The dearth of evidence related to cultural and gender variations of established associations between Internet Gaming Disorder (IGD) and other psychopathologies has been highlighted. Accordingly, the present study examined the association between depression and disordered gaming behaviors, while considering cultural perspectives of vertical individualism (independence and hierarchy) and gender as potentially variating factors. To achieve this, an ethnically diverse online sample of internet gamers from multicultural societies (N = 1032; Australia = 738; 71.5%; USA = 222; 21.5%; other multicultural countries = 72; 13.3%; Mage = 24 years; males = 503 [48.7%], females = 529 [51.3%]) completed the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF); the Depression, Anxiety and Stress Scale (DASS-21) and the Individualism and Collectivism Scale (ICS). Regression, moderation and moderated moderation analyses were conducted. Results demonstrated that gamers presenting concurrently with symptoms of depression and vertically individualistic inclinations reported higher levels of disordered gaming behaviors, with no significant gender differences. The findings obtained imply that practitioners globally, and especially in multicultural societies (e.g., Australia, USA), should consider cultural differences when developing prevention and intervention strategies for disordered gaming.
The popularity of gaming as a leisure activity is growing globally, with many countries reporting a steady growth in the prevalence of gaming. Overall, approximately 2.2 billion people play videogames worldwide (Newzoo, 2017). Moreover, according to the Electronic Software Association (ESA), more than 164 million adults in the United States of America (USA) play videogames and three-quarters of all Americans have at least one gamer in their household (ESA, 2019). Similar trends have been reported in Australia as approximately 67% of all Australians play video games on a regular basis (IGEA, 2018) and in the United Kingdom (UK) where a total of 32.4 million people played videogames in 2017 (Newzoo, 2017).
Research on videogame effects has sought to examine how the interaction between mental health symptoms and online gaming may precipitate or perpetuate disordered gaming (DG) outcomes (Petry & O’Brien, 2013; Dong & Potenza, 2014; Stavropoulos et al., 2016; Laconi et al., 2017). Moreover, previous studies suggested that judicious gaming can result in significant positive effects, including improved interpersonal skills, stimulated cognitive development and promotion of positive affect and well-being (Jones et al., 2014; Laconi et al., 2017). Furthermore, gaming may bolster psychological resilience, serving as a coping mechanism against life-adversities (Stavropoulos et al., 2016).
Notwithstanding the potential positive outcomes associated to online gaming, mounting evidence suggests that DG can lead to significant impaired psychological health and well-being (Caplan, 2002; Porter et al., 2010; Dong & Potenza, 2014; Pontes, Stavropoulos, & Griffiths, 2019; Stavropoulos, Gomez, Mueller, Yucel, and Griffiths, 2019b; Stavropoulos, Gomez, and Motti, 2019a; Stavropoulos, Dumble, Cokorilo, Griffiths, and Pontes, 2019d). More specifically, DG may accommodate low affect, decreased occupational performance and psychopathology (such as major depressive disorder; American Psychiatric Association [APA], 2013), maladaptive coping strategies and reduced adaptation (Young & Rodgers, 1998; Stavropoulos et al., 2016; Liu et al., 2018).
In light of the mounting evidence supporting the addictive and detrimental effects of DG, the World Health Organization (WHO, 2018) decided to recognize ‘Gaming Disorder’ as an official mental health disorder in the latest beta draft of the International Classification of Diseases (ICD-11). According to the WHO, gaming disorder is defined as a pattern of persistent gaming behavior manifested by three main diagnostic criteria: (i) impaired control over gaming (e.g., onset, frequency, intensity, duration, termination, context), (ii) increasing priority given to gaming to the extent that gaming takes precedence over other life interests and daily activities and (iii) continuation or escalation of gaming despite the occurrence of negative consequences (WHO, 2018). Moreover, gaming disorder should only be diagnosed when the behavior is of sufficient severity to result in clinically significant impairments in personal, family, social, educational, occupational or other important areas of functioning (WHO, 2018).
Despite the recent recognition of gaming disorder by the WHO (2018), the present study adopts the conceptualization of the behavior in line with Section III (‘Emerging measures and models’) of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5, Fifth edition; APA, 2013) for the following reasons: (i) it focuses on internet-based games, warranting internet specific terminology; (ii) adopting DSM-5 terminology enables international comparability and (iii) currently, DSM-5 terminology is supported by standardized and psychometrically sound assessment scales (Lemmens, Valkenburg & Gentile, 2015; Pontes & Griffiths, 2015; Stavropoulos et al., 2018a).
Thus, according to the DSM-5 (APA, 2013), DG is defined as 'Internet Gaming Disorder' and constitutes a persistent, ongoing engagement with internet-based games, causing functional impairment and distress (Petry & O’Brien, 2013; Pontes et al., 2014; Griffiths, Kuss & Pontes, 2016; Laconi et al., 2017). In this context, a positive DG diagnosis requires the endorsement of at least five of the following criteria: (1) excessive preoccupation with gaming; (2) withdrawal symptoms in the absence of gaming; (3) tolerance, or need to increase time spent gaming; (4) failed gaming abstinence attempts; (5) ceasing one’s other usual hobbies due to gaming; (6) continued gaming despite its negative impacts; (7) deception to significant others about gaming intensity; (8) using gaming as a coping mechanism (e.g., to escape or relieve distress) and (9) compromising one’s occupation, significant relationships or future opportunities due to gaming habits (APA, 2013).
Interestingly, there is inconsistent evidence on the global, gender-specific and culture-specific prevalence of DG (Laconi et al., 2018; Fam, 2018), and global prevalence estimates of DG have been found to range between 3.4 and 6.0% of users, with some countries reporting as high as 10.0%, respectively (Widyanto & McMurran, 2004; Hoeft et al., 2008; Pontes et al., 2014; Lemmens, Valkenburg & Gentile, 2015; Nazlıgül et al., 2018). Prevalence estimates vary significantly according to diagnostic criteria and conceptual definitions of the construct (Laconi et al., 2017).
Although adult populations (especially those aged between 30 and 35 years) comprise the majority of internet gamers, younger individuals remain the most vulnerable group, primarily due to developmental factors (i.e., increased impulsivity, and achievement and gratification needs; Stavropoulos et al., 2016; Burleigh et al., 2018; Laconi et al., 2017; Fam, 2018). Given the expanding popularity of gaming, Section III of the DSM-5 (APA, 2013) has highlighted the importance of understanding interactions between DG and other precipitating and perpetuating factors. Consequently, in-depth examination of associated DG contributing factors is warranted.
Gaming Motivation and Genres
Game genres and motivation have been found to be key risk factors for DG. Demetrovics and colleagues suggested that socialization, escapism, competition, coping with difficulties, developing skills, fantasy, and recreation constitute the main motivations for gaming (Demetrovics et al., 2011). Similarly, and aiming to identify higher and more inclusive gaming motivation domains, Yee, Ducheneaut and Nelson (2012) psychometrically supported that various game motivations comprise three higher-level categories (i.e., achievement, socialization and immersion). Alternatively, adopting the perspective of self-determination theory, Lafrenière, Verner-Filion and Vallerand (2012) asserted that gaming motivation is explained by intrinsic motivation, integrated, identified, introjected and external regulation, as well as amotivation-related needs and drives.
However, different game genres constitute broad categories of games that promote unique experiences and result in different motives for individual gamers (Ghuman & Griffiths, 2012). Although there is no clear consensus on a universal genre typology, these can indicatively include shooters (e.g., Call of Duty), multiplayer online battle arena (MOBA) (e.g., League of Legends) and strategy games (e.g., Tetris), among others. Genres incorporate different structural characteristics and in-game mechanisms (such as reward stimulation and hierarchical ranks) that moderate emotional and cognitive processes by targeting gamer’s motivations (Caplan, Williams, and Yee, 2009; Liu & Peng, 2009; Elliott et al., 2012; Müller et al., 2015). Primary excessive gaming drives have been identified, including (i) achievement and/or competition; (ii) socializing and/or belonging, and (iii) game immersion and/or identification with one’s virtual character (Hoeft et al., 2008; Müller et al., 2015). These motivations may elicit cognitive and emotional compensatory processes whereby the user may aim to substitute real-life deficits (i.g., achievement; Morcos et al., 2019). Research has found that of various gaming genres, the massively multiplayer online role-playing game (MMORPG) genre employs mechanisms appealing to these motives most profoundly (i.e., achievement, socialization and identity motives; Müller et al., 2015; Laconi et al., 2017; Burleigh et al., 2018). In considering the moderating impact on emotion and cognition, the MMORPG genre is assumed to pose greater DG risk to users predisposed to mood disorder symptoms, and especially depression (Stavropoulos et al., 2018b; Morcos et al., 2019). Therefore, the present study focuses on the MMORPG genre, while investigating the association between depression and DG symptoms.
Depression and Disordered Gaming
In addition to game genre and motivation, significant comorbidities have been supported between DG and other psychopathologies (Woelfling et al., 2008; Mihara & Higuchi, 2017; Pearcy et al., 2017; Kim et al., 2017; Adams et al., 2018; Liu et al., 2018), while addictions (such as DG) have been assumed to accommodate mood-regulation difficulties (Müller et al., 2015). In this context, depressive symptoms, including feelings of worthlessness, helplessness and hopelessness, difficulty concentrating, physical agitation (e.g., fidgeting), social isolation, and lethargic withdrawal from regular activities, have been strongly associated with addiction in general, and DG in particular (APA, 2013; Burleigh et al., 2018; Liu et al., 2018). Interestingly, associations between depressive and DG symptoms have been envisaged as complex, implying that symptoms of depression can initiate DG behaviors (as relief behaviors), which could later accommodate higher depression tendencies (Ho et al., 2014; Lee et al., 2017; Liu et al., 2018; Stavropoulos et al., 2019a). An individual experiencing feelings of worthlessness and low affect, for instance, may turn to internet gaming to gain a sense of self-worth and fulfillment, while finding their needs easily compensated for by features of the game itself (Stavropoulos et al., 2016; Liu et al., 2018). These align with the compensatory internet use hypothesis (Kardefelt-Winther, 2014), which proposes that gamers may counterbalance real-life experiences of distress and depression with positive experiences produced by game mechanisms. Consequently, behavioral addictions such as DG may on one side provide immediate relief and gratification from depressive symptoms, whilst promoting them in the longer term (Petry & O’Brien, 2013; Kaptsis et al., 2016; Kim et al., 2017).
Despite the established depression-DG association, there is a dearth of evidence assessing its potential cultural variations. This is imperative in the light of research consistently supporting that symptoms of depression and DG can be moderated by culture (and culturally dictated drives such as those for competitiveness and hierarchy; Arsenault, 2009; González & Adelantado, 2016). Research by Stavropoulos and colleagues (2019) has underscored the importance of such findings in developing culturally responsive interventions for multicultural countries (i.e., Australia and the USA). Consequently, the present study aims to address how the association between depression and DG may be moderated by cultural differences.
Disordered Gaming and Culture
Research has assumed that different cultural aspects may accommodate different forms of psychopathology including DG (Triandis, 1996; Charlton & Danforth, 2007; Stavropoulos et al., 2016; Stavropoulos et al., 2020). Moreover, the cross-cultural assessment of excessive internet use behaviors, including online gaming, has been the focus of scholarly examination because different response patterns may apply (Kiraly et al., 2019; Laconi et al., 2018; Lopez-Fernandez et al., 2019). Similarly, it has been supported that experiences of psychosocial, addictive, and psychopathological disorders differ across cultures, implicating specific cultural syndromes (Triandis, 1996; Wan & Chiou, 2006; Anderson et al., 2017).
Triandis (1996) implied that cultural syndromes (i.e., shared cultural perspectives) may have significant associations with disordered behaviors and addictions using a continuum ranging from “collectivism” to “individualism”. More specifically, collectivism describes one’s self-perception and behavior in line with a collective (e.g., the family or societal norms), while individualism describes one’s perception of self as independent and autonomous from the group where personal interests are prioritized.
These constructs occur in horizontal or vertical variations (Singelis et al., 1995; Triandis & Gelfand, 1998). Verticality describes cultural endorsement of social hierarchy, where individual worth is measured by competitive success, while horizontality describes cultural endorsement of equality, where all individuals are considered equal (Triandis, 2018). Research has suggested that verticality may have significant associations with DG, where verticality-related competitive goals and motivations interact with corresponding game modalities (such as achievement), increasing DG vulnerability (Stavropoulos et al., 2016). Similarly, individualistic features, related to independence and social disconnection aspects, may predispose addictive disorders such as DG. Furthermore, a combined vertical-individualistic cultural orientation could predict higher DG risk (Györkös et al., 2013; Stavropoulos et al., 2016).
Despite the rationale supporting these hypotheses, there is scarcity of empirical research validating them. This is of particular importance to multicultural populations (e.g., Australia, USA, UK), where cultural diversity implicates differences in psychopathological risk and responsiveness to treatment (Györkös et al., 2013; Stavropoulos et al., 2016). More specifically, multicultural countries (such as the USA and Australia) have been assumed to present with a dominant cultural orientation of a westernized vertically individualistic quality (e.g., competitiveness and hierarchy tend to be more prominent and common), while at the same time, variations on these vertically individualistic tendencies exist due to the concurrent influence of other cultures (Vargas & Kemmelmeier, 2013). Therefore, one could assume that game motivations related to achievement and hierarchy, in the context of vertically individualistic tendencies, may differ across gamers from multicultural societies. Further, the extent that the effect of other DG-related factors, such as depressive mood, could be moderated (exacerbated) by a more vertically individualistic cultural orientation remains questionable (Stavropoulos et al., 2016; Stavropoulos et al., 2019b). Competitive and independence game-related motivations, potentially appealing among vertically individualistic gamers, could exacerbate DG vulnerability in the MMORPG context (Györkös et al., 2013; Stavropoulos et al., 2016). Given the aforementioned gap in the literature, the present study examines if—and to what extent—the association between depressive mood and DG behaviors can be exacerbated by higher vertically individualistic tendencies among a sample of gamers coming from multicultural societies.
Disordered Gaming, Gender and Depression
Aside from broader cultural dimensions, research has identified individual factors, such as gender, as concurrently implicated in DG and depression vulnerability (Burleigh et al., 2018; Adams et al., 2018). Understanding the distinct influences of gender variations has been repetitively emphasized in developing effective interventions. More specifically, gender differences are reflected in motives underpinning gaming engagement (Müller et al., 2015). Males are typically driven by competition and achievement while females by social relationships (Taymur et al., 2016; Laconi et al., 2017). Similarly, it can be assumed that gender experiences can vary across different cultural orientations, with more individualistic cultures pertaining less distinct gender roles and drives than more collectivist cultures. Specifically, in more collectivistic cultures, drives of achievement and hierarchy are mostly enhanced among males compared to females, who are usually more driven by social and relationship needs (Anderson et al., 2017; Laconi et al., 2017).
Accompanying these, depression and DG are both known to manifest differently across genders (Chumbley & Griffiths, 2006; Stavropoulos et al., 2016; Anderson et al., 2017). Females are twice as likely as males to experience depression (APA, 2013), in contrast with DG, where males present more vulnerability (Liu et al., 2018). Based on previous research, it can be assumed that gender may additionally influence the moderation effect of a more vertically individualistic cultural orientation on the association between depressive and DG behaviors. For instance, males experiencing lack of purpose and achievement (in the context of a more depressive mood) may utilize internet games to compensate for it at different levels, depending on the extent of their vertically individualistic cultural orientation (Griffiths et al., 2004; Hoeft et al., 2008). Contrastingly, females experiencing isolation (in the context of depressive mood) may also compensate with excessive engagement in social aspects of the game at different levels, depending on their level of vertically individualistic cultural orientation (that encourages independence; Müller et al., 2015).
However, the specific effect that broader cultural dimensions, and especially vertical individualism, may have on such gender-related game motivations is yet to be understood empirically. This is important as literature has suggested that in more vertically individualistic cultures, combined motivations of achievement and competition may be exacerbated in male gamers (Beard & Wickham, 2016; Stavropoulos et al., 2019c). In this context, differences in gender motivations may culturally vary the established association between depression and DG symptoms (Laconi et al., 2017; Stavropoulos et al., 2019d). Thus, to shed light on these complex relationships, the present study considers the impact of gender on the potential moderating effect of higher vertically individualistic tendencies in the association between depressive mood and DG behaviors.
Conceptualizing Disordered Gaming Risk
To conceptualize and explain its findings, the present study adopts an integrative framework. Contemporary research and extant empirical findings have emphasized that DG symptoms can be explained by the dynamic interplay between various elements related to the gamer, their surrounding and the game itself (Valkenburg & Peter, 2013; Masten, 2014; Petry & O’Brien, 2013). Indicatively, Stavropoulos et al., (2016) advocates an integrated model encompassing individual, contextual, and game-related factors to conceptualize DG behaviors on a severity continuum ranging from minimum to maximum risk. This model posits that individual (e.g., sociodemographic, psychopathologies, and developmental factors) and real contextual factors (e.g., family climate and community culture) may accommodate (“push towards”) DG, while game factors (such as features of the game itself) may “pull” (invite) the individual (Stavropoulos et al., 2016). While the interactions between these push and pull mechanisms are reflected in previous theoretical models, researchers have highlighted that concurrent presentations of cultural and gender differences have yet to be investigated (Pearcy et al., 2017; Laconi et al., 2017).
The Present Study
Based on the review of the literature conducted, the present study investigated the contribution of gender in the established association between depression and DG from a specific cultural perspective examining a population of gamers recruited from multicultural societies. Accordingly, it considers a more vertically individualistic cultural orientation as a factor that may moderate the relationship between depression and DG. Finally, in order to ascertain distinctions between gender experiences in the depression-DG association across variable levels of vertical individualism, the present study considers gender as an additional moderator of DG risk. Therefore, in order to achieve the aforementioned aims, the following hypotheses were developed to be tested (see Fig. 1):
H1: Gamers with higher depressive symptoms will score significantly higher on DG symptoms.
H2: The association between depressive and DG symptoms will vary significantly according to levels of vertical individualism reported.
H3: The interaction between depressive and DG symptoms and vertical individualism may vary according to the gender of the gamer.
Eligible participants for the present study involved adults over the age of years 17, with residency in Australia, the USA, the UK, Canada, and New Zealand and familiarity with gaming applications (N = 1032 Mage = 24, SDage = 7, males = 503 [48.7%], females = 529 [51.3%]). The estimated maximum sampling error (at the 95% confidence interval) for 1032 participants is 3.11%, which satisfies Hill’s (1998) recommended acceptance level of ± 4%, respectively. Further sociodemographic and internet gaming information are found in Table 1.
Demographic (such as age and gender) and internet use questions (such as time spent gaming) were presented to participants prior to the primary self-report scales (of depressive and DG symptoms and cultural orientation).
Internet Gaming Disorder Scale–Short-Form (IGDS9-SF)
The IGDS9-SF (Pontes & Griffiths, 2015) assesses the severity of DG symptoms (reflecting the diagnostic criteria outlined in the DSM-5; APA, 2013). Each of the nine items is responded on uses a five-point Likert scale ranging from 1 (Never) to 5 (Very often), indicating severity of DG behaviors (e.g., “Do you play to temporarily escape or relieve a negative mood?”). The total score is derived from the summation of all item responses and ranges from 9 to 45, with higher scores indicating more severe DG symptoms. The instrument retains high internal reliability across Australia and the USA (Cronbach’s alpha = 0.92 and 0.90, respectively; Stavropoulos et al., 2018a) as well as in the present study (Cronbach’s alpha = 0.87).
Depression Anxiety Stress Scale
The Depression Anxiety Stress Scale (DASS-21) assesses the severity of depression, anxiety, and stress symptoms (Lovibond & Lovibond, 1995). The instrument has 21 items, each with seven assessing depression (e.g., “I couldn’t seem to experience any positive feeling at all”), anxiety (e.g., “I felt I was close to panic”) and stress (e.g., “I found it hard to wind down”). Each item is responded to a four-point Likert scale ranging from 1 (Never) to 4 (Almost always). Only items indicating symptoms of depression were used in the present study. Relevant item response values are accumulated to indicate total scores for each category (with scores ranging between 0 and 21 for depression). Cut-off scores are provided, indicating symptom severity (Normal = 0–4, Mild = 5–6, Moderate = 7–10, Severe = 11–13 and Extremely severe = 14+). Internal reliability in the present study was high (DASS Cronbach’s alpha = 0.91; depression items Cronbach’s alpha = 0.89).
Individualism and Collectivism Scale/Culture Orientation Scale
The Individualism and Collectivism Scale/Culture Orientation Scale (ICS) assesses cultural orientation across dimensions of vertical individualism, vertical collectivism, horizontal individualism and horizontal collectivism (Triandis and Gelfand, 1998). The instrument has 16 items, with four assessing vertical individualism (e.g., “Winning is everything”), four assessing vertical collectivism (e.g., “Parents and children must stay together as much as possible”), four assessing horizontal individualism (e.g., “I often do ‘my own thing”) and four assessing horizontal collectivism (e.g., “To me, pleasure is spending time with others”). Each item has a nine-point scale ranging from 1 (Never or Definitely no) to 9 (Always or Definitely yes). Scores for each dimension are produced by summing their relevant item scores (ranging from 4 to 36). Higher scores indicate stronger ideological alignment with the content of each dimension. Internal reliability for the present study was also high (Cronbach’s alpha = 0.71 for vertical individualism, 0.69 for vertical collectivism, 0.57 for horizontal individualism and 0.86 for horizontal collectivism).
This project was approved by the institution’s Human Research Ethics Committee prior to commencing in December 2018. Criteria for eligible participants included a minimum age of 18 years; residency in Australia, the USA, the UK, Canada, and New Zealand, and internet gaming experience. Sampling methods entailed sharing the online survey across media platforms (e.g., Facebook), through advertisement flyers, and virtual chat rooms (e.g., Discord). Given this study’s interest in gamer populations, independent distribution of the research survey was encouraged in online gaming communities. Responses were collected through SurveyGizmo, where participants first engaged with the Plain Language Information Statement (PLIS). This notified them of the voluntary nature of the study, the anonymous and secure storage of data, and required the digital provision of informed consent prior to continuation with the survey. Withdrawal was permitted prior to submitting a completed survey without penalties.
To assess the predictive association between depression (DASS scores) and DG behavior (H1), a two-step hierarchical linear regression analysis was conducted using the IBM Statistical Package for the Social Sciences (SPSS, 25th edition). Age and gender (dummy coded 0 = females, 1 = males) were inserted as independent variables to control for potential confounding effects (Step1), with depression inserted as an independent variable (Step2). To enhance the quality of the results, bootstrapping at the optimum level of 5000 resamples was applied (Hayes, 2017).
Based on Model 1 of the Process macro (by Hayes, 2017), a moderation analysis was then conducted to assess the potentially exacerbating effect of the gamer’s levels of vertical individualism on the depression-DG association (H2). Age and gender functioned as covariates to account for their potentially confounding effects. Depression was used as the independent (predictor) variable, with DG scores as the dependent (outcome) variable, and measured levels of the cultural dimension of vertical individualism as the moderating variable.
To assess H3, a moderated moderation analysis was conducted. Model 3 of the Process macro (Hayes, 2017) was applied to investigate whether the interactive effect between symptoms of depression, vertical individualism, and DG behavior varied according to the gender of the gamer. Age was simultaneously controlled for any potentially confounding effect. For this model, depression was the predictor variable, with DG as the outcome variable, vertical individualism as the moderator variable, and gender as the moderating moderator variable. Lastly, the Johnson-Neyman (J-N) technique was applied to indicate specific levels of significance (i.e., points of transition) of the moderating effects in both Model 1 and Model 3 on DG behavior (Hayes, 2017).
Before proceeding with the main models, the effect of the country of origin of the gamers (participants) was assessed with three successive analyses of variance (ANOVAs) in relation to the continuous variables involved in the current models. More specifically, IGD total score, depression, and vertical individualism were inserted as continuous dependent variables in three different ANOVAs, with the country of origin (1 = Australia; 2 = USA; 3 = Other [Canada, UK, New Zealand]) inserted as the independent variable. Findings indicated no significant differences (at the p < .001 level) and small or negligible effect sizes in regard to the country of origin considering IGD total score (F = 2.08, p = .125, H = 0.004), depression (F = 6.200, p = .002, H = 0.012), and vertical individualism (F = 0.573, p = .564, H = 0.001).
To assess H1, a cross-sectional analysis was conducted. The slope of the two-step hierarchical regression model (step 1 inserting age and gender as controls, step 2 inserting depression scores as the predictor) was statistically significant (F(1, 960) = 87.41, p < .001), accounting for 21% of variance in DG (R2 = .21). Depression exclusively explained 19.9% of variance in DG (Fchange(1, 960) = 243.3, p < .001, R2change = 0.20). Each point of increase in depression scores resulted in an increase in DG by 0.56 (b = 0.56, p < .001).
Furthermore, ordinary least squares regression moderation analysis was conducted to assess H2 (Hayes, 2017), assessing whether the associated levels of risk between depression and DG were exacerbated by levels of vertical individualism. More specifically, depression scores were input as the central predictor (D), with vertical individualism levels as the moderator (M), and their interacting effect (D × M) as further predictors (see Model 1 by Hayes, 2017). Age and gender were also inserted as covariates/controls (see equation below).
DG = a + b1(depression) + b2(vertical individualism) + b3(gender) + b4(age) + b5(depression × vertical individualism).
The results obtained for this analysis suggested that 28% of variance in DG behavior was accounted for by the full moderation model (R2 = .281), with the regression slope being significant (F(5, 958) = 74.74, p > .001). Depression and vertical individualism were found to interact significantly, exacerbating DG behaviors (b3 = 0.20, t(958) = 2.87, p = .004, LLCI = 0.004, ULCI = 0.025). This indicates that DG scores increase when the gamer presents simultaneously with higher depression and higher vertical individualism (see Fig. 2). The Johnson-Neyman technique was also applied to identify variations in this exacerbating association (Hayes, 2017), demonstrating no significant transition points.
In order to assess H3, a moderated moderation analysis was conducted (following Model 3 of methodology recommended by Hayes, 2017), examining whether the interacting effect between depression (D) and vertical individualism (M) on DG behavior varied according to gender (G). The following equation summarizes this model:
DG = a + b1(depression) + b2(vertical individualism) + b3(gender) + b4(age) + b5(depression × vertical individualism) + b6(depression × gender) + b7(vertical individualism × gender) + b8(depression × vertical individualism × gender).
The overall model explained 28.4% of DG variance (R2 = .28; see Table 2), with a significant slope in the full regression model (F(8, 955) = 50.97, p < .001). Notably, the three-way interaction coefficient between depression, vertical individualism, and gender indicated a non-significant exacerbating effect with DG (b = −.016, t = −1.62, p = .105). The separate two-way interactions between depression and gender and vertical individualism and gender were also non-significant (p = .338 and .149, respectively; see Table 2). These findings indicate that when present, the effect of the interaction between depression and vertical individualism did not significantly differ across genders in relation to DG behaviors. The Johnson-Neyman technique (Preacher, Rucker & Hayes, 2007) was applied to further explain this interaction and demonstrated no significant differences.
The present study identified a knowledge gap in research investigated how gender and cultural orientation, alongside their interplay (within multicultural societies), may influence the relationship between depression and DG (Arsenault, 2009; Griffiths et al., 2016; González & Adelantado, 2016; Stavropoulos et al., 2019a). Accordingly, hierarchical linear regression, moderation, and moderated moderation analyses were employed on a normative online sample of gamers coming from multicultural societies to examine these associations (Stavropoulos et al., 2016; Hayes, 2017). Overall, the results obtained corroborated previous literature, providing further support to the notion that higher depressive symptoms precipitate DG risk. Furthermore, an exacerbating influence of vertical individualism on this association was revealed, such that more vertically individualistic gamers experiencing symptoms of depression presented at greater risk of DG with no significant gender differences. These results have significant implications for clinical practice, where cultural orientation ought to be considered when introducing prevention and intervention strategies for those experiencing comorbid symptoms of depression and DG. Additionally, the findings obtained invite future research on the associations revealed, where the use of clinical samples and qualitative research methods is recommended.
Depression and Disordered Gaming Bond
The present study provided findings indicating that gamers experiencing elevated symptoms of depression would report increased DG behaviors (H1). This supports a substantial body of literature emphasizing the risk posited by symptoms of depression in developing addictive behaviors, particularly those of DG (Müller et al., 2015; Taymur et al., 2016; Burleigh et al., 2018; Adams et al., 2018; Liu et al., 2018; Stavropoulos et al., 2019b). More Specifically, gamers presenting with symptoms of depression may be at significantly higher risk of developing symptoms of DG than other gamers. This is in line with the suggestion that individual factors may contribute to DG behaviors advocated by the integrative theoretical framework adopted (Stavropoulos et al., 2016).
Specifically, this finding could be interpreted by past literature suggesting that the depression and DG association is based on cognitive and emotional processes perpetuated by excessive internet gaming (Yen et al., 2019). Interestingly, the compensatory internet use hypothesis (Kardefelt-Winther, 2014) explains how gamers may counterbalance real-life experiences of distress and depression with positive experiences promoted by gaming mechanisms (such as reward stimulation and social connection). Gamers experiencing low affect and helplessness, for instance, may utilize internet games for their motivational appeal to immersion and achievement, thus providing them with relief of their offline depression. When utilized excessively, however, this compensatory process may result into a maladaptive emotional regulation strategy, leading to DG (Kardefelt-Winther, 2014; Stavropoulos et al., 2016; Taymur et al., 2016; Morcos et al., 2019; Stavropoulos et al., 2019c).
Conversely, research has suggested that excessive internet gaming behavior places gamers at higher risk for real-life dysfunction (e.g., the loss of one’s job) that would in turn precipitate and/or perpetuate symptoms of depression (Griffiths, Kuss & Pontes, 2016; Adams et al., 2018; Stavropoulos et al., 2018c). These interactions advocate bi-directional and cyclical associations, whereby symptoms of depression and DG can not only initiate and maintain one another but may also occur concurrently to exacerbate one another’s severity (Stavropoulos, Kuss, Griffiths & Motti-Stefanidi, 2016; Liu et al., 2018). In this context, the findings of the present study encourage the development of clinical intervention strategies that target internet gaming behavior functioning as a maladaptive emotion regulation strategy to alleviate symptoms of depression.
The Significance of Culture in the Depression-Disordered Gaming Bond
The findings of this study also indicated that gamers report increased symptoms of DG when presenting concurrently with higher symptoms of depression and higher levels of vertical individualism (H2). In this context, gamers experiencing symptoms of depression, who might be more vertically individualistically orientated may find themselves at a significantly greater risk of developing symptoms of DG. This finding supports a significant body of literature advocating the influence of cultural orientation on the associations between psychopathologies and addictive behaviors in general, and in particular DG (Singelis et al., 1995; Györkös et al., 2013; Winkler et al., 2013; Taymur et al., 2016; Stavropoulos, Anderson et al., 2017; Stavropoulos et al., 2018c). More specifically, employing the integrative internet abuse framework, suggested by Stavropoulos et al. (2016), a more vertically individualistic orientation may foster and host achievement, competition, and ranking drives that when matched by mechanisms of the game could render the gamer more vulnerable to DG (Singelis et al., 1995; Györkös et al., 2013; Stavropoulos et al., 2018b). Indeed, vertically individualistic cultural orientation endorses behaviors related to self-driven achievement, an innate cultural value that is strongly reflected in the motivational appeal of the MMORPG genre. Interestingly, research has assumed that such overlaps may result in DG behaviors (Taymur et al., 2016; Laconi et al., 2017; Pearcy et al., 2017; Stavropoulos et al., 2018b). Such associations could become strengthened alongside concurrent gamer-related psychopathological features that may ‘push’ to a digital escape (i.e., symptoms of depression). In this context, depressed gamers, who are concurrently more vertically individualistically directed, may be at higher risk of developing DG than gamers presenting with equal levels of depression and lower vertically individualistic inclinations (i.e., achievement, competitiveness, and ranking). In developing prevention and intervention strategies, these findings encourage practitioners to consider in their case formulations and treatment plans cognitions and behaviors that may reflect more vertically individualistic tendencies, which could exacerbate DG risk effects, such as symptoms of depression (Griffiths, Kuss & Pontes, 2016).
The Gender Effect
With regard to the findings related to H3, the present study found no significant gender differences in the interaction between vertical individualism and symptoms of depression on DG behaviors. This finding contradicts existing literature describing the influence of gender on DG behaviors (Singelis et al., 1995; Chumbley & Griffiths, 2006; Yen et al., 2019; Anderson et al., 2017; Beard et al., 2017). Regarding the broad associations between gender differences and internet gaming motivations (aside of cultural orientation differences), research has in general emphasized that males are typically driven by achievement and immersion, while females are typically driven by social relationships (Györkös et al., 2013; Burleigh et al., 2018; Adams et al., 2018; Stavropoulos et al., 2018b; Stavropoulos et al., 2018c). However, gender-based motivations have been found to vary across cultures, as indicated by cross-cultural research (Beard & Wickham, 2016; Stavropoulos et al., 2018b). Nevertheless, gamers from westernized multicultural societies were examined here. In such societies, vertically individualistic tendencies related to the dominant culture could neutralize such gender differences, because both males and females tend to adopt motivations of achievement and ranking, which could therefore explain the results obtained (Beard & Wickham, 2016; Stavropoulos et al., 2018c; Stavropoulos et al., 2019c).
Limitations and Further Research
Despite its strengths, there are significant potential limitations to the present study. Firstly, participants held residence primarily in Australia and the USA, which may not be completely representative of the range of vertically individualistic variations. Secondly, the cross-sectional nature of the study compromises the clear causal direction between the associations examined. Thirdly, the exclusive use of self-report measures may have limited the capacity of the study to reflect clinical features of DG behavior, with the reliability of responses being vulnerable to uncontrolled factors (such as participant mood, intelligence, and situational effects).
To address these potential limitations, future research should examine a broader range of countries to capture a more diverse range of vertically individualistic variations. Additionally, qualitative approaches and longitudinal research designs are also recommended to aid estimating the reliability and accuracy of the associations revealed and to better reflect clinical features of DG across distinct segments of the global population of gamers. Finally, research should emphasize and identify protective factors associated with DG to assist the development of effective prevention and intervention strategies.
Implications and Conclusions
Considering the prevention of DG, the findings of the study suggest that gamers (particularly females) presenting with concurrent symptoms of depression and stronger vertical-individualistic orientation (with strong overlapping achievement, immersion, and social drives) should be prioritized within multicultural societies. Furthermore, the findings encountered suggest that clinical treatment of DG may benefit by targeting maladaptive cognitive and emotional-regulation tendencies associated with the gamer’s culture and gender, particularly those of vertical individualism.
In conclusion, the present study examined how symptoms of depression may precipitate DG behaviors differently, when considering the moderating effects of vertically individualistic cultural inclinations and gender within multicultural societies. Findings demonstrated that while symptoms of depression increase DG risk, a more vertically individualistic cultural orientation could exacerbate this effect, slightly more so among females than males. These emphasize the importance of understanding differences in the relationship between depression and DG risk in relation to cultural orientation, particularly in rapidly evolving multicultural societies.
Data for the current study are available upon request/contact with the corresponding author.
Adams, B. L., Stavropoulos, V., Burleigh, T. L., Liew, L. W., Beard, C. L., & Griffiths, M. D. (2018). Internet gaming disorder behaviors in emergent adulthood: A pilot study examining the interplay between anxiety and family cohesion. International Journal of Mental Health and Addiction, 17(4), 828–844.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington: American Psychiatric Publishing.
Anderson, E. L., Steen, E., & Stavropoulos, V. (2017). Internet use and problematic internet use: A systematic review of longitudinal research trends in adolescence and emergent adulthood. International Journal of Adolescence and Youth, 22(4), 430–454.
Arsenault, D. (2009). Video game genre, evolution and innovation. Eludamos. Journal for Computer Game Culture, 3(2), 149–176.
Beard, C. L., & Wickham, R. E. (2016). Gaming-contingent self-worth, gaming motivation, and internet gaming disorder. Computers in Human Behavior, 61, 507–515.
Beard, C. L., Haas, A. L., Wickham, R. E., & Stavropoulos, V. (2017). Age of initiation and internet gaming disorder: The role of self-esteem. Cyberpsychology, Behavior, and Social Networking, 20(6), 397-401. https://doi.org/10.1089/cyber.2017.0011
Burleigh, T. L., Stavropoulos, V., Liew, L. W., Adams, B. L., & Griffiths, M. D. (2018). Depression, internet gaming disorder, and the moderating effect of the gamer-avatar relationship: An exploratory longitudinal study. International Journal of Mental Health and Addiction, 16(1), 102–124.
Caplan, S. E. (2002). Problematic internet use and psychosocial well-being: Development of a theory-based cognitive–behavioral measurement instrument. Computers in Human Behavior, 18(5), 553–575.
Caplan, S., Williams, D., & Yee, N. (2009). Problematic internet use and psychosocial well-being among MMO players. Computers in Human Behavior, 25(6), 1312–1319.
Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behavior, 23(3), 1531–1548.
Chumbley, J., & Griffiths, M. (2006). Affect and the computer game player: The effect of gender, personality, and game reinforcement structure on affective responses to computer game-play. Cyberpsychology & Behavior, 9(3), 308–316.
Dong, G., & Potenza, M. N. (2014). A cognitive-behavioral model of internet gaming disorder: Theoretical underpinnings and clinical implications. Journal of Psychiatric Research, 58, 7–11. https://doi.org/10.1016/j.jpsychires.2014.07.005.
Demetrovics, Z., Urbán, R., Nagygyörgy, K., Farkas, J., Zilahy, D., Mervó, B., Reindl, A., Ágoston, C., Kertész, A., & Harmath, E. (2011). Why do you play? The development of the motives for online gaming questionnaire (MOGQ). Behavior Research Methods, 43(3), 814–825.
Elliott, L., Golub, A., Ream, G., & Dunlap, E. (2012). Video game genre as a predictor of problem use. Cyberpsychology, Behavior and Social Networking, 15(3), 155–161.
Electronic Software Association, 2019. Comprehensive industry research. Retrieved January 10, 2020, from: https://www.theesa.com/industry/essential-facts-2019/
Fam, J. Y. (2018). Prevalence of internet gaming disorder in adolescents: A meta-analysis across three decades. Scandinavian Journal of Psychology, 59, 524–531.
Ghuman, D., & Griffiths, M. D. (2012). A cross-genre study of online gaming: Player demographics, motivation for play, and social interactions among players. International Journal of Cyber Behavior, Psychology and Learning, 2(1), 13–29.
González, C. S. G., & Adelantado, V. N. (2016). A structural theoretical framework based on motor play to categorize and analyze active video games. Games and Culture, 11(7–8), 690–719.
Griffiths, M. D., Davies, M. N., & Chappell, D. (2004). Demographic factors and playing variables in online computer gaming. Cyberpsychology & Behavior, 7(4), 479–487.
Griffiths, M. D., Kuss, D. J., & Pontes, H. M. (2016). A brief overview of internet gaming disorder and its treatment. Australian Clinical Psychologist, 2(1), 20108.
Györkös, C., Becker, J., Massoudi, K., Antonietti, J. P., Pocnet, C., de Bruin, G. P., & Rossier, J. (2013). Comparing the horizontal and vertical individualism and collectivism scale and the Auckland individualism and collectivism scale in two cultures: Switzerland and South Africa. Cross-Cultural Research, 47(3), 310–331.
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Publications.
Hill, R. (1998). What sample size is “enough” in internet survey research. Interpersonal Computing and Technology, 6(3–4), 1–10.
Ho, R. C., Zhang, M. W., Tsang, T. Y., Toh, A. H., Pan, F., Lu, Y., ... & Watanabe, H. (2014). The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry, 14(1), 183.
Hoeft, F., Watson, C. L., Kesler, S. R., Bettinger, K. E., & Reiss, A. L. (2008). Gender differences in the mesocorticolimbic system during computer game-play. Journal of Psychiatric Research, 42(4), 253–258.
IGEA (2018). Digital Australia Report 2018. Retrieved January 10, 2020, from: https://www.igea.net/wp-content/uploads/2017/07/Digital-Australia-2018-DA18-Final-1.pdf
Jones, C., Scholes, L., Johnson, D., Katsikitis, M., & Carras, M. C. (2014). Gaming well: Links between videogames and flourishing mental health. Frontiers in Psychology, 5, 260.
Kaptsis, D., King, D. L., Delfabbro, P. H., & Gradisar, M. (2016). Withdrawal symptoms in internet gaming disorder: A systematic review. Clinical Psychology Review, 43, 58–66.
Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31(1), 351–354.
Kim, Y.-J., Lim, J. A., Lee, J. Y., Oh, S., Kim, S. N., Kim, D. J., Ha, J. E., Kwon, J. S., & Choi, J.-S. (2017). Impulsivity and compulsivity in internet gaming disorder: A comparison with obsessive–compulsive disorder and alcohol use disorder. Journal of Behavioral Addictions, 6(4), 545–553.
Király, O., Bőthe, B., Ramos-Diaz, J., Rahimi-Movaghar, A., Lukavska, K., Hrabec, O., et al. (2019). Ten-item internet gaming disorder test (IGDT-10): Measurement invariance and cross-cultural validation across seven language-based samples. Psychology of Addictive Behaviors, 33(1), 91–110.
Laconi, S., Kaliszewska-Czeremska, K., Gnisci, A., Sergi, I., Barke, A., Jeromin, F., et al. (2018). Cross-cultural study of problematic internet use in nine European countries. Computers in Human Behavior, 84, 430–440.
Laconi, S., Pires, S., & Chabrol, H. (2017). Internet gaming disorder, motives, game genres and psychopathology. Computers in Human Behavior, 75, 652–659.
Lafrenière, M. A. K., Verner-Filion, J., & Vallerand, R. J. (2012). Development and validation of the gaming motivation scale (GAMS). Personality and Individual Differences, 53(7), 827–831.
Lee, S. Y., Lee, H. K., & Choo, H. (2017). Typology of internet gaming disorder and its clinical implications. Psychiatry and Clinical Neurosciences, 71(7), 479–491.
Lemmens, J. S., Valkenburg, P. M., & Gentile, D. A. (2015). The Internet Gaming Disorder Scale. Psychological Assessment, 27(2), 567–582.
Liu, M., & Peng, W. (2009). Cognitive and psychological predictors of the negative outcomes associated with playing MMOGs (massively multiplayer online games). Computers in Human Behavior, 25(6), 1306–1311.
Liu, L., Yao, Y. W., Li, C. S. R., Zhang, J. T., Xia, C. C., Lan, J., ... & Fang, X. Y. (2018). The comorbidity between internet gaming disorder and depression: Interrelationship and neural mechanisms. Frontiers in Psychiatry, 9, 154.
Lopez-Fernandez, O., Griffiths, M. D., Kuss, D. J., Dawes, C., Pontes, H. M., Justice, L., ... & Männikkö, N. (2019). Cross-cultural validation of the Compulsive Internet Use Scale in four forms and eight languages. Cyberpsychology, Behavior and Social Networking, 22, 451–464.
Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the Beck depression and anxiety inventories. Behaviour Research and Therapy, 33(3), 335–343.
Masten, A. S. (2014). Invited commentary: Resilience and positive youth development frameworks in developmental science. Journal of Youth and Adolescence, 43, 1018–1024.
Mihara, S., & Higuchi, S. (2017). Cross-sectional and longitudinal epidemiological studies of internet gaming disorder: A systematic review of the literature. Psychiatry and Clinical Neurosciences, 71(7), 425–444.
Morcos, M., Stavropoulos, V., Rennies, J. J., Clark, M., & Pontes, H. M. (2019). Internet gaming disorder: Compensating as a Draenei in World of Warcraft. International Journal of Mental Health and Addiction, 1–17. https://doi.org/10.1007/s11469-019-00098-x.
Müller, K. W., Janikian, M., Dreier, M., Wölfling, K., Beutel, M. E., Tzavara, C., Richardson, C., & Tsitsika, A. (2015). Regular gaming behavior and internet gaming disorder in European adolescents: Results from a cross-national representative survey of prevalence, predictors, and psychopathological correlates. European Child & Adolescent Psychiatry, 24(5), 565–574.
Nazlıgül, M. D., Baş, S., Akyüz, Z., & Yorulmaz, O. (2018). Internet gaming disorder and treatment approaches: A systematic review. Addicta: The Turkish Journal on Addictions, 5, 13–35.
Newzoo (2017). Gaming report. Retrieved January 10, 2019, from: https://newzoo.com/insights/articles/the-global-games-market-will-reach-108-9-billion-in-2017-with-mobile-taking-42/
Petry, N. M., & O'Brien, C. P. (2013). Internet gaming disorder and the DSM-5. Addiction, 108(7), 1186–1187.
Pearcy, B. T., McEvoy, P. M., & Roberts, L. D. (2017). Internet gaming disorder explains unique variance in psychological distress and disability after controlling for comorbid depression, OCD, ADHD, and anxiety. Cyberpsychology, Behavior and Social Networking, 20(2), 126–132.
Pontes, H. M., Kiraly, O., Demetrovics, Z., & Griffiths, M. D. (2014). The conceptualisation and measurement of DSM-5 internet gaming disorder: The development of the IGD-20 Test. PLoS One, 9(10), e110137.
Pontes, H. M., & Griffiths, M. D. (2015). Measuring DSM-5 Internet gaming disorder: Development and validation of a short psychometric scale. Computers in Human Behavior, 45, 137-143. https://doi.org/10.1016/j.chb.2014.12.006
Pontes, H. M., Stavropoulos, V., & Griffiths, M. D. (2019). Emerging insights on internet gaming disorder: Conceptual and measurement issues. Addictive Behaviors Reports Epub ahead of print. https://doi.org/10.1016/j.abrep.2019.100242.
Porter, G., Starcevic, V., Berle, D., & Fenech, P. (2010). Recognizing problem video game use. Australian and New Zealand Journal of Psychiatry, 44(2), 120–128.
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227.
Singelis, T. M., Triandis, H. C., Bhawuk, D. P., & Gelfand, M. J. (1995). Horizontal and vertical dimensions of individualism and collectivism: A theoretical and measurement refinement. Cross-Cultural Research, 29(3), 240–275.
Stavropoulos, V., Gomez, R., & Motti, F. (2019a). Introduction to the special topic:“internet gaming disorder: A pathway towards assessment consensus”. Frontiers in Psychology, 10, 1822.
Stavropoulos, V., Baynes, K. L., O’Farrel, D. L., Gomez, R., Mueller, A., Yucel, M., & Griffiths, M. (2020). Inattention and disordered gaming: Does culture matter? Psychiatric Quarterly. Epub ahead of print, 1–16. https://doi.org/10.1007/s11126-019-09702-8.
Stavropoulos, V., Gomez, R., Mueller, A., Yucel, M., & Griffiths, M. (2019b). User-avatar bond profiles: How do they associate with disordered gaming? Addictive Behaviors, 103, 106245.
Stavropoulos, V., Kuss, D., Griffiths, M., & Motti-Stefanidi, F. (2016). A longitudinal study of adolescent internet addiction: The role of conscientiousness and classroom hostility. Journal of Adolescent Research, 31(4), 442–473.
Stavropoulos, V., Beard, C., Griffiths, M. D., Buleigh, T., Gomez, R., & Pontes, H. M. (2018a). Measurement invariance of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) between Australia, the USA, and the UK. International Journal of Mental Health and Addiction, 16(2), 377–392.
Stavropoulos, V., Anderson, E. E., Beard, C., Latifi, M. Q., Kuss, D., & Griffiths, M. (2018b). A preliminary cross-cultural study of hikikomori and internet gaming disorder: The moderating effects of game-playing time and living with parents. Addictive Behaviors Reports, 9, 100137.
Stavropoulos, V., Griffiths, M. D., Burleigh, T. L., Kuss, D. J., Doh, Y. Y., & Gomez, R. (2018c). Flow on the internet: A longitudinal study of internet addiction symptoms during adolescence. Behaviour & Information Technology, 37(2), 159–172.
Stavropoulos, V., Adams, B. L., Beard, C. L., Dumble, E., Trawley, S., Gomez, R., & Pontes, H. M. (2019c). Associations between attention deficit hyperactivity and internet gaming disorder symptoms: Is there consistency across types of symptoms, gender and countries? Addictive Behaviors Reports, 9, 100158.
Stavropoulos, V., Dumble, E., Cokorilo, S., Griffiths, M. D., & Pontes, H. M. (2019d). The physical, emotional, and identity user-avatar association with disordered gaming: aApilot study. International Journal of Mental Health and Addiction, 1–13 Epub ahead of print. https://doi.org/10.1007/s11469-019-00136-8.
Taymur, I., Budak, E., Demirci, H., Akdağ, H. A., Güngör, B. B., & Özdel, K. (2016). A study of the relationship between internet addiction, psychopathology and dysfunctional beliefs. Computers in Human Behavior, 61, 532–536.
Triandis, H. C. (1996). The psychological measurement of cultural syndromes. American Psychologist, 51(4), 407–415.
Triandis, H. C., & Gelfand, M. J. (1998). Converging measurement of horizontal and vertical individualism and collectivism. Journal of Personality and Social Psychology, 74(1), 118.
Triandis, H. C. (2018). Individualism and collectivism. London: Routledge.
Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221–243.
Vargas, J. H., & Kemmelmeier, M. (2013). Ethnicity and contemporary American culture: A meta-analytic investigation of horizontal–vertical individualism–collectivism. Journal of Cross-Cultural Psychology, 44(2), 195–222.
Wan, C. S., & Chiou, W. B. (2006). Why are adolescents addicted to online gaming? An interview study in Taiwan. Cyberpsychology & Behavior, 9(6), 762–766.
Widyanto, L., & McMurran, M. (2004). The psychometric properties of the Internet Addiction Test. Cyberpsychology & Behavior, 7(4), 443–450.
Winkler, A., Dörsing, B., Rief, W., Shen, Y., & Glombiewski, J. A. (2013). Treatment of internet addiction: A meta-analysis. Clinical Psychology Review, 33(2), 317–329.
Woelfling, K., Thalemann, R., & Gruesser-Sinopoli, S. M. (2008). Computer game addiction: A psychopathological symptom complex in adolescence. Psychiatrische Praxis, 35(5), 226–232.
World Health Organization (2018). ICD-11 beta draft: Gaming disorder. Retrieved January 10, 2020, from: https://www.who.int/features/qa/gaming-disorder/en/
Yee, N., Ducheneaut, N., & Nelson, L. (2012). Online gaming motivations scale: Development and validation. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 2803–2806). New York: ACM.
Yen, J. Y., Lin, H. C., Chou, W. P., Liu, T. L., & Ko, C. H. (2019). Associations among resilience, stress, depression, and Internet gaming disorder in young adults. International Journal ofEenvironmental Research and Public Health, 16(17), 3181. https://doi.org/10.3390/ijerph16173181
Young, K. S., & Rogers, R. C. (1998). The relationship between depression and internet addiction. Cyberpsychology & Behavior, 1(1), 25–28.
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O’Farrell, D.L., Baynes, KL., M. Pontes, H. et al. Depression and Disordered Gaming: Does Culture Matter?. Int J Ment Health Addiction (2020). https://doi.org/10.1007/s11469-020-00231-1
- Gaming disorder
- Gaming addiction
- Vertical individualism