مقاله انگلیسی ارزیابی روانسنجی نسخه روسی مقیاس اختلال بازی برای نوجوانان
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Appendix 1: The Russian version of the Gaming Disorder Scale for Adolescents
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Abstract
Problematic gaming has become an emerging global health issue. Formal recognition of gaming disorder in the ICD-11 is a new opportunity for the discipline to conduct further investigation concerning the psychological consequences of problematic gaming. The present study investigated the psychometric properties and construct structure of the recently developed Gaming Disorder for Scale for Adolescents (GADIS-A), a multi-dimensional instrument that screens for gaming disorder symptoms, among Russian adolescent gamers. The sample comprised 933 adolescent gamers (547 boys and 386 girls) recruited via a web-based platform, using a multistage sampling method. Analysis showed the GADIS-A had very good internal consistency (Cronbach’s alpha coefficient = .891; Composite reliability = .89) and adequate test–retest reliability after two weeks (intraclass coefficient =0.68 with 95% CI [0.61, 0.77]. Exploratory structural equation modeling (ESEM) showed the data fitted well. Measurement invariance testing indicated the GADIS-A was invariant by gender and gaming medium (online vs. offline). As for criterion-related validity, high scores on the GADIS-A positively correlated with scales assessing depression, anxiety, impulsivity, and difficulties in emotion regulation, and negatively correlated with social connectedness and life satisfaction. Using latent profile analysis, four groups of gamers were identified, and problematic gaming was associated with greater mental health problems. The findings indicated that psychological comorbidity (e.g., depression and anxiety) was more prevalent among gamers with higher risk of GD. The findings indicate that GADIS-A is a reliable and valid instrument to assess the symptoms and severity of gaming disorder among Russian adolescents.
Background
The substantial development of digital technologies has generated many opportunities for social interaction, educational activities, and leisure (e.g., gaming), and has led to major societal and individual changes (Kuss & Billieux, 2017; van Laer & Van Aelst, 2010). However, there is now a sizeable empirical base demonstrating that human-technology interactions can be problematic and/or addictive for a small minority of individuals (Cheng et al., 2018; Shi et al., 2019). For a minority of adolescents, problematic gaming has become an emerging global health issue. Gaming behavior may be viewed as being on a continuum with non-problematic gaming at one end and problematic (i.e., addictive or pathological) gaming at the other (Griffiths et al., 2017). Epidemiological studies have reported prevalence rates of pathological gaming among adolescents ranging from 1% to 6% across Asia, Australia, and Europe (Anthony et al., 2020; Sugaya et al., 2019). Moreover, research into GD has substantially grown on a global level. However, comparison and interpretation of findings can be difficult due to methodological issues such as heterogeneity among the many different screening tools (Pontes et al., 2021).