behaviors (i.e., gam-
ing, social media, and internet use).
These results were consistent with the wider literature in
regard to the association with potentially addictive behaviors
and/or substance use [131,132], while the findings
concerning disordered gaming also showed parallels with oth-
er behavioral addictions and substance disorder fields (e.g.,
gambling [133,134]). However, the variation in the consump-
tion of substances or frequency of behaviors within the sur-
veyed literature may indicate that traditional approaches in
psychiatric comorbidities [135] and problem behavior theory
[13] may not be a viable approach when assessing disordered
consumption of substances and resulting behaviors. Gamers
Curr Addict Rep (2019) 6:383401 393
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may instead be making pragmatic choices involving their con-
sumption of substances, which may not be an indication of
uncontrolled behavior [86]. For example, having increased
amounts of caffeine or using smartdrugs could be used to
provide a competitive edge while gaming, which could be
particularly true for those who play games professionally
[136]. This may explain why illicit substance use (as opposed
to legal substance use) varies in the surveyed literature, be-
cause it may be a choice by gamers to prolong their gaming
with stimulants such as caffeine or nicotine [83]. However,
gamers may choose to consume substances irrespective of
videogame participation [86], which would explain the high
rate of nicotine use [84] and alcohol use [130]insomesam-
ples of gamers. For example, if an individual is trying to quit
smoking, they may increase their alcohol consumption (which
has been associated with disordered gaming [30]). In an at-
tempt to offset their need for nicotine, they may engage in
other potentially addictive behaviors (e.g., alcohol consump-
tion), which may then co-occur with an addiction, such as GD.
This suggests an underlying association with disordered sub-
stance use, which can be seen in other disordered behaviors,
such as gambling disorder [137,138].
Based on the empirical studies reviewed, problematic
gamers consume a variety of substances while engaged in
videogames. More specifically, while gaming, between 23.3
74.2% of gamers consumed caffeine [82,86], 21.725.3%
smoked cigarettes [82,86], 41.244.6% smoked cannabis [28,
82], 21.340.4% consumed alcohol [82,86], and 14.5% con-
sumed illicit substances [86]. In regard to problematic and dis-
ordered behavior, the findings suggested that problematic gam-
bling [85], problematic shopping, problematic sex, and prob-
lematic work [84] were associated with disordered gaming,
while disordered exercise was not related [29,83].
Indeed, the presented evidence suggests that the co-
occurrence of potentially addictive behaviors is not uncom-
mon and is associated with a number of maladaptive outcomes
for both adults [27] and adolescents [31,139]. There appears
to be a clear divide between the experience of co-occurrence
among adults and adolescents. The literature demonstrates
that adults with disordered gaming frequently feature co-
occurring problematic or disordered substance use (e.g., alco-
hol use [30,32,35]), while disordered eating [29]appears less
frequently. However, the opposite appears to be true for ado-
lescents, who appear to experience co-occurring disordered
behaviors, such as social media addiction or problematic in-
ternet use [10,31]. The discrepancy between adults and ado-
lescents may be explained due to the scarcity of available
substances due to age-related factors [140] because disordered
substance use is seen to increase as adolescents get older
[102], allowing them to purchase alcohol or nicotine legally.
It is also worth noting that many of the problematic behaviors
co-occurring with disordered gaming are ones that can be per-
formed concurrently with gaming. For example, the surveyed
literature shows that problematic exercise and problematic gam-
ing co-occur. This may be attributed to the fact that gaming does
not typically facilitate exercise,asgamingislargelyasedentary
behavior, whereas exercise requires vigorous physical activity
[29], which acts as a protective factor in GD [141]. This idea is
also corroborated by the way the literature consistently shows
that smoking and alcohol use co-occur with GD [27,30,32,
130]. This may arise because the gaming context can facilitate
the concurrent use of alcohol and smoking (i.e., nicotine or can-
nabis), especially if used as part of a coping strategy [30].
Coping strategies were one of the three ways (i.e., (i) cop-
ing strategies, (ii) emotional regulation and attachment, and
(iii) personality characteristics) in which the development and
maintenance of co-occurrence was considered in behavioral
and substance addictions. Schneider et al. [102] considered
coping strategies to be a key element in the development
and maintenance of co-occurrence in an adolescent sample.
Their results suggested that behavioral disengagement was a
common coping strategy by those who experienced disor-
dered gaming. One proposed reason of this resulting behavior
is the self-medication hypothesis. This hypothesis suggests
that in addiction-related disorders, individuals use substances
in order to overcome painful affective states as well as related
mental disorders [142], and this has been a common area of
interest in problematic internet use [143,144]. It may also
indicate that maladaptive coping strategies (i.e., emotional
avoidance and/or behavioral disengagement) may play a key
role in the development of co-occurring behaviors within dis-
ordered gaming. Furthermore, when these coping strategies
co-occur, it is evident that these strategies will exacerbate
disordered gaming symptoms, more so than either one on their
own [145]. However, while there has been some literature to
suggest that maladaptive coping strategies play an important
role in problematic internet use [8,145], further research is
needed in the case of disordered gaming.
Estévez et al. [7] suggested that disordered behavior (e.g.,
disordered gaming) and substance use may be explained utilizing
emotional regulation and attachment theory. It has been sug-
gested that low levels of emotional regulation are associated with
an increase in risky behaviors, such as GD [146] and substance
use [147]. Furthermore, emotional regulation is also predictive of
addictive behaviors (but not substance addiction), suggesting that
individuals with difficulty in emotional regulation may engage in
addictive behaviors such as gaming to avoid (i.e., behavioral
disengage) or regulate negative feelings or emotions (i.e., the
self-medication hypothesis [7,145,148]). Moreover, Estévez
and colleaguesresearch suggests that attachment may also pre-
dict co-occurring use, specifically in behaviors that are potential-
ly addictive. Poor peer-attachment was found to predict GD and
gambling disorder, and poor maternal attachment predicted prob-
lematic internet use. Individuals with a secure attachment are
characterized by a self-acceptance of emotional needs.
However, an individual with a non-secure attachment style
Curr Addict Rep (2019) 6:383401
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may pay little attention to their emotional needs and feel they
have a lack of support [7]. This may then cause them to avoid
interpersonal relationships [149], lending support to the notion
that behavioral addictions may be understood as a form of escape
and compensation for poor relationships [150]. Indeed, it could
be suggested that individuals employ maladaptive behavioral
coping strategies in response to poor emotional regulation or
attachment, which may in turn aid in the development and main-
tenance of co-occurring at-risk behaviors.
Another dimension that has been considered in the develop-
ment and maintenance of co-occurrence in GD is personality
traits and factors. Low conscientiousness has been found to be
associated with behavioral addictions (e.g., SNS addiction and
GD [33]). This suggests that people who experience problem-
atic or disordered gaming may have low conscientiousness and
may have a low priority of duties and obligations [151], lack of
planning ability [152], low self-control, weakness for tempta-
tions [153], and experience procrastination [154]. This is in line
with Walther et al. [103], whose results suggested that individ-
uals that experience problematic or disordered gaming also
have high impulsiveness (i.e., a lack of self-control), which
has been associated with problematic or disordered behavior,
and/or substance use [155]. Furthermore, problematic gamers
only shared a small overlap in personality factors with problem
gambling (i.e., problematic behavior), even though problematic
gambling shares more of an overlap in personality factors with
problematic substance use than problematic gaming. However,
problematic gamers reported higher scores on ADHD symp-
toms, high irritability/aggression, high social anxiety, and low
self-esteem than any other addiction in Walther et al.s paper
[103], suggesting that gaming may take a unique dispositional
position within the examined addictive behaviors here. The
aforementioned studies indicate that personality traits or factors
may impact the likelihood for co-occurrence to manifest in
people experiencing problematic or disordered gaming.
The literature reviewed represents important examples of the
next logical step in the progression of research beyond preva-
lence rates of co-occurrence. Each of the reviewed studies ex-
plored either specific psychological, sociological, and/or physio-
logical factors. This in turn can guide future research into pre-
senting a holistic representation of the specific risk factors (e.g.,
coping strategies and identity styles), which may contribute to
developing, maintaining, or exacerbating co-occurring potential-
ly addictive disorders. Furthermore, future research could help
inform public policy and guide the development of treatment that
encompasses the full clinical presentations of patients. However,
only four recent studies [7,80,102,103] have taken the extra
step to investigate the etiology and mechanisms of co-occurring
Understanding these processes is needed to further the un-
derstanding of addictive disorders. Nevertheless, the extant
findings are beneficial in advancing the field and providing a
framework for how to consider the mechanisms of co-occurring
addictive behaviors in a multifaceted manner. Furthermore, the
present review also highlights the potential for differing mech-
anisms of action, despite similar observed effects, suggesting
that behavioral and substance addictions, and their co-
occurrence involve complex processes. In understanding these
factors, treatment efficacy may be increased by targeting com-
mon etiological mechanisms across multiple disorders (e.g.,
coping mechanisms [102], or personality factors [103]), much
like the direction of the literature within the substance disorders
Co-occurrence Within Disordered Gaming Compared
to the Substance Disorder Literature
Arguably, GD is one of the newer behavioral disorders to be
investigated. Nevertheless, past substance use disorder literature
can be used to provide a reference point on how to advance the
co-occurrence research into disordered gaming. The drug and
alcohol abuse literature appears to focus on the epidemiology
of co-occurrence as it appears to be commonly studied [156], a
trend that the GD literature is following. Furthermore, within the
substance abuse literature, co-occurring behavioral and substance
addictions appear to be commonly considered in both the general
and clinical populations [25,87], indicating that the GD literature
should also mimic this global approach. In addition, individuals
with co-occurring behavioral or substance use disorders (or prob-
lematicuse)tendtohavepoorerfunctioning and treatment out-
comes, much like individuals with disordered gaming
[156158]. These findings within the substance use literature
are in part facilitated by the longitudinal research investigating
the development, maintenance, and remission of each disorder,
which the present field of co-occurrence in disordered gaming
While research on GD focuses on the prevalence and co-
occurrence of psychiatric disorders [23], the substance use lit-
erature has gone much further by investigating and identifying
the epidemiological factors of co-occurrence and the impact co-
occurring disorders can have. For example, there have been a
number of studies that have investigated a wide range of under-
lying mechanisms between co-occurring substance use and oth-
er disorders such as neurobiological commonalities, genetic
markers, temporal changes, and qualitative research focusing
on behavioral changes [159,160]. Furthermore, the substance
use literature has also investigated whether treating one disorder
causes the accompanying co-occurring disorder to go into re-
mission, concluding that it can vary depending upon the disor-
ders and individual presentation [25,161]. However, when
looking to research concerning disordered gaming, this addi-
tional step has not yet been made, and the effects of co-
occurrence and its impact on course of illness and by type of
disorder are not yet known. Additionally, the substance abuse
literature has also closely examined the exacerbating effects of
multiple co-occurring disorders [158,162]. While the research
Curr Addict Rep (2019) 6:383401 395
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
on disordered gaming has begun to move in this direction,
research on substance use has attempted to separate various
dimensions of co-occurrence (e.g., psychiatric disorders, mental
health, and social functioning) by controlling for their effects on
the primary disorder in question [163].
Finally, when considering treatments, the substance use lit-
erature has paved the way for behavioral disorders. There is a
general agreement that co-occurring disorders may require an
integrated approach [164,165] which consider not just the pri-
mary disorder, but also the co-occurring disorder. For example,
in a systematic review on people who experiences severe men-
tal illness and co-occurring substance use suggested that moti-
vational interviewing in conjunction with cognitive behavior
therapy (CBT; targeting both substance use, and mental health
respectively) showed qualityevidence for reducing substance
use and improving mental health than just CBT alone.
However, this type of approach is not near the level of accep-
tance as more traditional treatments (such as CBT), although
there are considerable efforts to evaluate its efficacy in the sub-
stance use field [24,162]. In contrast, the research into integra-
tive treatments that targets both disordered gaming and co-
occurring addictive disorders is, to the best of authorsknowl-
edge, notably absent from the literature.
Future Research
A majority of the surveyed literature does not go beyond mea-
sures of association and with measures of prevalence being ques-
tionable due to overwhelming lack of representativeness of sam-
ples. The published literature suggests that there are various be-
havioral and substance-related addiction disorders that have the
potential to co-occur with GD. However, there is very little ad-
ditional literature that continues to investigate this further.
Regarding the co-occurrence of disordered gaming with other
behavioral addictions, only a few studies exist, suggesting a co-
occurrence with problematic gambling, shopping, and social me-
dia use. While there has not been an extensive amount of litera-
ture on the co-occurrence prevalence rates of disordered gaming
with other addictive behaviors, it has been explored across sev-
eral geographical locations and cultures, indicating that it is mov-
ing in a similar direction of other addiction-related literature (e.g.,
gambling [157]). However, while it is important that this line of
enquiry is followed, it is also important to investigate the etio-
logical aspects of co-occurrence within GD because it is experi-
enced differently across culturally diverse groups of people.
There is a significant gap in the literature when it comes to
longitudinal studies that focus on the changes of co-occurring
addictive disorders over time. The current literature estab-
lishes that co-occurrences between disordered gaming and
other addictive-related disorders are common. Furthermore,
no paper to the authorsknowledge has investigated whether
disordered gaming preceded the onset of another co-occurring
addictive disorder or vice versa. It is imperative to understand
how co-occurring disorders interact over time in order to de-
velop appropriate treatment methods. Moreover, models for
hypothesizing potential treatment frameworks and outcomes,
which consider onset or remission of other co-occurring prob-
lematic or disordered behavior, would be instrumental in im-
proving potential effectiveness of treatment methods. For ex-
ample, having confidence that disordered gaming symptoms
typically occur within specific substance abuse disorders (e.g.,
alcohol or cannabis abuse) may allow for a more tailored
approach that targets both disordered gaming and the co-
occurring use of other behaviors or substances. Future studies
should also consider investigating the time of onset in relation
to disordered gaming because this would also provide more
robust data and allow for more significant conclusions to be
Substance Use Literature May Act as a Model to Guide
Future Research
A finding that was consistent across both adults and adoles-
cents was that those who presented with problematic or disor-
dered gaming and a co-occurring addiction-related condition
consistently reported more severe experiences as assessed
using clinical measures [27,30,31], which is mirrored within
the substance abuse literature [25,166]. Another way in which
the reviewed literature mirrored the substance use literature is
the calls for the early intervention for individuals experiencing
co-occurring disorders [167], with a number of studies calling
for additional early intervention screening measures [30], pro-
viding psychoeducation on the co-occurring disorder [27], or
considering shared clinical features (e.g., personality factors
[33]). These suggestions highlight the need for careful clinical
assessment of co-occurring problematic behaviors that may
have developed on a subclinical level and, thus, might con-
tribute to the primary disorder.
The momentum of research examining GD more generally
has increased and those in the field are engaging in effective
efforts to understand the impact of co-occurring addictive be-
haviors. The substance use literature provides various research
frameworks and designs that could be utilized in the future to
bring gaming research in line with the wider field of addictive
disorders. For example, investigating the nuances between
different co-occurring disordered use in clinical samples
[25], continuing investigations into prevalence, but expanding
and evaluating the epidemiological data of such impacts as
onset and remission [22], and establishing clinical trials and
protocols that are tailored toward individuals presenting with
co-occurring disorders [25,160].
Although the present review identified several important
trends within the disordered gaming co-occurrence literature,
Curr Addict Rep (2019) 6:383401
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
it is subject to limitations. Firstly, methodology used in the
review was descriptive and does not quantitatively synthesize
data. Although the authors followed a rigorous and transparent
review methodology, it still investigates the breadth of litera-
ture, rather than its depth, and as such, no statistical conclu-
sions can be drawn from the results. Secondly, the study ex-
cluded literature that was not peer-reviewed. Furthermore, the
inclusion criteria meant that only English language papers
were reviewed, limited by a specific set of databases and
search terms. As a result, the authors may have missed rele-
vant studies in other languages or databases. As with any
review, screening and selection is always a subjective process
and is thus prone to biases. Despite capturing a wide range of
research terms in several databases, it is possible that relevant
studies may have been missed due to a lack of fit with the
inclusion criteria. Finally, considering only the use of papers
that were published in the last several years may have also
contributed the small amount of papers on co-occurrence and
gaming disorder.
The evidence in the present review suggests an increase in
research interest on co-occurrence of other addiction-related
behaviors with disordered gaming. However, currently, most
research investigates the prevalence rates of co-occurring ad-
diction-related disorders with disordered gaming and fre-
quently demonstrated the potential for co-occurrence between
problematic and disordered behaviors and substance use.
Various reviewed papers considered novel ways to investigate
the potential development and maintenance of problematic
and disordered gaming and its co-occurrence, which could
be improved further by considering the frameworks and study
designs used in the substance addiction disorder literature.
Indeed, the research indicates that co-occurrence in problem-
atic and/or disordered gaming is common, and when examin-
ing the substance use field as a guide, outcomes may be im-
proved when separate treatment modalities for these co-
occurring disorders are offered in combination. While it is
not certain how well these treatment models may work
in a diverse population, current research consistently calls
for trials of multimodal treatment (i.e., using tailored
treatments that consider co-occurring behavior or sub-
stance use) to take place.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://, which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
Papers of particular interest, published recently, have been
highlighted as:
Of importance
1. Yau YHC, Crowley MJ, Mayes LC, Potenza MN. Are Internet use
and video-game-playing addictive behaviors? Biological, clinical
and public health implications for youths and adults. Minerva
Psichiatr. 2012;53:15370.
2. American Psychiatric Association (2014) Diagnostic and statisti-
cal manual of mental disorders : DSM-5.
3. World Health Organization. ICD-11 for mortality and morbidity
statistics. In: Int. Classif. Dis; 2018.
4. Lemmens JS, Valkenburg PM, Peter J. The effects of pathological
gaming on aggressive behavior. J Youth Adolesc. 2011;40:3847.
5. Griffiths MD, Meredith A. Videogame addiction and its treatment.
J Contemp Psychother. 2009;39:24753.
6. Grüsser SM, Thalemann R, Griffiths MD. Excessive computer
game playing: evidence for addiction and aggression?
CyberPsychology Behav. 2007;10:2902.
7. Estévez A, Jáuregui P, Sánchez-Marcos I, López-González H,
Griffiths MD. Attachment and emotion regulation in substance
addictions and behavioral addictions. J Behav Addict. 2017;6:
8. Brand M, Laier C, Young KS. Internet addiction: coping styles,
expectancies, and treatment implications. Front Psychol. 2014;5.
9. Yung K, Eickhoff E, Davis DL, Klam WP, Doan AP. Internet
addiction disorder and problematic use of Google Glass
in pa-
tient treated at a residential substance abuse treatment program.
Addict Behav. 2015;41:5860.
10. Király O, Griffiths MD, Urbán R, Farkas J, Kökönyei G, Elekes Z,
et al. Problematic internet use and problematic online gaming are not
the same: findings from a large nationally representative adolescent
sample. Cyberpsychology, Behav Soc Netw. 2014;17:74954.
11. Adams BLM, Stavropoulos V, Burleigh TL, Liew LWL, Beard
CL, Griffiths MD. Internet gaming disorder behaviors in emergent
adulthood: a pilot study examining the interplay between anxiety
and family cohesion. Int J Ment Health Addict. 2018;17:82844.
12. King DL, Delfabbro PH, Zwaans T, Kaptsis D. Clinical features and
axis I comorbidity of Australian adolescent pathological Internet and
video game users. Aust New Zeal J Psychiatry. 2013;47:105867.
13. Ko C, Yen J-Y, Yen C, Chen C, Weng C, Chen C. The association
between internet addiction and problematic alcohol use in adoles-
cents: the problem behavior model. CyberPsychology Behav.
14. Schimmenti A, Infanti A, Badoud D, Laloyaux J, Billieux J.
Schizotypal personality traits and problematic use of massively-
multiplayer online role-playing games (MMORPGs). Comput
Human Behav. 2017;74:28693.
15. Sussman S, Lisha N, Griffiths M. Prevalence of the addictions: a
problem of the majority or the minority? Eval Health Prof. 2011;34:
16. Haylett SA, Stephenson GM, Lefever RMH. Covariation in ad-
dictive behaviours: a study of addictive orientations using the
shorter PROMIS questionnaire. Addict Behav. 2004;29:6171.
17. Gossop M. A web of dependence. Addiction. 2001;96:6778.
Curr Addict Rep (2019) 6:383401 397
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
18. Martin RJ, Usdan S, Cremeens J, Vail-Smith K. Disordered gam-
bling and co-morbidity of psychiatric disorders among college
students: an examination of problem drinking, anxiety and depres-
sion. J Gambl Stud. 2014;30:32133.
19. Urbanoski KA, Castel S, Rush BR, Bassani DG, Wild TC. Use of
mental health care services by Canadians with co-occurring sub-
stance dependence and mental disorders. Psychiatr Serv. 2007;58:
20. Burleigh TL, Stavropoulos V, Liew LWL, Adams BLM, Griffiths
MD. Depression, internet gaming disorder, and the moderating
effect of the gamer-avatar relationship: an exploratory longitudinal
study. Int J Ment Health Addict. 2018;16:10224.
21. Najt P, Fusar-Poli P, Brambilla P. Co-occurring mental and sub-
stance abuse disorders: a review on the potential predictors and
clinical outcomes. Psychiatry Res. 2011;186:15964.
22. Freimuth M, Waddell M, Stannard J, Kelley S, Kipper A,
Richardson A, et al. Expanding the scope of dual diagnosis and
co-addictions: behavioral addictions. J Groups Addict Recover.
23. Ko C-H, Yen J-Y, Yen C-F, Chen C-S, Chen C-C. The association
between internet addiction and psychiatric disorder: a review of
the literature. Eur Psychiatry. 2012;27:18.
24. Burdzovic Andreas J, Lauritzen G, Nordfjærn T. Co-occurrence
between mental distress and poly-drug use: a ten year prospective
study of patients from substance abuse treatment. Addict Behav.
25. Morisano D, Babor TF, Robaina KA. Co-occurrence of substance
use disorders with other psychiatric disorders: implications for
treatment services. NAD Publ. 2014;31:525.
26. Siddaway AP, Wood AM, Hedges LV. How to do a systematic
review: a best practice guide for conducting and reporting narra-
tive reviews, meta-analyses, and meta-syntheses. Annu Rev
Psychol. 2019;70:74770.
27. Lee HJ, Tran DD, Morrell HER. Smoking, ADHD, and problem-
atic video game use: a structural modeling approach.
Cyberpsychology, Behav Soc Netw. 2018;21:2816.
28. Mérelle SYM, Kleiboer AM, Schotanus M, Cluitmans TLM,
Waardenburg CM, Kramer D, et al. Which health-related prob-
lems are associated with problematic video-gaming or social me-
dia use in adolescents? A large-scale cross-sectional study. Clin
Neuropsychiatry. 2017;14:119.
29. Müller A, Loeber S, Söchtig J, Te Wildt B, De Zwaan M. Risk for
exercise dependence, eating disorder pathology, alcohol use dis-
order and addictive behaviors among clients of fitness centers. J
Behav Addict. 2015;4:27380.
30. Na E, Lee H, Choi I, Kim D-JD-J. Comorbidity of internet gaming
disorder and alcohol use disorder: a focus on clinical characteris-
tics and gaming patterns. Am J Addict. 2017;26:32634.
31. Pontes HM.Investigating the differential effects of social network-
ing site addiction and Internet gaming disorder on psychological
health. J Behav Addict. 2017;6:60110.
32. Ream GL, Elliott LC, Dunlap E. Playing video games while using
or feeling the effects of substances: associations with substance
use problems. Int J Environ Res Public Health. 2011;8:397998.
33. Andreassen C, Griffiths MD, Gjertsen SR, Krossbakken E, Kvam
S, Pallesen S. The relationships between behavioral addictions and
the five-factor model of personality. J Behav Addict. 2013;2:909.
34. Monacis L, De Palo V, Griffiths MD, Sinatra M. Exploring indi-
vidual differences in online addictions: the role of identity and
attachment. Int J Ment Health Addict. 2017;15:85368.
35.Erevik EK, Torsheim T, Andreassen CS, Krossbakken E, Vedaa
Ø, Pallesen S (2019) The associations between low-level gaming,
high-level gaming and problematic alcohol use. Addict Behav
Reports 100186 This article is important as it provided novel
insight in the way gaming can also act as a protective factor in
co-occurning problematic substance use.
36. Andreassen C, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z,
Mazzoni E, et al. The relationship between addictive use of social
media and video games and symptoms of psychiatric disorders: a
large-scale cross-sectional study. Psychol Addict Behav. 2016;30:
37. Andreassen CS, Torsheim T, Brunborg GS, Pallesen S.
Development of a Facebook addiction scale. Psychol Rep.
38. Lemmens JS, Valkenburg PM, Peter J. Development and valida-
tion of a game addiction scale for adolescents. Media Psychol.
39. Kessler RC, Adler L, Ames M, et al. The World Health
Organization adult ADHD self-report scale (ASRS): a short
screening scale for use in the general population. Psychol Med.
40. Foa EB, Huppert JD, Leiberg S, Langner R, Kichic R, Hajcak G,
et al. The obsessive-compulsive inventory: development and val-
idation of a short version. Psychol Assess. 2002;14:48596.
41. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the
hospital anxiety and depression scale. J Psychosom Res. 2002;52:
42. Kircaburun K, Griffiths MD. The dark side of internet: preliminary
evidence for the associations of dark personality traits with specif-
ic online activities and problematic internet use. J Behav Addict.
43. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG (2001)
The alcohol use disorders identification test guidelines for use in
primary care. Organ. Mund. la Salud.
44. Donnellan MB, Oswald FL, Baird BM, Lucas RE. The mini-IPIP
scales: tiny-yet-effective measures of the big five factors of per-
sonality. Psychol Assess. 2006;18:192203.
45. Derogatis LR, Lipman RS, Rickels K, Uhlenhuth EH, Covi L. The
Hopkins symptom checklist (HSCL): a self-report symptom in-
ventory. Behav Sci. 1974;19:115.
46. Pápay O, Urbán R, Griffiths MD, Nagygyörgy K, Farkas J,
Kökönyei G, et al. Psychometric properties of the problematic
online gaming questionnaire short-form and prevalence of prob-
lematic online gaming in a national sample of adolescents.
Cyberpsychology, Behav Soc Netw. 2013;16:3408. https://doi.
47. Demetrovics Z, Szeredi B, Rózsa S. The three-factor model of
internet addiction: the development of the problematic internet
use questionnaire. Methods: Behav. Res; 2008.
48. Radloff LS. The CES-D scale: a self-report depression scale for
research in the general population. Appl Psychol Meas. 1977;1:
49. Winch RF, Rosenberg M. Society and the adolescent self-image.
Soc Forces. 2006;44:255.
50. Young KS. Internet addiction: the emergence of a new clinical
disorder. CyberPsychology Behav. 1998;1:23744.
51. Tejeiro Salguero RA, Bersabé Morán RM. Measuring problem
video game playing in adolescents. Addiction. 2002;97:16016.
52. Conners CK, Erhardt D, Epstein JN, Parker JDA, Sitarenios G,
Sparrow E. Self-ratings of ADHD symptoms in adults I: factor
structure and normative data. J Atten Disord. 1999;3:14151.
53. Meerkerk G-J, Van Den Eijnden RJJM, Vermulst AA, Garretsen
HFL. The compulsive internet use scale (CIUS): some psychomet-
ric properties. CyberPsychology Behav. 2008;12:16. https://doi.
Curr Addict Rep (2019) 6:383401
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
54. van Rooij AJ, Ferguson C, Van de Mheen D, Schoenmakers TM.
Problematic internet use: comparing video gaming and social me-
dia use (conference abstract). J Behav Addict. 2015;4:162.
55. DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P. Mortality
prediction with a single general self-rated health question: a meta-
analysis. J Gen Intern Med. 2006;21:26775.
56. Muris P, Meesters C, van den Berg F. The Strengths and
Difficulties Questionnaire (SDQ). Eur Child Adolesc Psychiatry.
57. American Academy of Pediatrics. Committee on public education
(2001) American academy of pediatrics: children, adolescents,
and television. Pediatrics.
58. Kemper HCG, Ooijendijk WTM, Stiggelbout M (2000)
Consensus over de Nederlandse norm voor gezond bewegen.
Tijdschr. voor gezondheidswetenschappen.
59. Martens M, van Assema P, Brug J. Why do adolescents eat what
they eat? Personal and social environmental predictors of fruit,
snack and breakfast consumption among 1214-year-old Dutch
students. Public Health Nutr. 2005;8:125865.
60. Fioravanti G, Casale S. Evaluation of the psychometric properties
of the Italian internet addiction test. Cyberpsychology, Behav Soc
Netw. 2015;18:1208.
61. Monacis L, de Palo V, Griffiths MD, Sinatra M. Validation of the
Internet Gaming Disorder Scale Short-Form (IGDS9-SF) in an
Italian-speaking sample. J Behav Addict. 2016;5:68390.
62. Pontes HM, Griffiths MD. Measuring DSM-5 internet gaming
disorder: development and validation of a short psychometric
scale. Comput Human Behav. 2015;45:13743.
63. Monacis L, de Palo V, Sinatra M, Berzonsky MD. The revised
identity style inventory: factor structure and validity in Italian
speaking students. Front Psychol. 2016;7.
64. Fossati A, Feeney JA, Donati D, Donini M, Novella L, Bagnato
M, et al. On the dimensionality of the attachment style question-
naire in Italian clinical and non clinical participants. J Soc Pers
Relat. 2003;20:5579.
65. Hausenblas HA, Downs DS. How much is too much? The devel-
opment and validation of the exercise dependence scale. Psychol
Heal. 2002;17:387404.
66. Müller A, Claes L, Smits D, Gefeller O, Hilbert A, Herberg A,
et al. Validation of the German version of the exercise dependence
scale. Eur J Psychol Assess. 2013;29:2139.
67. Fairburn CG, Beglin SJ. Assessment of eating disorder psychopa-
thology: interview or self-report questionnaire. Int J Eat Disord.
68. Hilbert A, de Zwaan M, Braehler E. How frequent are eating
disturbances in the population? Norms of the eating disorder ex-
amination-questionnaire. PLoS One. 2012.
69. Faber RJ, OGuinn TC. A clinical screener for compulsive buying.
J Consum Res. 2002;19:459.
70. Mueller A, Mitchell JE, Crosby RD, Gefeller O, Faber RJ, Martin
A, et al. Estimated prevalence of compulsive buying in Germany
and its association with sociodemographic characteristics and de-
pressive symptoms. Psychiatry Res. 2010;180:13742. https://doi.
71. Wölfling K, Müller KW, Beutel M. Reliability and validity of the
scale for the assessment of Pathological Computer-Gaming
(AICA-S). Medizinische Psychol: Psychother. Psychosom; 2011.
72. Klein V, Rettenberger M, Boom K-D, Briken P (2014) A valida-
tion study of the German version of the hypersexual behavior
inventory (HBI). Eine Validierungsstudie der Dtsch Version des
Hypersexual Behav Invent (HBI).
73. Reid RC, Li DS, Gilliland R, Stein JA, Fong T. Reliability, valid-
ity, and psychometric development of the pornography consump-
tion inventory in a sample of hypersexual men. J Sex Marital Ther.
74. Dybek I, Bischof G, Grothues J, Reinhardt S, Meyer C, Hapke U,
et al. The reliability and validity of the Alcohol Use Disorders
Identification Test (AUDIT) in a German general practice popula-
tion sample. J Stud Alcohol. 2006;67:47381.
75. So K, Sung E. A validation study of the brief Alcohol Use
Disorder Identification Test (AUDIT): a brief screening tool de-
rived from the AUDIT. Korean J Fam Med. 2013;34:11.
76. Dickman SJ. Functional and dysfunctional impulsivity: personal-
ity and cognitive correlates. J Pers Soc Psychol. 1990;58:95102.
77. Won S-D, Han C. Reliability and validity of the Korean version of
the impaired control scale. Psychiatry Investig. 2018;15:85260.
78. Kim KI, Kim JH, Won HT. Korean manual of symptom checklist-
90- revision. Seoul: Jung Ang Juk Sung Publisher; 1984.
79. Kim K, Kim WS.Korean-BAS/BIS scale. Korean J Heal Psychol.
80. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics
Z, Mazzoni E, et al. The relationship between addictive use of
social media and video games and symptoms of psychiatric disor-
ders: a large-scale cross-sectional study. Psychol Addict Behav.
81. Lovibond PF, Lovibond SH. The structure of negative emotional
states: comparison of the Depression Anxiety Stress Scales
(DASS) with the Beck depression and anxiety inventories.
Behav Res Ther. 1995;33:33543.
82. Gallimberti L, Buja A, Chindamo S, Rabensteiner A, Terraneo A,
Marini E, et al. Problematic use of video games and substance
abuse in early adolescence: a cross-sectional study. Am J Health
Behav. 2016;40:594603.
83. Ivory AH, Ivory JD, Lanier M. Video game use as risk exposure,
protective incapacitation, or inconsequential activity among uni-
versity students. J Media Psychol. 2017;29:4253.
84. Konkolÿ Thege B, Hodgins DC, Wild TC. Co-occurring sub-
stance-related and behavioral addiction problems: a person-cen-
tered, lay epidemiology approach. J Behav Addict. 2016;5:614
85. McBride J, Derevensky J. Gambling and video game playing
among youth. J Gambl Issues. 2017;2016:15678.
86. Škařupová K, Blinka L, Ťápal A. Gaming under the influence: an
exploratory study. J Behav Addict. 2018;7:4938.
87. van Rooij AJ, Kuss DJ, Griffiths MD, Shorter GW, Schoenmakers
TM, van de Mheen D. The (co-)occurrence of problematic video
gaming, substance use, and psychosocial problems inadolescents.
J Behav Addict. 2014;3:15765.
88. American Psychiatric Association (2014) Diagnostic and statisti-
cal manual of mental disorders : DSM-5.
89. Konkolÿ Thege B, Colman I, El-guebaly N, Hodgins DC, Patten
SB, Schopflocher D, et al. Substance-related and behavioural ad-
diction problems: two surveys of Canadian adults. Addict Res
Theory. 2015;23:3442.
90. McBride J, Derevensky J. Internet gambling behavior in a sample
of online gamblers. Int J Ment Health Addict. 2009;7:14967.
91. American Psychiatric Association (2000) Diagnostic and statisti-
cal manual of mental disorders. 4th text revision ed. American
Psychiatric Association, Washington.
92. Charlton JP, Danforth IDW. Distinguishing addiction and high
engagement in the context of online game playing. Comput
Human Behav. 2007;23:153148.
Curr Addict Rep (2019) 6:383401 399
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
93. Charlton JP, Danforth IDW. Validating the distinction between
computer addiction and engagement: online game playing and
personality. Behav Inf Technol. 2010;29:60113.
94. van Rooij AJ, Schoenmakers TM, van den Eijnden RJ, Vermulst
AA, van de Mheen D. Video game addiction test: validity and
psychometric characteristics. Netw: Cyberpsychol. Behav. Soc;
95. Rosenberg M. Society and the adolescent self-image. Princeton
NJ: Princeton University Press; 1965.
96. Russell D, Peplau LA, Cutrona CE. The revised UCLA loneliness
scale: concurrent and discriminant validity evidence. J Pers Soc
Psychol. 1980;39:47280.
97. Engels RCME, Finkenauer C, Meeus W, DekovićM. Parental
attachment and adolescentsemotional adjustment: the associa-
tions with social skills and relational competence. J Couns
Psychol. 2001;48:42839.
98. La Greca AM, Stone WL. Social anxiety scale for children-re-
vised: factor structure and concurrent validity. J Clin Child
Psychol. 2005;22:1727.
99. Jiang Z, Shi M. Prevalence and co-occurrence of compulsive buy-
ing, problematic internet and mobile phone use in college students
in Yantai, China: relevance of self-traits. BMC Public Health.
100. Kessler RC, Hwang I, Labrie R, Petukhova M, Sampson NA,
Winters KC, et al. DSM-IV pathological gambling in the national
comorbidity survey replication. Psychol Med. 2008;38:135160.
101. McBride J, Derevensky J. Internet gambling and risk-taking
among students: an exploratory study. J Behav Addict. 2012;1:
102. Schneider LA, King DL, Delfabbro PH. Maladaptive coping
styles in adolescents with internet gaming disorder symptoms.
Int J Ment Health Addict. 2018;16:90516.
103. Walther B, Morgenstern M, Hanewinkel R. Co-occurrence of ad-
dictive behaviours: personality factors related to substance use,
gambling and computer gaming. Eur Addict Res. 2012;18:167
104. Terry A, Szabo A, Griffiths M. The exercise addiction inventory: a
new brief screening tool. Addict Res Theory. 2004;12:48999.
105. Leung L. Leisure boredom, sensation seeking, self-esteem, and
addiction: symptoms and patterns of cell phone use. Mediat
Interpers Commun. 2008.
106. Andreassen CS, Griffiths MD, Hetland J, Pallesen S.
Development of a work addiction scale. Scand J Psychol.
107. McCrae RR, Costa PT. A contemplated revision of the NEO five-
factor inventory. Pers Individ Dif. 2004;36:58796. https://doi.
108. Gratz K, Roemer L. Multidimensional assessment of emotion reg-
ulation and dysregulation. J Psychopathol Behav Assess. 2004;26:
109. Hervás, Gonzalo; Jódar R (2008) Adaptación al castellano de la
Escala de Dificultades en la Regulación Emocional. Clínica y
110. Armsden GC, Greenberg MT. The inventory of parent and peer
attachment: individual differences and their relationship to psy-
chological well-being in adolescence. J Youth Adolesc. 1987;16:
111. Gallarin M, Alonso-Arbiol I. Dimensionality of the inventory of
parent and peer attachment: evaluation with the Spanish version.
Span J Psychol. 2013;16:E55.
112. Pedrero Pérez EJ, Rodríguez Monje MT, Gallardo Alonso F,
Fernández Girón M, Pérez López M, Chicharro Romero J.
Validación de un instrumento para la detección de trastornos de
control de impulsos y adicciones: el MULTICAGE CAD-4.
Trastor Adict. 2007;9:26978.
113. Fargues MB, Lusar AC, Jordania CG, Sánchez XC. Validación de
dos escalas breves para evaluar la adicción a Internet y el abuso de
móvil. Psicothema. 2009.
114. Chamarro A, Carbonell X, Manresa JM, Munoz-Miralles R,
Ortega-Gonzalez R, Lopez-Morron MR, et al. El Cuestionario
de Experiencias Relacionadas con los Videojuegos (CERV): Un
instrumento para detectar el uso problemático de videojuegos en
adolescentes españoles. Adicciones. 2014;26:30311.
115. Winters KC, Stinchfield RD, Fulkerson J. Toward the develop-
ment of an adolescent gambling problem severity scale. J Gambl
Stud. 1993;9:6384.
116. Petry NM, Rehbein F, Gentile DA, Lemmens JS, Rumpf HJ,
Mößle T, et al. An international consensus for assessing internet
gaming disorder using the new DSM-5 approach. Addiction.
117. Carver CS, Scheier MF, Weintraub KJ. Assessing coping strate-
gies: a theoretically based approach. J Pers Soc Psychol. 1989;56:
118. Rehbein F, Psych G, KleimannM,MediasciG,MößleT.
Prevalence and risk factors of video game dependency in adoles-
cence: results of a German nationwide survey. Cyberpsychology,
Behav Soc Netw. 2010;13:26977.
119. Kandel DB, Davies M. Epidemiology of depressive mood in ad-
olescents: an empirical study. Arch Gen Psychiatry. 1982;39:
120. Stadler C, Janke W, Schmeck K. IVE: Inventar zur Erfassung von
Impulsivität, risikoverhalten und empathie bei 9- bis 14-jährigen
Kindern : Manual. Göttingen: Hogrefe; 2002.
121. Melfsen SS. Sozial ängstliche Kinder: Untersuchungen zum
mimischen Ausdrucksverhalten und zur Emotionserkennung.
Marburg: Tectum-Verlag; 1999.
122. Döpfner M, Lehmkuhl G (1998) DISYPS-KJ: Diagnostik-System
für psychische Störungen im Kindes- und Jugendalter nach ICD-
10 und DSM-IV ; klinische Diagnostik - Elternurteil - Erzieher-
und Lehrerurteil - Selbsturteil ; Manual, 2nd ed. Huber, Bern.
123. Döring N, Bortz J. Psychometrische einsamkeitsforschung:
Deutsche neukonstruktion der UCLA loneliness scale.
Diagnostica. 1993.
124. von Collani G, Herzberg PY. Eine revidierte Fassung der
deutschsprachigen Skala zum Selbstwertgefühl von Rosenberg.
Zeitschrift für Differ und Diagnostische Psychol. 2003;24:37.
125. Schwarzer R. Skalen zur Erfassung von Lehrer- und
Schülermerkmalen: Dokumentation der psychometrischen
Verfahren im Rahmen der wissenschaftlichen Begleitung des
Modellversuchs Selbstwirksame Schulen. Berlin: Freie
Universität Berlin; 1999.
126. Carver CS. You want to measure coping but your protocoltoo
long: consider the brief cope. Int J Behav Med. 1997;4:92100.
127. McMahon EM, Corcoran P, McAuliffe C, Keeley H, Perry IJ,
Arensman E. Mediating effects of coping style on associations
between mental health factors and self-harm among adolescents.
Crisis. 2013;34:24250.
128. Buckner JD, Zvolensky MJ, Farris SG, Hogan J. Social anxiety
and coping motives for cannabis use: the impact of experiential
avoidance. Psychol Addict Behav. 2014;28:56874.
129. Gregg L, Haddock G, Emsley R, Barrowclough C. Reasons
for substance use and their relationship to subclinical psy-
chotic and affective symptoms, coping, and substance use
Curr Addict Rep (2019) 6:383401
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
in a nonclinical sample. Psychol Addict Behav. 2014;28:
130. Müller M, Montag C. The relationship between internet addiction
and alcohol consumption is influenced by the smoking status in
male online video gamers. Clin Neuropsychiatry. 2017;14:3443.
131. Tavolacci MP, Ladner J, Grigioni S, Richard L, Villet H,
Dechelotte P. Prevalence and association of perceived stress, sub-
stance use and behavioral addictions: a cross-sectional study
among university students in France, 2009-2011. BMC Public
Health. 2013;13.
132. Smith JL, Mattick RP, Jamadar SD, Iredale JM. Deficits in behav-
ioural inhibition in substance abuse and addiction: a meta-analysis.
Drug Alcohol Depend. 2014;145:133.
133. Griffiths M, Sutherland I. Adolescent gambling and drug use. J
Community Appl Soc Psychol. 1998;8:4237.
134. Griffiths M, Parke J, Wood R. Excessive gambling and substance
abuse: is there a relationship? J Subst Use. 2002;7:18790.
135. Starcevic V, Khazaal Y. Relationships between behavioural addic-
tions and psychiatric disorders: what is known and what is yet to
be learned? Front Psychiatry. 2017;8:53.
136. Dance A. Smart drugs: a dose of intelligence. Nature. 2016;531:
137. Goudriaan AE, Oosterlaan J, de Beurs E, van den Brink W.
Psychophysiological determinants and concomitants of deficient
decision making in pathological gamblers. Drug Alcohol Depend.
138. Cunningham-Williams RM, Cottler LB, Compton WM,
Spitznagel EL, Ben-Abdallah A. Problem gambling and comor-
bid psychiatric and substance use disorders among drug users
recruited from drug treatment and community settings. J Gambl
Stud. 2000;16:34776.
139. Bibbey A, Phillips AC, Ginty AT, Carroll D. Problematic internet
use, excessive alcohol consumption, their comorbidity and cardio-
vascular and cortisol reactions to acute psychological stress in a
student population. J Behav Addict. 2015;4:4452.
140. Tsai J, Huh J, Idrisov B, Galimov A, Espada JP, Gonzálvez MT,
et al. Prevalence and co-occurrence of addictive behaviors among
russian and spanish youth. J Drug Educ. 2016;46:3246.
141. Liew LWL, Stavropoulos V, Adams BLM, Burleigh TL, Griffiths
MD. Internet gaming disorder: the interplay between physical ac-
tivity and useravatar relationship. Behav Inf Technol. 2018;37:
142. Khantzian EJ. The self medication hypothesis of addictive disor-
ders: focus on heroin and cocaine dependence. Am J Psychiatry.
143. Senormanci O, Konkan R, Guclu O, Senormanci G. Evaluation of
coping strategies of male patients, being treated in internet addic-
tion outpatient clinic in Turkey. J Mood Disord. 2014;4:14.
144. Tang J, Yu Y, Du Y, Ma Y, Zhang D, Wang J. Prevalence of
internet addiction and its association with stressful life events
and psychological symptoms among adolescent internet users.
Addict Behav. 2014;39:7447.
145. Kuss D, Dunn TJ, Wölfling K, Müller KW, H dzelek M,
Marcinkowski J. Excessive internet use and psychopathology:
the role of coping. Clin Neuropsychiatry. 2017;14:7381.
146. Estévez A, Herrero D, Sarabia I, Jáuregui P. El papel mediador de
la regulación emocional entre el juego patológico, uso abusivo de
Internet y videojuegos y la sintomatología disfuncional en jóvenes
y adolescentes. Adicciones. 2014;26:28290.
147. Schreiber LRN, Grant JE, Odlaug BL. Emotion regulation and
impulsivity in young adults. J Psychiatr Res. 2012;46:6518.
148. Aldao A, Nolen-Hoeksema S, Schweizer S. Emotion-regulation
strategies across psychopathology: a meta-analytic review. Clin
Psychol Rev. 2010;30:21737.
149. Malik S, Wells A, Wittkowski A. Emotion regulation as a mediator
in the relationship between attachment and depressive symptomatol-
ogy: a systematic review. J Affect Disord. 2015;172:42844.
150. Vollmer C, Randler C, Horzum MB, Ayas T. Computer game
addiction in adolescents and its relationship to chronotype and
personality. SAGE Open. 2014;4:215824401351805.
151. Andreassen C, Griffiths MD, Hetland J, Pallesen S. Development
of a work addiction scale. Scand J Psychol. 2012;53:26572.
152. Lee D, Kelly KR, Edwards JK. A closer look at the relationships
among trait procrastination, neuroticism, and conscientiousness.
Pers Individ Dif. 2006;40:2737.
153. Wang C-C, Yang H-W. Passion for online shopping: the influence
of personality and compulsive buying. Soc Behav Personal an Int
J. 2008;36:693706.
154. Verplanken B, Herabadi A. Individual differences in impulse buy-
ing tendency: feeling and no thinking. Eur J Pers. 2001;15:S71
155. Di Nicola M, Tedeschi D, De Risio L, et al. Co-occurrence of
alcohol use disorder and behavioral addictions: relevance of im-
pulsivity and craving. Drug Alcohol Depend. 2015;148:11825.
156. Kuss D, Griffiths M, Karila L, Billieux J. Internet addiction: a
systematic review of epidemiological research for the last decade.
Curr Pharm Des. 2014;20:402652.
157. Yakovenko I, Hodgins DC. A scoping review of co-morbidity in
individuals with disordered gambling. Int Gambl Stud. 2018;18:
158. Winkler A, Dörsing B, Rief W, Shen Y, Glombiewski JA.
Treatment of internet addiction: a meta-analysis. Clin Psychol
Rev. 2013;33:31729.
159. Szerman N, Martinez-Raga J, Peris L, Roncero C, Basurte I, Vega
P, et al. Rethinking dual disorders/pathology. Addict Disord Their
Treat. 2013;12:110.
160. Ruiz P. Dual disorders: a worldwide perspective. Addict Disord
Their Treat. 2017;16:1514.
161. Kalina K, Vacha P. Dual diagnoses in therapeutic communities for
addicts: possibilities and limits of integrated treatment.
Adiktologie. 2013;13:14464.
162. Cleary M, Hunt GE, Matheson S, Walter G. Psychosocial treat-
ments for people with co-occurring severe mental illness and sub-
stance misuse: systematic review. J Adv Nurs. 2009;65:23858.
163. Grant BF, Goldstein RB, Saha TD, et al. Epidemiology of DSM-5
alcohol use disorder. JAMA Psychiatry. 2015;72:757.
164. Roncero C, Grau-López L, Casas M. Dual disorders. Addict
Disord Their Treat. 2017;16:1759.
165. Carrà G, Bartoli F, Brambilla G, Crocamo C, Clerici M. Comorbid
addiction and major mental illness in Europe: a narrative eeview.
Subst Abus. 2015;36:7581.
166. Gossop M, Marsden J, Stewart D. Dual dependence: assessment of
dependence upon alcohol and illicit drugs, and the relationship of
alcohol dependence among drug misusers to patterns of drinking,
illicit drug use and health problems. Addiction. 2002;97:16978.
167. Staiger PK, Richardson B, Long CM, Carr V, Marlatt GA.
Overlooked and underestimated? Problematic alcohol use in cli-
ents recovering from drug dependence. Addiction. 2013;108:
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... Similar applies to other potential addictive behaviors on the Internet, such as the problematic use of online pornography, social networks, or online shopping. These problematic online behaviors may occur together with gaming disorder (Burleigh, Griffiths, Sumich, Stavropoulos, & Kuss, 2019;, but may also be an own entity. Recent theoretical frameworks such as the Interaction of Person-Affect-Cognition-Execution (I-PACE) model (Brand, Young, Laier, Wölfling, & Potenza, 2016; assume that similar psychological processes underlie the different types of (online) addictive behaviors. ...
... Furthermore, some specific Internet-use disorders seem likely to co-occur, especially disordered gaming and socialnetworks use (Burleigh et al., 2019;. Using latent profile analysis, Charzy nska, Sussman, and Atroszko (2021) identified that disordered social-networking and shopping as well as disordered gaming and pornography use often occurred together respectively. ...
... Studies suggest well-being to be particularly impaired when multiple specific Internet-use disorders cooccur (Charzy nska et al., 2021). The joint occurrence of specific Internet-use disorders is not infrequent (e.g., Burleigh et al., 2019; which may partly explain the relatively high intercorrelations between the disorders measured by ACSID-11 and IGDT-10 respectively. This underscores the importance of a uniform screening tool to determine commonalities and differences more validly across different types of disorders due to addictive behaviors. ...
Full-text available
Background and aims With the inclusion of gaming disorder in the ICD-11, diagnostic criteria were introduced for this relatively new disorder. These criteria may also be applied to other potential specific Internet-use disorders, which may be classified in ICD-11 as other disorders due to addictive behaviors, such as online buying-shopping disorder, online pornography-use disorder, social-networks-use disorder, and online gambling disorder. Due to the heterogeneity in existing instruments, we aimed to develop a consistent and economic measure of major types of (potential) specific Internet-use disorders based on ICD-11 criteria for gaming disorder. Methods The new 11-item Assessment of Criteria for Specific Internet-use Disorders (ACSID-11) measures five behavioral addictions with the same set of items by following the principles of WHO’s ASSIST. The ACSID-11 was administered to active Internet users ( N = 985) together with an adaptation of the Ten-Item Internet Gaming Disorder Test (IGDT-10) and screeners for mental health. We used Confirmatory Factor Analyses to analyze the factor structure of ACSID-11. Results The assumed four-factorial structure was confirmed and was superior to the unidimensional solution. This applied to gaming disorder and to the other specific Internet-use disorders. ACSID-11 scores correlated with IGDT-10 as well as with the measures of psychological distress. Discussion and Conclusions The ACSID-11 seems to be suitable for the consistent assessment of (potential) specific Internet-use disorders based on ICD-11 diagnostic criteria for gaming disorder. The ACSID-11 may be a useful and economic instrument for studying various behavioral addictions with the same items and improving comparability.
... These behaviours may demonstrate features of typical addictive behaviours like constant preoccupation, loss of control, high intensity and frequency, and continuation or escalation of the behaviour despite the occurrence of negative consequences and cause significant distress and impairment to an individual's overall functioning [5]. These behaviours are often interwoven and may feed each other [6,7]. Due to the rapid development of technology, it has been suggested that excessive use of social media may have characteristics similar to excessive (or addiction-like) behaviours associated with gambling and gaming, thus potentially posing a risk for important areas of functioning among adolescents [8]. ...
... Substance use has been linked to gambling and gaming in many studies [6,27]. There is also clear evidence that adolescents whose parents are aware of their whereabouts and activities are less likely to participate in risky behaviours [28][29][30]. ...
... The co-occurrence of behavioural and substance addictions has been noted [6]. Also, having a behavioural addiction increases the probability of developing other behavioural addictions [48]. ...
Full-text available
Purpose: Adolescents' excessive social media use has characteristics similar to other addictive behaviours. This study aims to explore whether the same risk factors are associated with excessive social media use as with excessive gaming and gambling among Finnish adolescents. Methods: Multinomial logistic regression analyses were carried out using the European School Survey Project on Alcohol and Other Drugs data, collected from Finnish adolescents aged 15-16 in 2019 (n = 4595). Results: Excessive use of social media was more common among girls (reported by 46% of respondents) than boys of the same age (28%), whereas boys reported both excessive gaming (23%) and gambling (6%) more often than girls (4% and 1%, respectively). All differences between genders were statistically significant (p < 0.0001). Daily smoking was associated with a high risk of excessive gambling (AOR = 3.23) and low risk of excessive gaming (AOR = 0.27) but had no significant effect on excessive social media use. Cannabis use in the past 12 months was positively associated only with excessive gambling (AOR = 2.39), while past 12 months alcohol consumption increased the risk for excessive social media use (AOR = 1.25). Conclusions: Adolescent girls are at greater risk of excessive social media use than boys, while boys are at greater risk of excessive gaming and gambling. The associations with known risk factors are somewhat different for excessive use of social media as compared to excessive gambling and gaming and should be acknowledged when developing preventive measures for adolescents.
... The last 20 years saw a paradigm shift in the conceptualization of addiction, suggesting that addictive behaviors can take place in alternative realms which may not necessarily involve the use of substances (i. e., behavioral addictions; APA, 2013; Burleigh et al., 2019;Demetrovics & Griffiths, 2012;Griffiths, 1996;Griffiths, 2005;Griffiths, 2017;Kardefelt-Winther et al., 2017;Sixto-Costoya et al., 2021;West & Brown, 2013;Wong et al., 2012). These include a range of diverse behaviors such as excessive online gambling (Griffiths, 1995;Montiel et al., 2021), hypersexual activity (Carnes, 1983;Krueger, 2016), problematic internet use (Anderson et al., 2017;Stavropoulos et al., 2013;Van Rooij et al., 2017), disordered gaming Stavropoulos et al., 2019), problematic social media use (Pontes et al., 2018;Schivinski et al., 2020), compulsive shopping (Andreassen et al., 2015;Müller et al., 2021), and problematic exercising (Beck Lichtenstein & Jensen, 2016;Beck Lichtenstein et al., 2017). ...
... Indeed, research supports that predisposing factors such as depression (Xu et al., 2020), anxiety , maladaptive strategies (Ostovar et al., 2021), and adverse life experiences (Farré et al., 2015), may act as antecedents leading to the development and maintenance of co-occurring addictive behaviors (see also the I-PACE model explaining the rise of addictive behaviors, in particular in the online realm; Brand et al., 2016Brand et al., , 2019. Similarly, evidence indicates that commonalities across forms of addictions might act as a 'gateway' increasing the likelihood of comorbid addictions (Burleigh et al., 2019;Rozgonjuk et al., 2021). For example, Delfabbro and King (2020) suggest that the 'digital convergence' of certain online activities facilitates the comorbid presentations of addictions in online environments (i.e., gambling, gaming, disordered internet use, etc.). ...
... Additionally, empirical evidence suggests that common elements across different symptoms of addiction may increase the likelihood of developing cross-addictive behaviours in two important ways (Ford & Håkansson, 2020;Fuss et al., 2019;Tang et al., 2020). Firstly, common elements may facilitate a cycle of reciprocity, exacerbating the risk of transitioning from one addictive behavior to another (e.g., one abuses alcohol and while drinking progressively develops disordered gaming behaviors; Burleigh et al., 2019). Secondly, individuals may seek gratification through alternative addictive behaviors while aiming to disengage from a previously established addiction (e.g., drug abusers may substitute their use of substances with alcohol while aiming to abstain from the first; Brown et al., 2021;Haylett et al., 2004). ...
Full-text available
Background Common elements across different forms of addiction suggest the possibility of comorbid addictions, as well as the transition/replacement of one form of addiction with another. This study aimed to conduct a Network analysis of symptoms of 10 forms of addictive behaviors to examine their behavioral commonalities/ interrelations. Methods: To address this aim, an online community sample of 968 adult participants (33.6% women, 66.4% men) completed self-rating questionnaires covering a range of addictive behaviors including alcohol, drugs, tobacco, sex, online gambling, internet use, internet gaming, social media use, shopping, and exercise. Their responses were examined with regularized partial correlation network analysis (EBICglasso) and a community detection algorithm (Walktrap) to identify: (a) specific links between neighboring forms of addiction; and (b) clustering of symptoms of addiction. Results: Findings showed positive network connections across different addictive behaviors, with addictive tendencies towards gambling showing the highest centrality, sequentially followed by addictive tendencies towards internet use, internet gaming, alcohol, shopping, social media use, drugs, sex, smoking, and exercise. Conclusion: Symptoms associated with disordered drug use and gambling are suggested to maintain severity of addictive disorders and increase the likelihood of developing cross addictive behaviors. Clinical implications for the assessment and treatment of addiction comorbidities and the replacement of one form of addiction with another are discussed considering these findings. Keywords Neighboring addictionCross addictionAddiction taxonomyNetwork Analysis
... On a different note, IGD is often associated with various substance use disorders. For example, a recent review suggested that adults with disordered gaming frequently show problematic or disordered substance use [28]. In addition, several studies analyzing neuroanatomical changes in the brain, including reward and executive functioning mechanisms, have reported similar changes in both IGD and substance use [24,[29][30][31][32]. ...
... Despite the general contributing factors to IGD symptomatology, we observed that IGD symptoms were differently affected by various substance use in males and females. The general association of IGD and substance use is in line with a recent review [28], which concluded that many of the problematic behaviors co-occurring with disordered gaming can be performed concurrently with problematic gaming, potentially as part of a coping strategy [45]. Unique associations between various substance use, psychological symptoms, and IGD found in our study for males and females might indicate possible gender-specific predisposition, coping strategies, or vulnerabilities, what may be used in therapeutic approaches to tackle IGD symptom severity as gender specific. ...
Full-text available
Background Problematic Internet gaming is an increasingly recognized global mental health problem. This multicultural cross-sectional study examined the association between Internet gaming disorder (IGD) symptoms and anxiety and depressive symptoms and substance use within a sample of young Internet users. In total, 3529 college/university students (1260 (35.7%) males; mean age 21 ± 3 years) were surveyed online. We assessed online gaming patterns using the Internet Gaming Disorder Self-report for College/University Students (ICMH-IGD), symptoms of depression using the Patient Health Questionnaire-9, and symptoms of anxiety using the Generalized Anxiety Disorder scale-7. Results IGD symptoms were associated with symptoms of depression, anxiety, and substance use, independent of time spent online, psychiatric diagnosis, culture, or sociodemographic characteristics. For males, more significant IGD symptoms were associated with more extended Internet browsing per day time and higher levels of anxiety and depressive symptoms, while for females, with more extended Internet browsing per day time, marihuana use, and higher levels of depressive symptoms. Conclusions Our study found that more overt symptoms of IGD were associated with higher levels of anxiety and depressive symptoms and substance use. Still, these associations differed among males and females, suggesting that gender differences should be considered when planning specific treatments.
... Neuroimaging studies support the similarities of problematic gaming with substance-related addictions at different levels (Han et al., 2016). Research has demonstrated significant associations between problematic gaming behaviors and depression (Brunborg et al., 2014), anxiety (Bonnaire & Baptista, 2019), and sleep disturbance (Burleigh et al., 2019;Lam, 2014). However, there is only limited empirical evidence as to whether GD is the cause or just the consequence of such psychopathologies (González-Bueso et al., 2018). ...
... More specifically, young adults who experience high levels of daily stress and miss social support in the offline world engage in intensive use of digital media, and online social support can contribute to the development of addictive behaviors that decrease well-being . Moreover, problematic gaming behavior has been reported to be associated with lower levels of life satisfaction and with higher levels of loneliness, depression, anxiety, and other addictive tendencies (Burleigh et al., 2019;Király et al., 2015). ...
Full-text available
Problematic gaming has become an emerging global health issue. Formal recognition of gaming disorder in the ICD-11 is a new opportunity for the discipline to conduct further investigation concerning the psychological consequences of problematic gaming. The present study investigated the psychometric properties and construct structure of the recently developed Gaming Disorder for Scale for Adolescents (GADIS-A), a multi-dimensional instrument that screens for gaming disorder symptoms, among Russian adolescent gamers. The sample comprised 933 adolescent gamers (547 boys and 386 girls) recruited via a web-based platform, using a multistage sampling method. Analysis showed the GADIS-A had very good internal consistency (Cronbach's alpha coefficient = .891; Composite reliability = .89) and adequate test-retest reliability after two weeks (intraclass coefficient =0.68 with 95% CI [0.61, 0.77]. Exploratory structural equation modeling (ESEM) showed the data fitted well. Measurement invariance testing indicated the GADIS-A was invariant by gender and gaming medium (online vs. offline). As for criterion-related validity, high scores on the GADIS-A positively correlated with scales assessing depression, anxiety, impulsivity, and difficulties in emotion regulation, and negatively correlated with social connectedness and life satisfaction. Using latent profile analysis, four groups of gamers were identified, and problematic gaming was associated with greater mental health problems. The findings indicated that psychological comorbidity (e.g., depression and anxiety) was more prevalent among gamers with higher risk of GD. The findings indicate that GADIS-A is a reliable and valid instrument to assess the symptoms and severity of gaming disorder among Russian adolescents. Supplementary information: The online version contains supplementary material available at 10.1007/s12144-021-02575-w.
... Age and monthly household income were adjusted due to the differences of age and family economic status in screen media use (Long et al., 2018;Luk et al., 2018) and sleep problems (Lallukka et al., 2012;Sivertsen et al., 2009). We included alcohol drinking as a covariate as drinkers were more likely to have high screen media use (Burleigh et al., 2019;Luk et al., 2018) and sleep problems (Huang et al., 2013). Given few participants reported smoking and gambling, the two variables were not included as covariates to avoid sparse data bias. ...
Objectives To explore associations of screen time (total, mobile gaming) with sleep problems in Chinese young adults. Methods This was a 4-week daily morning (completion rate=82.1%, 909/1107) and evening (completion rate=92.4%, 1061/1148) assessment study in 41 university students (22 female, mean age=22.3 [SD 4.2] years). Short sleep duration<7 hours, difficulty initiating sleep, difficulty maintaining sleep, early morning awakening, and any of these three insomnia symptoms were self-reported in the morning. Mobile gaming time was self-reported in the evening, whilst total screen time was objectively tracked. Bayesian multilevel mixed-effects modeling disaggregated between- and within-person associations. Results Between person, longer mobile gaming time predicted short sleep duration (adjusted odds ratio [AOR]=1.90, 95% CI 1.39, 2.69), any insomnia symptoms (AOR=1.59, 95% CI 1.20, 2.11), difficulty initiating sleep (AOR=3.05, 95% CI 1.51, 6.24), and difficulty maintaining sleep (AOR=2.19, 95% CI 1.18, 3.74). Short sleep duration (adjusted b=0.99, 95% CI 0.05, 1.95), any insomnia symptoms (adjusted b=1.19, 95% CI 0.24, 1.94), and difficulty initiating sleep (adjusted b=1.72, 95% CI 0.11, 3.19) reversely increased mobile gaming time. Within person, any insomnia symptoms (adjusted b=0.17, 95% CI 0.04, 0.31) and early morning awakening (adjusted b=0.28, 95% CI 0.08, 0.48) increased next-day mobile gaming time. Total screen time was not associated with sleep problems both between and within person. Conclusions Bidirectional between-person associations of mobile gaming time with short sleep duration and insomnia symptoms informed multiple-health-behavior-change interventions. Unidirectional within-person associations of insomnia symptoms with next-day mobile gaming time informed just-in-time adaptive interventions addressing daily variations in insomnia symptoms. [250/250 word limits]
... A survey of college students revealed that the sharing behaviors on social media were similar to self-promotion and peer promotion of alcohol use [38]. Gaming disorder can co-occur with a variety of other addictive behaviors such as alcohol use and the addictive use of social media [39]. Research investigating the co-occurrence of addictive behaviors and substance use is increasing. ...
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Addiction in adolescence is increasing and has a significant impact on physical and mental health. Notably, addictions can be comorbid and affect each other. Despite the recent growing interest in food addiction (FA) and problematic smartphone use (PSU), few studies have investigated their association in adolescents. We investigated the relationship between FA and PSU in adolescents and the effects of eating behaviors. A total of 209 adolescents (44.5% male; mean age = 12.86 ± 0.7 years) participated in the current school-based community study. We found a positive correlation between the dimensional Yale Food Addiction Scale for Children 2.0 (dYFAS-C2.0) and the Smartphone Overdependence Scale after adjusting for age, sex, body mass index, and socioeconomic status. The high-risk PSU group accounted for 17.2% of participants. Furthermore, this group showed 2.3 times higher dYFAS-C2.0 scores than the general group. Emotional overeating and satiety responsiveness were correlated with PSU. A comprehensive evaluation of addiction symptoms is needed for proper intervention, especially in adolescents with symptoms of abnormal eating behaviors.
... This may explain why total anxiety score and physiological anxiety were both positively correlated with IGD. It has also been shown that social anxiety is a risk factor for the development and continuation of IGD (55)(56)(57). Another study reported a positive two-way relationship between Internet gaming and social anxiety (58). It may be that individuals who are reluctant to communicate with others due to social anxiety participate in games to meet their social needs to a certain extent. ...
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Background Internet gaming disorder (IGD) has become a serious public health problem in East Asia, and studies have reported IGD to be significantly associated with anxiety, but no causal relationship between the two has yet been demonstrated. Children are at high risk of developing IGD, however, previous studies have principally focused on the condition in adults and adolescents and reported non-clinical samples. A large-scale survey is needed to research and evaluate IGD and anxiety in children and adolescents to understand the current situation of IGD in children and explore the impact of IGD on anxiety. Methods A cross-sectional study using an online questionnaire was conducted between March 1 and July 31, 2021. A total of 10,479 school children and adolescents in the western provinces of China were selected by convenience sampling. A questionnaire was used to collect data anonymously. The questionnaire covered IGD and the Revised Children's Manifest Anxiety Scale (RCMAS). Welch's ANOVA Test and Games-Howell test were used to test for differences in anxiety levels between IGD groups. Poisson regression analysis was used to further investigate the key predictors of IGD. Results 3.2% of participants ( n = 334) (95% CI: 2.9–3.2%) were classified as at high risk of presenting with IGD, 71.1% ( n = 7,454) (95% CI: 70.3–72.0%) were classified as low-risk players, and 25.7% ( n = 2,691) (95% CI: 24.9–26.5%) were classified as non-gaming. The average RCMAS score was (7.18 ± 7.534). The high-risk group had a higher total score RCMAS, as well as scoring higher in its three dimensions. Regression analysis using gender, age, and total RCMAS score as independent variables, and risk of IGD as a dependent variable showed that the odds ratio (OR) for gender was 2.864 (95% CI: 2.267–3.618), and the OR for total RCMAS score was 1.101 (95% CI: 1.087–1.114). The OR for age was not statistically significant. Conclusion Anxiety was a predictor of IGD, with statistically significant group differences in total anxiety, as well as the dimensions of physiological anxiety, social correlation, and sensitivity. The timely assessment of anxiety in children and adolescents, training social skills, and facilitating effective integration into society could be effective ways of reducing the incidence and impact of IGD.
... 3% estimated by two recent meta-analyses (Stevens et al., 2020;Kim et al., 2021) potentially constitute 200 million of people playing pathologically. Over just a few years during which both internet gaming disorder, IGD (APA, 2013) and gaming disorder, GD (WHO, 2019) were officially introduced, a large amount of evidence in a form of associations between IGD or GD and different psychological, socioeconomic, gaming or other phenomena, has been accumulated Paulus et al., 2018;Burleigh et al., 2019). Inclusion of GD into the 11th revision of the International Classification of Diseases (WHO, 2019) is therefore justified not only from the clinical perspective and public health needs (Rumpf et al., 2018) but also based on extensive longitudinal evidence on the negative consequences (e.g., increased anxiety, depression, loneliness, or emotional distress, and decreased life satisfaction, school performance, poor relationship with parents, or social competence) (Richard et al., 2020). ...
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Background: This large-scale meta-analysis aimed to provide the most comprehensive synthesis to date of the available evidence on risk and protective factors for (internet) gaming disorder (as defined in the DSM-5 or ICD-11) across all studied populations.Methods: The risk/protective factors included demographic characteristics, psychological, psychopathological, social, and gaming-related factors. In total, we have included 1578 effects from 250 different studies, summarizing data from 206690 participants. Apart from estimating these predictive associations and relevant moderating effects, we implemented state-of-the-art adjustments for publication bias, psychometric artifacts, and other forms of bias arising from the publication process. Additionally, we carried out an in-depth assessment of the quality of underlying evidence by examining indications of selective reporting, statistical inconsistencies, the typical power of utilized study designs to detect theoretically relevant effects, and performed various sensitivity analyses.Results: The available evidence suggests the existence of numerous moderately strong and highly heterogeneous risk factors but only a few empirically robust protective factors (all having markedly smaller effect sizes).Conclusions: We discuss the theoretical implications of our results for prominent theoretical models of gaming disorder and for the existing and future prevention strategies. The impact of various examined biasing factors on the available evidence seemed to be modest, yet we identified shortcomings in the measurement and reporting practices.Registration number: Preregistered at PROSPERO under ID:CRD42020187776.
Problematic internet use (PIU) is more common in young adult populations than any other adult age group. Previous research has suggested that PIU is associated with higher rates of mental health disorders, psychological distress, and some substance misuse behaviors in college students. This study utilizes data from 417,780 US college students to explore associations between PIU and a variety of substance use outcomes. Unadjusted and adjusted odds ratios were used to investigate associations between PIU and substance use disorder (SUD) diagnosis, misuse of cigarettes, e-cigarettes, alcohol, marijuana, cocaine/methamphetamine, sedatives, hallucinogens, opiates, inhalants, MDMA, other club drugs, prescription pain killers, prescription sedatives, and prescription stimulants. Among the 417,780 US college students included in our analytic cohort, 123,330 (29.52%) reported PIU. Students who demonstrated PIU had a significantly higher risk of substance misuse behaviors, including misuse of opiate, sedative, hallucinogen, club drugs, and inhalant, illicit use of prescription pain killers, and SUD diagnosis, than their peers who did not demonstrate patterns of PIU. These findings highlight the need to promote the physical, social, and emotional wellbeing of students more effectively by considering PIU in prevention and intervention efforts aimed to decrease the prevalence of addictive behaviors in US college settings.
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Eine deutsche Fassung der revidierten UCLA Loneliness Scale (Russell et al., 1980) wurde einer repräsentativen gesamtdeutschen Stichprobe (N = 592) vorgelegt. Testkennwerte wie interne Konsistenz (ex= .89) und mittlerer Trennschärfenindex (ru = .51) sind zufriedenstellend und replizieren frühere Befunde deutscher Über­setzungen des Fragebogens. Westdeutsche Untersuchungsteilnehmer (M = 1.84) haben signifikant höhere Einsamkeitswerte als ostdeutsche (M = 1.58). Die Skala enthält drei Dimensionen, die signifikant zwischen Einsamen und weniger Einsamen differenzieren und die sich als „Einsamkeitsgefühle", ,,wahrgenommene emotionale Isolation" und „wahrgenommene soziale Isolation" interpretieren lassen. Vergleiche soziodemographischer Subgruppen liefern Belege zur Validität der Skala und ihrer Dimensionen. A German adaptation of the revised UCLA Loneliness Scale (Russell et al., 1980) was assessed in a representative sample of 592 subjects in East and West Germany. Psychometrie characteristics of the scale like internal consistency (ex= .89) and mean item-total score correlation (r;, = .51) were found to be satisfactory and repli­cate results of earlier research of German questionnaire translations. Participants from West Germany score significantly higher (M = 1.84) on loneliness than those from East Germany (M= 1.58). Factor analysis yieldes three dimensions of the scale, labeled and explained in terms of „feelings of loneliness", ,,perceived emotional iso­lation", and „perceived social isolation". All lhree factors discriminate significantly between the lonely and the not-so-lonely. Comparisons of sociodemographic sub­groups provide evidence supporting the validity of the scale and its dimensions.
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The current study aimed to investigate associations between gaming and different patterns of problematic alcohol use, controlling for important demographics, personality and mental health covariates. Data was collected by an online survey during fall 2016 (N = 5217). Students who had participated in a survey among students in Bergen, Norway, one year earlier were invited to participate. Crude and adjusted binary logistic regression analyses were conducted in order to assess the relationship between different patterns of problematic alcohol use and gaming (i.e. low-level gaming and high-level gaming vs. no gaming) while controlling for important covariates. The different gaming groups were categorised based on the number of symptoms of “gaming addiction” (in total seven) that they endorsed: 4 > symptoms = low-level gaming, 4 ≤ symptoms = high-level gaming. Only 0.2% (n = 11) endorsed all seven symptoms. Low-level gaming was positively associated with patterns of problematic alcohol use in the crude analyses; these associations became non-significant when controlling for demographic variables. High-level gaming was inversely associated with patterns of problematic alcohol use when controlling for demographics, personality, and mental health covariates. The inverse relationship between high-level gaming and problematic alcohol use (when controlling for covariates) suggest that heavy investment in gaming may protect against excessive alcohol use and alcohol-related harm. Possible explanations discussed for the inverse associations include high-level gamers having less available time to drink, intoxication being incompatible with gaming, and/or high-level gamers experiencing sufficient satisfaction/escape and social bonding by gaming, hence having less need for alcohol.