Almost 4.54 billion people are nowadays connected to the Internet, and about half of the world's population, 3.8 billion people, regularly use social networks, an increase of about 9% compared to 2019 (Digital, 2020). According to ISTAT data (2019), 76.1 of households in Italy have Internet access, and almost all 15–24-year-old browse the Web (over 90%), with lower rates of access among later age groups. The Covid-19 pandemic has also widened the digital divide between those included and those excluded from the community network (Beaunoyer et al., 2020).
Over the last 15 years, research on new technologies addiction has increased exponentially, although the phenomenon of Internet Addiction (IA) has not yet been unequivocally outlined (cf. Yellowlees & Marks, 2007). Due to the widespread use of the Internet, especially among young people, research on IA has focused on adolescents, stressing individual and relational risk factors. More specifically, the most at-risk youngsters show low social openness, reduced emotional intelligence, and a liking for secluded activities (Young & Rodgers, 1998; Kircaburun et al., 2020). Other risk factors are a high level of perceived loneliness (Morahan-Martin & Schumacher, 2000) and the presence of depressive traits with suicidal ideation (Kraut et al., 1998; Yu et al., 2020). In this respect, Caplan (2007) introduced the term "Preference for Online Social Interaction" (POSI) in order to describe adolescents perceiving themselves as safer, more effective, more confident, and more comfortable in online interaction than in traditional face-to-face interactions. A recent study investigated the relationship among social anxiety, motivation, and POSI and suggested that metacognitions may play an essential role in the association between social anxiety and Internet Gaming Disorder (IGD), along with POSI (Marino et al., 2020). Moreover, a permissive parenting style can be included in environmental risk factors (Maftei & Enea, 2020).
IA's worldwide prevalence is reported to be around 6%, with peaks of 10.9% in the Far East and lower rates in Europe (2.6%; cf. Cheng & Li, 2014). Another analysis focused on the prevalence rates of IA and gaming disorders in Southeast Asia revealed an aggregate prevalence rate of 20% for IA and 10.1% for IGD (Chia et al., 2020).
In terms of developmental outcomes, the disorder has been associated with: identity shortfalls (Kim et al., 2012), brain structure alterations (Lin et al., 2012; Wang et al. (2020), impairments in cognitive functioning (Park et al., 2011), risk-seeking behavior (Tsitsika et al., 2011; Dong & Potenza, 2016), low quality of interpersonal relationships (Milani, Osualdella, & Di Blasio, 2009), eating disorders (Kim et al., 2010; Hadwiger et al., 2019), internalizing symptoms (Pace, D'Urso, & Zappulla, 2019) and self-harming behavior (Lam et al., 2009; Tang et al., 2020).
DSM-5 introduced the diagnosis of IGD in the third section of the manual, which partly included some of Internet Addiction characteristics. IGD is defined as a form of pathological video game addiction with characteristics typical of behavioral addictions (Kuss & Griffiths, 2012), characterized by nine diagnostic criteria, such as abstinence, tolerance, loss of control over gaming behavior, use of games in order to shun unpleasant emotional states, jeopardizing of a relationship, an educational or work opportunity because of the gaming habits.
Internet Gaming Disorder: prevalence and patterns
Video gaming is a hobby enjoyed by young and old across the globe. In 2020, there were an estimated 2.7 billion gamers across the world (Newzoo, 2020). There were almost 1.5 billion gamers in the Asia Pacific region, making it the largest for video gaming worldwide. In Europe, they were 386 million, making it the second-largest region for video gaming. In Italy, according to a survey conducted by IIDEA (Italian Interactive Digital Entertainment Association) in 2019, people who used video games were 39% of the entire population aged between 6 and 64 years, playing on average 7.4 hours per week. The most used gaming platforms are mobile devices such as smartphones and tablets. In youngsters aged 11-14, 26% use handheld consoles, 41% computers, 49% tablets, 53% smartphones, and 64% consoles (Italian Interactive Digital Entertainment Association, 2020).
Research investigating the prevalence of Internet Gaming Disorder (IGD) shows it is higher for males (Wartberg, Kriston, Thomasius, 2020), and it is more widespread in Asian countries (Van Rooij et al., 2014; Chia et al. 2020). The prevalence appears to range between 3.4% and 6.4%, with a high discrepancy between males (6.8%) and females (1.3%) (Fam, 2018). The highest prevalence was found in the Asian population: 17.5% for male adolescents and 7.9% for female adolescents (Jang et al., 2020). Early Italian data (Milani et al. 2018) indicate a prevalence of subthreshold risk (3 out of 9 symptoms) in 15.2% and diagnosis (5 out of 9 symptoms) in 2.1%. The data also indicate a different prevalence according to gender: males seem to be more at risk for IGD, females seem to be more vulnerable to IA.
Although the time spent gambling is a potential risk factor for addiction development, this is not a diagnostic criterion. There is a consensus that addicted gamblers spend more time gambling than the control population (cf. Gentile et al., 2011; Lemmens & Hendriks, 2016). However, more than the time itself, a more relevant risk factor seems to be the gaming habits, i.e., gaming sessions at unusual times of the day (at night during the working week; Triberti et al., 2018; Musetti et al., 2019).
Other risk factors not related to gaming that may influence IGD development appear to be male gender (Van Rooij et al., 2014; Su et al., 2020), neuroticism as a personality trait (Wang, Ho, Chan, & Tse, 2015; Gonzáles-Bueso et al., 2020), inclination to aggressiveness and acceptance of violence (Müller et al., 2015; Jeong et al., 2020; Paulus et al., 2018). Other research highlights the following among the risk factors associated with IGD: online relationship and friendship seeking (Caplan, Williams, & Yee, 2009; Kardefelt-Winther, 2014), immersion and dissociation seeking (Snodgrass, Dengah, Lacy, & Fagan, 2013; Snodgrass et al., 2018), use of the game as a coping and escape strategy from everyday stressors and negative emotions (Cole & Hooley, 2013; King, Delfabbro, & Griffiths, 2011; Kuss, Louws, & Wiers, 2012; Li, Liau, & Khoo, 2011; Milani et al., 2018).
About consequences of IGD in terms of maladaptive outcomes, the literature shows that youths at risk of gaming addiction tend to prefer mediated and virtual relationships over face-to-face ones (Hussain & Griffiths, 2009) and are characterized by behavioral problems (Brunborg et al., 2014), ADHD (Kim et al., 2020; Chang et al., 2020), low performance at school (Jeong & Kim, 2011; Sugaya et al. (2019), risk of alcohol and substance abuse (Van Rooij et al., 2014; Wenzel, Bakken, Johansson, Götestam & Øren, 2009).
Finally, concerning symptomatology, there is evidence of an association between IGD and depressive and mood-deflection signs (Brunborg et al. 2014, Van Rooij et al. 2014; Wenzel, Bakken, Johansson, Götestam & Øren, 2009; Ostinelli et al., 2021), symptoms related to anxiety and panic disorders (Cole & Hooley, 2013; Rehbein et al., 2010; Walther, Morgenstern & Hanewinkel, 2012; Wang et al. (2017), low self-esteem (Lemmens, Valkenburg & Peter, 2011; Wartberg et al., 2019), somatization (Allison et al. 2006; Dworak, Schierl, Bruns, Struder, 2007; Cerniglia et al., 2019), impulsivity (Walther et al., 2012; Hu et al., 2017), irritability and aggressiveness (Ko et al., 2009; Milani et al., 2018), as well as ADHD (Batthyány, Müller, Benker & Wölfling, 2009; Evren et al., 2019).
Migratory background and developmental risk
The significance of ethnicity in migrant children's development is substantial (Valtolina, 2013). Ethnic belonging is related to all physiological and psychological changes of human development, mainly affecting family and peer relationships (Henneberger et al., 2016; Graham & Echols, 2018). So, although with significant differences depending on several variables (place of birth, country of origin, integration, family aim, etc.), children with the migratory background are thought to be at significant developmental risk, with psychological distress and risk-taking behaviors, such as smoking, drinking, drug addiction, IA (Kouider, Koglin & Petermann, 2014; Nakash et al., 2012).
Several studies (Verkuyten, 1998; Pascoe & Richman, 2009; Bilgin, 2017; Giuliani, Tagliabue & Regalia, 2018; Motto-Stefanidi, Pavlopoulos & Asendorpf, 2018) highlight how migrant children are often discriminated, with negative implications for their development and psychological well-being. Moreover, other elements are relevant: the effects of migration trauma, such as the stress resulting from the loss of family and friends, the radical change of daily habits; the acculturation stress (Berry, 2006), i.e., the stress resulting from dealing with a new culture, very often completely different from the family culture (Guarnaccia & Lopez, 1998; Stevens & Vollebergh, 2008; Walsh, Shulman, & Maurer, 2008; Kien et al., 2018). The stress associated with the acculturation process can lead some youngsters to increase risk behaviors (Barbato et al., 2013; Boerchi, 2014; Cristini et al., 2015; Betancourt, Frounfelker, Mishra, Hussein & Falzarano, 2015; Motto-Stefanidi, 2018).
So, as some scholars did (Canale et al., 2017), it could be said that adolescents with a migrant background show more behavioral problems than native adolescents, also regarding IGD. Although this phenomenon's nosological classification is still a matter of debate, it is argued that IGD might be described as a non-substance-related addiction. Epidemiological surveys reveal that it affects up to 3% of adolescents and seems to be related to psychosocial symptoms (Müller et al., 2015).
IGD and IA are not exclusive to offspring of migrant parents, but also migrant unaccompanied minors, a significant portion of the migratory flow towards Europe, mainly in recent years (Valtolina & Boerchi, 2019).
Since several studies highlighted the vulnerability of migrants to behavioral addiction such as gambling disorder (Stinchfield, 2000; Ellenbogen, Gupta, & Derevensky, 2007; Hayer & Griffiths, 2016; Canale et al., 2017; Gainsbury, 2017; Wardle et al., 2019), it is crucial to assess whether this vulnerability also includes technological dependencies.
Furthermore, it should be considered that gaming addiction is chronic: Gentile et al. (2011) emphasized that over 80% of pathological gamers are out of control for at least two years. Therefore, video game addiction is an issue that needs to be further investigated, especially in young people with a migrant background, due to its severe consequences on development and mental health.
The Present Study
The study here presented intends to collect preliminary data on the prevalence of technological addictions in a population of students with a migratory background compared to Italian ones and identify possible maladaptive correlations of the disorders. For the research, we decided to verify both the prevalence and characteristics of IGD – a diagnosis consolidated in the literature and present in the DSM-5 – and the Internet Addiction construct, as it is still widely considered even in the academic field.
The study's objectives can be summarized as follows:
testing the differences between Italian and migrant students in terms of problematic use of videogames and the Internet:
identifying any risk factors predicting the emergence of problematic involvement in videogame activities and Internet use.
The present study intends to investigate both the differences in the distribution of addictions between students with Italian citizenship (ITA) and those without Italian citizenship (WIC) as well as between males and females and the role coping strategies and interpersonal relationships can play in increasing addiction to video games and the Internet.
More precisely, we will test the following hypotheses, formulated following the literature on the subject:
1) WIC students' scores in terms of IGD and Internet addiction will be higher than ITA students' scores;
2) male students' scores for IGD will be higher than females students' scores, while female students' score for Internet addiction will be higher than male students' scores;
3) male and female students' scores about IGD and Internet addiction will not be different regarding their citizenship;
4) both IGD and Internet addiction scores will increase with age;
5) maladaptive coping strategies will contribute to predict both IGD and Internet addiction;
6) the quality of interpersonal relationships will contribute to contrast IGD and Internet addictions.
532 students participated in the study. After controlling for outliers with the Mahalanobis method, 14 of them (2.6%) were not considered for the following analysis. Age ranged from 9 to 20 y.o. (M = 15.80; DS = 2.161) attending different types and orders of schools in four big Italian cities (Brescia, Milano, Roma, and Verona). Gender was not equally distributed, with females more represented than males (F = 64.5%; M = 35.5%). Fifty students (9.7%) had no Italian citizenship, 18 originating in Europe and 32 in Extra-European countries. ITA and WIC groups were similar by age (t(516) = -1.526, p = .128), and gender (χ2(1) = .006, p = .941).
Participants compiled the following questionnaires:
- Revised Video Games Addiction Questionnaire (VGA; Gentile et al., 2012), composed of 16 items on a 3-point Likert scale, aimed to identify the possible presence of problematic and uncontrolled use of video games (both online and offline). Cronbach’s Alpha was acceptable (α = .71).
- Internet Addiction Test (IAT, Young, 1998), composed of 20 items on a 5-point Likert scale, aimed to investigate how the use of the Internet can affect social life, academic and job career quality, and time control. Cronbach's Alpha was good (α = . 89).
- Children's Coping Strategies Checklist (CCSC, Ayers & Sandler, 1999; Italian adaptation of Camisasca et al., 2012), composed of 54 items on a 4-point Likert scale, aimed to test children and adolescents' ability to cope with stress by mean of the use of cognitive coping strategies (active coping, distraction strategies, avoidance strategies, support seeking strategies). Cronbach's Alpha was excellent (α = . 90).
Assessment of Interpersonal Relations (AIR, Bracken, 1997) measures adolescents' interpersonal competence in relationships with peers and with adult figures. The questionnaire comprises five subscales (relationship with the mother, with the father, with the female peers, with the male peers, and with the teachers) composed of the same 35 items on a 4-point Likert scale. Cronbach's Alpha was excellent (α = . 95).
The study was presented to the students indicating that its goal was to investigate their behaviors related to video games and the use of the Internet, and how they deal with life events and people closest to them. Subsequently, their parents were given a letter of presentation of the study and a form to collect their informed consent signed by both parents. The questionnaire's administration to the students took place in group mode in the classrooms and during school hours. Participation was voluntary, and participants were informed of the possibility of withdrawing from the collaboration at any time. Data was collected prior to the Covid-19 pandemic.
The first three hypotheses were tested by the Analysis of the Variance, separately for IGD and IA, considering nationality and gender interactions.
A path analysis model tested the remaining hypotheses with coping strategies, quality of the relationships, age, and gender correlating themselves and affecting IGD and IA separately.
We tested the metric measurement invariance (Steenkamp, & Baumgartner, 1998) of the ITA and WIC models through multigroup CFAs with the maximum likelihood method and AMOS software to test if the factor loadings were equal in ITA and WIC groups. We compared fit indexes to test if the two models were not different. Δχ2 should not be significant, ΔCFI should be lower than .010 (Chen, 2007). Because the model had zero degrees of freedom for the unconstrained model, χ2 was zero, and CFI was one.
Even if, due to the small size of the WIC group, some analyses were not statistically significant, we believe that, in line with the ASA's statement on p-values (Wasserstein & Lazar, 2016), the conditions exist to consider useful some of the results obtained for the scientific debate.