Introduction

“Impulsivity is an aspect of behaviour which adds important colour to everyday life.” (Evenden, 1999 [1 p.348]).

Impulsivity has been defined in various ways as a tendency to perform actions that appear rash, hastily expressed, overly risky, or inappropriate to the situation [2]. Impulsivity is a multifaceted construct. It refers to a variety of related aspects leading to different forms of impulsive behaviors [1], which may lead to undesirable consequences [2]. A heightened tendency towards impulsive responding is evident in various psychiatric disorders such as Attention Deficit Hyperactivity Disorder (ADHD), Obsessive–Compulsive Disorder (OCD), substance-use disorders, and behavioral addictions [3,4,5,6]. Thus, impulsivity is a transdiagnostic construct and a key component of both substance-related and non-substance-related addictive behaviors [7••]. The construct has been much discussed in the context of theories of the development and maintenance of addictive behaviors (e.g. [8,9,10,11]); however, the exact neurocognitive processes are not yet clear [12•].

In this review, we will have a closer look at impulsivity in the context of gaming disorder. First, we will introduce impulsivity and its various facets as defined by different researchers. Based on the overlaps between previous definitions and used measures, we identify three main facets of impulsivity, namely motor, attentional, and decisional impulsivity. Second, we will describe mechanisms involved in the development and maintenance of gaming disorder with a special focus on mechanisms that involve facets of impulsivity. Then, we will summarize findings on associations between gaming disorder and the three main facets of impulsivity assessed by self-report and behavioral measures. For this purpose, we reviewed comprehensively the existing literature on empirical findings regarding impulsivity in gaming disorder. Therefore, we searched several databases including Google Scholar, PubMed, and Scopus for articles (reviews, meta-analyses, and original studies) published on the topic in international peer-reviewed journals. We focused on literature published within the past 5 years; however, we also refer to some older sources that seem to be particularly significant in the respective context.

Facets of Impulsivity

There is a scientific consensus that impulsivity is a multifaceted construct. Nevertheless, impulsivity is among the psychological and neuroscientific constructs that have been defined in multiple partly disjunctive and partly overlapping manners. One consensus is that impulsive behavior is not per se disadvantageous but may have many adaptive features, which may explain why impulsive behavioral traits have persisted throughout evolutionary history [1]. However, impulsive behavior may also become dysfunctional, which can, according to Dickman [13], be divided into at least three separable sub-dimensions: attentional impulsivity (resulting from insufficient focusing of attention), reflection impulsivity (acting immediately on first impressions), and disinhibition (failure to inhibit responses). A work by Barratt, Patton [14] identified three dimensions of (dysfunctional) impulsive traits: motor (i.e., acting without thinking), attentional (lack of attention focus), and non-planning (lack of foresight/ future orientation). These dimensions are captured by the widely used Barratt Impulsiveness Scale (BIS-11 [15]). Impulsivity has also been considered the opposite of self-control and as such representing striving for immediate reward and problems to delay gratification (e.g. [16]). Using factor analysis on frequently used measures of impulsivity, Whiteside, Lynam [17] identified four factors: urgency, (lack of) premeditation, (lack of) perseverance, and sensation seeking, which are captured by the UPPS Impulsivity Scale. Urgency describes the tendency to act rashly under conditions of strong (negative) affect despite potential negative long-term consequences (associated with problems to resist temptations). The UPPS, with urgency originally related only to negative affect, was later extended to additionally capture “positive urgency” referring to the tendency to act impulsively in response to being in a positive affective state [18]. Lack of premeditation refers to difficulties in thinking/reflecting on the possible consequences before acting (impulse control problems). Lack of perseverance describes difficulties in staying focused to complete a task (attentional problems). The last factor, called sensation seeking, refers to the tendency to engage in activities that are particularly exciting or dangerous. This is a slightly different component compared to the previous facets of impulsivity, which alludes to the urge to try new, exciting (adventurous) things in particular, well aware that they might be dangerous. Unlike other facets, sensation seeking is less about problems of resisting something or being able to stay with it but about (purposeful) seeking rewards and taking risks. This is similar to the “fun seeking” facet of a scale measuring sensitivity of the so-called Behavioral Inhibition System and Behavioral Activation System (BIS/BAS) [19]. The BAS is assumed to motivate responses towards rewarding stimuli and is assessed by three subscales: BAS drive (motivation to pursue goals), BAS reward responsiveness (tendency to respond with positive affect to potential future reward), and BAS fun seeking (tendency to quickly engage in potentially rewarding experiences). Especially, BAS fun seeking is assumed to involve elements of making impulsive decisions, while BAS drive may resemble motoric approach motivation (regardless of inherent pleasurability).

MacKillop et al. [20] identified three facets of impulsivity using structural equation modeling on diverse (behavioral) measures of impulsivity: impulsive choice (delay discounting measures, e.g., Monetary Choice Questionnaire), impulsive action (e.g., Go/No-Go task, Stop-Signal task), and impulsive personality traits (self-report scales such as BIS-11 and UPPS). Impulsive action parallels motor impulsivity while impulsive personality traits in turn comprise traits of different facets of impulsivity, which could be further differentiated. Based on existing cognitive tests, Fineberg et al. [21] defined an additional sub-type of impulsivity, named “disadvantageous decision making.” This facet refers to difficulties in weighing options which may result in unfavorably risky decision-making behavior as assessed by risky choice tasks (e.g., Iowa Gambling Task, Cambridge Gambling Task, Game of Dice Task).

In summary, impulsivity is a broad construct that can be divided into different sub-facets. The conceptualizations partly overlap and vary in the degree of detail and focus considered. Three main facets of impulsivity can be identified, for which the largest consensus in the theoretical conceptualizations and empirical findings can be defined: (1) motor impulsivity (also referred to as/ comprising: impulsive action, disinhibition, urgency, (lack of) premeditation), difficulties to inhibit motoric responses if required/ “acting without thinking,” (2) attentional impulsivity (also referred to as “(lack of) perseverance”), difficulties in focusing attention to task-relevant parameters, and (3) decisional impulsivity (also referred to as reflection impulsivity, choice impulsivity, non-planning impulsiveness) reflecting difficulties in gathering/weighing relevant information or reflecting on possible consequences before making a decision, which can manifest in overly risky/disadvantageous decision-making including high discounting of delayed rewards.

Various different types of measures are used to capture facets of impulsivity including self-report as well as behavioral measures, which refer to separate, partly independent sources of evidence. Self-report scales generally reflect more general, stable dispositions or personality traits. Behavioral measures capture the function of specific cognitive abilities in particular states and contexts and may include, on the one hand, general outcomes/ conditions, such as decisions regarding (virtual) monetary rewards or motor responses towards neutral stimuli, and, on the other hand, cue-related outcomes/ conditions which are specific to the domain/ behavior under study. The latter tasks aim to investigate (a) responses towards specific stimuli (in comparison to neutral stimuli), e.g., Go/No-Go tasks including gaming cues and neutral cues, or (b) whether presentation of (task irrelevant) specific stimuli leads to biases/ interference, e.g., Go/No-Go task with gaming pictures in the background of otherwise neutral target stimuli (e.g., geometric shapes). Consequently, cue-related tasks do not capture general but stimuli-specific impulsive tendencies which are not assessed by general self-report measures. Table 1 summarizes three main facets of impulsivity including exemplary measures.

Table 1 Different facets of impulsivity including definitions and exemplary measures
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We would like to note that there are many different approaches to subdivisions of the construct and its measures, some of which overlap. Depending on the level of detail of the different subprocesses, one can arrive at different classifications of the subfacets and methods. Existing definitions and cognitive measures of the multifaceted construct of impulsivity have been reviewed previously [21,22,23,24].

Research on addictive disorders has placed a strong focus on (reduced) inhibitory control of overt actions (i.e., motor impulsivity) [25]. In this review, we will have a closer look at gaming disorder and empirical results regarding measures of not only motor, but also attentional and decisional impulsivity.

Gaming Disorder

The use of the internet and specific online activities can, in some cases, lead to negative consequences and impairments in everyday life. Problematic use of the internet is a relevant and growing public health issue which may involve multiple facets [26•]. One of these facets is gaming disorder, which is one prominent subtype of addicitive behaviors within the complex phenomena subsumed under the umbrella term “problematic usage of the internet” [26•]. With the ICD-11, the World Health Organization has introduced an instrument that provides new structured diagnoses for gaming disorder and other addictive behaviors (e.g., gambling disorder) that can be specified as being performed predominantly online or offline. Gaming disorder is estimated to affect about 3% of the world’s (adolescent and adult) population, with significantly higher rates for male (6.31%) compared to female samples (2.54%) [27•]. Gaming disorder is defined as a persistent pattern of gaming behaviors (continuous or episodic) that manifests itself over a broader period of time (usually 12 months or longer). According to the ICD-11, it is characterized by the following diagnostic criteria:

  1. 1.

    Impaired control over gaming (onset, frequency, duration, stopping)

  2. 2.

    Increased priority given to gaming over other (daily) activities

  3. 3.

    Continuation or escalation of gaming despite negative consequences (e.g., family conflict, educational/professional difficulties, negative health outcomes)

  4. 4.

    Marked distress and/or functional impairment (e.g., in personal, family, social life)

Theoretically and empirically derived models (e.g., the Tripartite Neurocognitive Model of Internet Gaming Disorder; [28]) suggest that the development and maintenance of gaming disorder is characterized by (1) increased activity of an “impulsive” system, (2) decreased activity of a “reflective” system, resulting from/ aggravated by an (3) “interoceptive awareness” system. The interoceptive awareness system (associated with the insular cortex) is assumed to modulate the balance between the other two systems. Increasing imbalance, manifested by a tendency to react impulsively, may contribute to the maintenance of addictive behaviors. This is in accordance with other frameworks such as the Interaction of Person-Affect-Cognition-Execution (I-PACE) model [9], assuming that reinforcement and associative learning mechanisms as well as attentional and cognitive biases contribute to the development of cue-reactivity and craving when being confronted with specific triggers leading to “impulsive” behavioral enactment (despite negative consequences) especially when stimuli-specific inhibitory control is reduced. The model assumes interactions between affective and cognitive processes and predisposing (trait) variables [9], and both impulsivity and compulsivity are considered important [12•].

The different facets of impulsivity can be found at various points and causes of action within these models. For example (see Fig. 1), attentional impulsivity is represented by attentional biases which can promote cue-reactivity responses; motor impulsivity can be associated with reductions in (stimulus-specific) inhibitory control, fast responding, or (implicit) approach tendencies; and decisional impulsivity is associated with reduced reflection about options (probably accompanied by lower executive functioning) and altered reward expectancies. General (trait) impulsivity can be considered as a temperamental feature (belonging to a person’s core characteristics). Temperamental features affect the way an individual perceives and responds to stimuli in a specific situation. High predispositions to certain facets of impulsivity are likely to favor corresponding situation-/stimuli-specific impulsive reactions. For example, gamers with high levels of general motor impulsivity are probably more likely to have difficulties in inhibiting behavioral responses when confronted with stimuli related to gaming. However, with increasing symptom severity, increased stimuli-specific impulsivity can be assumed. This means, for example, that persons with tendencies towards gaming disorder do not necessarily have high general impulsivity to nevertheless show specific attentional biases towards gaming-related stimuli.

Fig. 1
figure 1

Illustration of the main components (later stages) of the I-PACE model [9] with additional highlighting of components that can be assigned to specific facets of motor impulsivity (red), attentional impulsivity (orange), and decisional impulsivity (blue)

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Impulsivity in Gaming Disorder

In the following, we will summarize the empirical evidence on impulsivity in gaming disorder individually for the three main facets of impulsivity (i.e., motor, attentional, and decisional impulsivity). For each facet, we distinguish between measures of general impulsivity (self-report and behavioral) and stimulus-specific impulsivity.

Evidence on overall associations between symptoms of gaming disorder measures of general impulsivity has been reviewed 4 years ago by Şalvarlı, Griffiths [29•]. They summarized 33 studies published between 2000 and 2019 that analyzed associations between general impulsivity measures (without focusing on specific sub-facets) and gaming disorder severity. Except one study [30], all other studies reported positive associations between impulsivity measures and gaming disorder. Most frequently used self-report measures were the BIS-11, the UPPS, and BIS/BAS (e.g. [31,32,33]), while main tasks included were the Stop-Signal Task, Go/No-Go task, and Delay Discounting tasks (e.g. [34,35,36,37]). A meta-analysis including 40 studies on problematic internet use (including gaming disorder) identified deficits in different cognitive domains including behavioral measures of impulsivity, such as Go/No-Go task, Stop-Signal Task, Stroop task, and different decision-making tasks [38]. The findings point at elevated motor impulsivity, attentional impulsivity, and decisional impulsivity in gaming disorder and general problematic internet use. Studies using the BIS-11 often reported the overall score only, indicating higher impulsivity in gaming disorder [32, 34, 39,40,41]. The broad variety of measures and different facets covered by them invites more detailed consideration. In this review, we examine the involvement of the multiple facets of impulsivity in gaming disorder by using the taxonomy of motor impulsivity, attentional impulsivity, and decisional impulsivity and, wherever possible, by separating general from stimuli-specific (gaming-related) impulsivity and distinguishing between self-report and behavioral measures.

Motor Impulsivity in Gaming Disorder

Difficulties in General Inhibitory Control

Self-Report Measures

Self-report measures of motor impulsivity reviewed here include BIS-11 motor, UPPS urgency, and BAS drive.

Findings on BIS-11 subscale-level indicate higher BIS-11 motor scores in individuals with gaming disorder compared to those without [33, 42, 43]. Furthermore, BIS-11 motor was found to predict symptom severity of gaming disorder, as the only BIS-11 facet [44••] or with the highest effect size [45]. Metcalf, Pammer [36] reported no significant differences regarding motor impulsivity. However, the sample size was small and limited to male participants.

Regarding UPPS, some studies reported non-significant differences between gaming disorder and control groups [30, 46]; however, these studies have a risk of sampling bias and include male participants only. More recently, in a large sample of over 3000 free-to-play gamers (gender-balanced) significantly elevated scores in individuals with gaming disorder compared to those without are reported in all UPPS subscales (despite the additional subscale positive urgency), especially in the negative urgency and sensation seeking subscales [47]. Negative urgency was also reported to be predictive of gaming disorder with ADHD comorbidity [48]. The study by Raybould et al. [44••] indicates that association between impulsivity and symptom severity may depend on gaming disorder measurement. They reported that positive and negative urgency predicted gaming disorder symptoms using the DSM-5 measure, but only positive urgency was a significant predictor when using the ICD-11 measure of gaming disorder symptoms.

Rho et al. [49] identified BAS drive (as the only BIS/BAS subscales) as a significant predictor of gaming disorder. Na et al. [50] did not find significant differences regarding BIS/BAS scores between gaming disorder and control groups; however, individuals with gaming disorder and comorbid alcohol use disorder showed elevated BAS scores (drive, fun-seeking, and reward responsiveness).

Behavioral Measures

Behavioral measures of motor impulsivity mainly comprise neutral/standard (also referred to by others as “cold”) motor inhibitory control tasks, most prominently Go/No-Go and Stop-Signal tasks.

Recently, Raybould et al. [44••] found that the number of errors in a standard Go/No-Go task (without addiction-related cues) predicted symptom severity (in both DSM-5 and ICD-11 symptom measures). This is in accordance with previous findings from (male) problem gamers who showed lower accuracy in no-go trials compared to casual gamers [51]. Furthermore, gaming disorder symptoms were associated with slower reaction times [44••] and elevated no-go-N2 latency indicating difficulties in early stages of response inhibition [34]. Earlier, van Holst et al. [52] did not find such association with performance in a standard Go/No-Go task. However, the sample was limited to male adolescent gamers.

A meta-analysis on Go/No-Go, the Stroop, and the Stop-Signal tasks identified that individuals with gaming disorder show moderate impairments in response inhibition compared to healthy controls [53]. However, regarding Stop-Signal Task, the meta-analysis focused on response accuracy and not on the stop-signal reaction time (SSRT) measuring response inhibition efficiency. Regarding SSRT, most studies did not report significant differences between individuals with gaming disorder and control groups (for a summary, see [54]) indicating that it is still not clear whether individuals with gaming disorder show general motor response inhibition deficits.

Stimulus-Specific Reductions in Inhibitory Control

The empirical evidence for stimuli-specific inhibitory control is very limited. Measures of stimulus-specific inhibitory control include tasks with addiction-related cues (in contrast to neutral cues), also referred to as “hot” versions of, e.g., Go/No-Go or Stop-Signal tasks. Implicit (motoric) approach tendencies towards gaming-related cues can further be measured with gaming-specific Approach-Avoidance tasks (AAT).

The number of errors in the stimulus-related Go/No-Go task is positively associated with symptom severity [44••, 52]. Studies on approach biases in gaming disorder are scarce. Using an AAT, Rabinovitz, Nagar [55] identified that excessive gamers show approach tendencies toward gaming cues. More recent results support this tendency [56]. Both reported that approach-tendencies and urge to game were reduced after cognitive bias modification training; however, evidence is still lacking.

To summarize, findings indicate that gaming disorder is associated with elevated motor impulsivity especially when considering self-report measures. Inhibitory control appears to be especially reduced in case gaming-related cues are present, although empirical evidence is still limited. Individuals with gaming disorder may show general deficits in motor inhibitory control as measured with standard tasks (not involving addiction-related cues); however, the findings seem to be strongly dependent on the scores used for the respective tasks.

Attentional Impulsivity in Gaming Disorder

General Attentional Impulsivity/Attention Deficits

Self-Report Measures

Self-report measures assessing attentional impulsivity mainly refer to the BIS attentional subscale and measures of tendencies towards attention deficit hyperactivity disorder (ADHD).

Looking at the BIS-11 subscales, Metcalf, Pammer [36] reported that individuals with gaming disorder score significantly higher than non-gamers as well as highly engaged gamers on the BIS-11 attentional subscale. To note, this study included a small exclusively male sample. A similar pattern (i.e., differences in attentional but none of the other BIS-11 subscales) has been reported in a more diverse sample of individuals with tendencies towards specific Internet-use disorders including gaming, online buying-shopping, and social network use [57]. Higher scores on BIS-11 attentional (in addition to other subscales) in gaming disorder versus control groups have also been reported by others in adult and adolescent samples [33, 42, 58]. Regarding linear relationships, BIS-11 attentional was reported to correlate moderately with gaming disorder symptom severity, in a large predominantly male sample of adult World of Warcraft (WoW) gamers [45] as well as in a large gender-balanced adolescent sample [58] with correlation coefficients of 0.28 and 0.25, respectively. Contrarily, using DSM-5 as well as ICD-11 symptom counts and diagnostic cutoffs, in a gender-balanced sample of over 300 adults, Raybould et al. [44••] did not find any differences or associations concerning BIS-11 attentional (but motor). Heightened attentional impulsivity in gaming disorder populations may especially occur in samples consisting of (predominantly) male adolescents.

To note, the associations between attentional deficits and gaming disorder appear to differ between genders and countries of origin [59]. Attention deficits are more common in (young) males [60], with boys with ADHD (compared to girls with ADHD) showing more hyperactivity and weaker motor inhibitory control [61]. ADHD is an independent diagnosis with a prevalence of 5.9% in children and adolescents and 2.5% in adults [62]. In the DSM-5, it is listed as a comorbidity of gaming disorder. Gaming disorder and ADHD often co-occur, in young adults as well as children and adolescents [63,64,65,66]. Longitudinal data show (bidirectional) associations between changes in symptom severity of gaming disorder and ADHD over time [67, 68]. Individuals with gaming disorder and comorbid ADHD are reported to show even heightened impulsivity [63]. However, ADHD comprises more than attention deficits, and other facets such as negative urgency have been found to be predictive of ADHD and gaming disorder comorbidity [48].

Behavioral Measures

Behavioral measures of general attentional impulsivity comprise classical tasks of selective attention abilities. The main task used in gaming disorder literature is the Stroop task.

Results regarding Stroop performance in individuals with gaming disorder are mixed. Some report no significant differences in Stroop performance [51, 69, 70]. In contrast, others (i.e., fMRI studies with small sample sizes) report weaker performance in classical Stroop task (i.e., higher number of errors and longer reaction times in incongruent trials) in adults [71] and adolescents [72] with gaming disorder compared to those without. Another study reported more errors but faster reaction times in incongruent trials in gaming disorder compared to control groups [73].

Stimulus-Specific Attentional Impulsivity/Attentional Bias

In experimental addiction research, the addiction-Stroop task (i.e., a Stroop task including with addiction-related cues) has often been used to measure stimulus-specific attentional shifts/interference. Attentional biases towards specific cues are also measured by other tasks such as the dot-probe or visual probe task.

The number of errors for gaming-related words in an addiction-Stroop task correlated positively with symptom score in a sample of male adolescents [52]. Similarly, longer reaction times toward gaming-related words in an addiction-Stroop task indicated attentional bias in excessive gamers compared to regular game users [74]. A similar trend toward attentional bias (although not significant) was reported by Zhang et al. [75] who compared male young adults with gaming disorder against a control group. In the dot-probe task, higher number of errors indicated attentional bias in individuals with gaming disorder/ excessive gamers compared to control participants [52, 74]. Liu et al. [76] used a standard Go/No-Go task and a “gaming distracting” modification with gaming-related cues. The cues were placed in the background (task-irrelevant). Performance in such a Go/No-Go version indicates the extent to which general inhibitory control varies as a consequence of attentional shift towards distracting stimuli. Results showed that individuals with gaming disorder, compared to a control group, made significantly more commission errors in the gaming distracting Go/No-Go task, while the groups did not differ in the standard Go/No-Go task [76].

Overall, evidence shows that attentional impulsivity is closely associated with gaming disorder. The direction of this relationship is discussed and probably bidirectional [77]. Individuals with gaming disorder show attentional biases toward gaming-related contents which may result in performance degradation in executive tasks. ADHD and gaming disorder are common comorbidities which must be considered (together with age and gender) to reduce functional impairments in this specific patient population.

Decisional Impulsivity in Gaming Disorder

General Decisional Impulsivity

Self-Report Measures

Self-report measures of decisional impulsivity include the BIS-11 non-planning subscale and BAS fun seeking representing the striving for immediate outcomes without reflecting/weighing potential consequences.

Most studies did not find any differences in BIS-11 non-planning between gaming disorder and control groups [36, 42, 43], with the exception of the findings by Ryu et al. [33]. Achab et al. [45] reported bivariate correlations between BIS-11 non-planning and gaming disorder symptom severity in a large sample of adult WoW gamers, however with smallest effect size of all BIS-11 subscales (r = 0.17). Others report no significant correlations with BIS-11 non-planning [58].

Dong et al. [78] reported that individuals with gaming disorder had higher BAS fun seeking sensitivity (but no differences in other BAS domains) compared to regular game users. The same was reported for a student sample diagnosed with gaming disorder compared to non-gaming-disorder control group [40]. However, despite significance, the differences reported in these two studies were rather marginal in size. The findings are consistent with previous findings indicating that especially the BAS fun seeking domain is associated with gambling disorder [79] and internet addiction [80]. Compared to BIS-11 non-planning, BAS fun seeking points more at reward responsiveness or risk seeking tendency, which may be related but not core features of impulsivity. The UPPS sub-facet “(lack of) premeditation” was not associated with gaming disorder symptoms [30, 44••].

Behavioral Measures

Behavioral measures of general decisional impulsivity include risky choice tasks (e.g., Iowa Gambling Task, Game of Dice Task) as well as the Information Sampling Task and delay discounting/ intertemporal choice tasks.

A meta-analysis by Yao et al. [81] including 24 studies identified small but significant deficits in decision-making performance (comprising risk, ambiguity, and intertemporal choice tasks) between individuals with and without gaming disorder. Looking more closely, recent findings indicate that gaming disorder is associated with disadvantageous decision-making especially under (objective) risk conditions (measured by, e.g., the Game of Dice Task or later trials of the Iowa Gambling task), and less with decision-making under ambiguous risk conditions (measured by, e.g., the Balloon Analogue Risk Task, or earlier trials of the Iowa Gambling Task) [82]. This points at heightened risk-taking tendencies (objective risk) and less difficulties in processing of feedback (ambiguous risk) in individuals with gaming disorder. This assumption is further supported by meta-analytical findings on probability discounting in gaming disorder, indicating increased decisional impulsivity represented by a stronger tendency to take risks in probabilistic gains together with faster response times [83]. Meta-analyses on intertemporal choice task measures show that gaming disorder is associated with steeper discounting of delayed rewards [81, 84]. Results from the Information Sampling Task indicate that individuals with gaming disorder, compared to healthy control participants, sample less information prior to deciding [46], indicating reduced gathering of relevant information.

Stimulus-related decisional impulsivity using behavioral measures that present addiction-related stimuli during a decision-making task has not yet been applied to gaming disorder, to the best of our knowledge.

In summary, gaming disorder appears to be associated with more short-sighted decision making and reduced gathering of relevant information. This might indicate less reflection about risks; however, general decisional impulsivity, in terms of general difficulties in reflecting on possible consequences, is not necessarily associated with gaming disorder. Preferences for fun seeking, immediate gratification, and risk taking may indicate a higher striving for reward (while disregarding potential risks) in some individuals with gaming disorder. However, respective decisions do not have to be impulsive per se but can also be subject to rational cost/benefit considerations. Whether decision making in individuals with gaming disorder is altered/ impaired by the presentation of specific cues, it remains to be investigated empirically.

Conclusions

The present review demonstrates that impulsivity is an important topic in gaming disorder research and potentially in clinical contexts. The systematic examination along three main facets of impulsivity and by separating general from stimuli-specific impulsivity and self-report from behavioral measures suggests that the current evidence for the involvement of specific impulsivity-related processes in gaming disorder is heterogenous. However, in order to advance the understanding of mechanisms underlying affective and cognitive processes underlying gaming disorder, it will be important in future studies to systematically differentiate between the sub-constructs of impulsivity and to investigate how these impulsivity facets may be specifically associated with other gaming disorder features.

Considering attentional deficits in individuals with gaming disorder is important for clinical practice, as studies indicate that individuals with gaming disorder and comorbid ADHD show higher gaming disorder symptoms over time, poorer recovery rates, and higher relapse rate within 1 year, compared to individuals having gaming disorder without comorbid ADHD [67]. This longitudinal association may be bidirectional (at least for males) and appear to be linked more to the inattention component than to the hyperactivity component of ADHD [68].

Regarding attentional deficits, but also other facets of impulsivity, gender-related differences must be considered as they probably contribute significantly to the development and maintenance of gaming disorder [85]. Gaming disorder is over 2.5 times more prevalent in males compared to females [27•]. Gender may moderate the relationship between impulsivity and gaming disorder [86] as well as that with other predictors [58]. Also, associations between attentional deficits and gaming disorder appear to differ between genders [59]. Furthermore, the negative consequences resulting from excessive gaming may differ by gender in the directions of more social problems for boys and more emotional problems for girls [87]. To note, most studies on cognitive performance in gaming disorder are based on predominantly male samples (see, e.g., overviews by [58]) as is the case in research on other mental disorders. Gender-related differences in brain and behavior require more systematic investigation to derive more targeted conclusions for clinical practice.

Decisional impulsivity in general is not clearly associated with gaming disorder. In some domains and tasks, decision-making does not seem to be significantly impaired. However, individuals with gaming disorder may tend to more disadvantageous decisions when (a) high gains are available (despite high risk), (b) gains are available immediately (and not delayed), and (c) relevant information must first be gathered. What has not yet been studied experimentally is whether gaming disorder is associated with changes in decision-making behavior in the presence of affective stimuli. In experimental addiction research, decision-making tasks such as the Iowa Gambling Task have been modified with addiction-related pictures presented on either the advantageous or disadvantageous card decks, e.g., in substance-use disorders [88], eating disorders [89], pornography use [90], buying/shopping disorder [91], or problematic social-network use [92] with results indicating stimulus-related interference with decision-making behavior. Future studies could apply this procedure to the context of gaming to investigate stimulus-specific decisional impulsivity in gaming disorder. We are also pursuing this approach in a current research unit [93]. Findings on impairments in decision making may provide valuable insight into mechanisms that lead to functional impairments in everyday life in individuals suffering from gaming disorder.

Limitations lie in the heterogeneity of definitions and measures of both impulsivity and gaming disorder. Facets of impulsivity may overlap and may not be clearly separable but need more precise definitions. For example, motor impulsivity in terms of “acting without thinking” also implies difficulties in reflecting on consequences before making a decision (decisional impulsivity), and difficulties in gathering/weighing of relevant information (decisional impulsivity) may also result from difficulties to focusing attention to task-relevant parameters (attentional impulsivity). Behavioral measures such as performance in decision-making tasks represent a conglomerate of diverse cognitive and affective functions and often correlate poorly with self-report measures [94]. Also, the diagnostic measures of gaming disorder are heterogeneous. The classification and estimated prevalence rates may vary strongly depending on the used screening instrument [95]. A consistent assessment of gaming disorder and the use of unified diagnostic criteria are essential to produce comparable results.

In sum, there are many individual findings on selected facets of impulsivity in gaming disorder. We would encourage future research to more systematically and comprehensively address different facets of impulsivity using self-report as well as behavioral measures. Specific correlates or moderating variables, such as gender, comorbidities, or general executive functions, should be included in order to understand the role of specific aspects of impulsivity as transdiagnostic features in the context of gaming disorder. Regarding causality, we may speculate that some (more general) aspects of impulsivity depict vulnerability factors, while other (more specific) impulsivity aspects may additionally develop during the course of the disorder. Future studies should follow a longitudinal approach and make use of behavioral measures including addiction-related cues to investigate changes in stimuli-specific impulsivity over time.