
The rise and growing popularity of online games has led to the appearance of excessive gaming that in some cases can lead to physical and psychological problems. Several measures have been developed to explore the nature and the scale of the phenomenon. However, few measures have been validated psychometrically. The aim of the present study was to test the psychometric properties of the 12-item Problematic Online Gaming Questionnaire Short-Form (POGQ-SF) and to assess the prevalence of problematic online gaming. Data collection was carried out to assess the prevalence of problematic online gaming in a national representative adolescent sample by using an offline (pen and pencil) method. A total of 5,045 secondary school students were assessed (51% male, mean age 16.4 years, SD=0.9 years) of which 2,804 were gamers (65.4% male, mean age 16.4 years, SD=0.9 years). Confirmatory factor analysis was applied to test the measurement model of problematic online gaming, and latent profile analysis was used to identify the proportion of gamers whose online game use can be considered problematic. Results showed that the original six-factor model yielded appropriate fit to the data, and thus the POGQ-SF has appropriate psychometric properties. Latent profile analysis revealed that 4.6% of the adolescents belong to a high risk group and an additional 13.3% to a low risk group. Due to its satisfactory psychometric characteristics, the 12-item POGQ-SF appears to be an adequate tool for the assessment of problematic online gaming.
Male, Adolescent, Psychometrics, Data Collection, BF Psychology / lélektan, Self Concept, Behavior, Addictive, Risk-Taking, Sex Factors, Video Games, Adolescent Behavior, Surveys and Questionnaires, Prevalence, Humans, Recreation, Female, Factor Analysis, Statistical
Male, Adolescent, Psychometrics, Data Collection, BF Psychology / lélektan, Self Concept, Behavior, Addictive, Risk-Taking, Sex Factors, Video Games, Adolescent Behavior, Surveys and Questionnaires, Prevalence, Humans, Recreation, Female, Factor Analysis, Statistical
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