An important proportion of infants and adolescents in Japan are using Internet-equipped devices, including smartphones, tablets, and game consoles. However, the relationship between the risk of IA and the age at initial habitual Internet use remains unknown. We aimed to investigate this relationship among adolescents.
We surveyed 1,775 subjects in seven public junior high schools in Kanagawa prefecture, Japan, in November 2017. Students were asked to complete the Young's Diagnostic Questionnaire (YDQ), which captured information regarding gender, school grade, night sleep, age at which they first started using the Internet at least once weekly, Internet usage situation, and Internet use time for purposes other than study. Data from subjects who reported experience of weekly Internet use were analyzed.
Junior high school students who were younger at initial weekly Internet use tended to have problematic Internet use (PIU) and to spend more time on Internet activities. In particular, initial weekly Internet use before the age of five in boys was associated with a significantly increased risk of PIU (YDQ ≥ 5), with an odds ratio of 14.955, compared with initial weekly Internet use after the age of 12. Smartphone ownership significantly increased the risk of PIU compared with no ownership among the total population and among girls.
Discussion and Conclusions
Junior high school male students displayed a robust relationship between initial weekly Internet use and PIU, whereas junior high school female students displayed a particularly strong relationship between smartphone ownership and PIU. Therefore, longitudinal IA preventive education from an early age is necessary.
Data from a specialist treatment facility for Internet addiction (IA) in Japan showed that (a) the vast majority of treatment seekers are addicted to online games, (b) their symptoms are often quite severe, and (c) there is a significant demand for IA treatment. In addition, systemic obstacles to the delivery of medical services in Japan exist due to the exclusion of IA criteria from ICD-10. Consequently, the inclusion of GD criteria in ICD-11 will almost certainly increase the capacity and quality of treatment through advances in research and possible changes in national medical systems to meet treatment demand.
The World Health Organization included gaming disorder (GD) in the eleventh revision of International Classification of Diseases in 2019. Due to the lack of diagnostic tools for GD, a definition has not been adequately applied. Therefore, this study aimed to apply an operationalized definition of GD to treatment-seekers. The relationship between the diagnoses of GD and Internet gaming disorder (IGD) in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders was also examined. Methods: Study participants comprised 241 treatment-seekers who had engaged in excessive gaming and experienced related problems. Psychiatrists applied the GD diagnostic criteria to the participants using a diagnostic form developed for this study. Information on gaming behavior and functional impairment was obtained through face-to-face interviews conducted by clinical psychologists. Results: In total, 78.4 and 83.0% of the participants fulfilled the GD and IGD diagnostic criteria, respectively. The sensitivity and specificity of GD diagnosis were both high when the IGD diagnosis was used as the gold standard. Participants with GD preferred online PC and console games, spent significantly more time gaming, and showed a higher level of functional impairment compared to those who did not fulfill the GD diagnostic criteria. Discussion and Conclusion: The definition of GD can be successfully applied to treatment-seekers with excessive gaming and related problems. A high concordance of GD and IGD diagnoses was found in those participants with relatively severe symptoms. The development and validation of a diagnostic tool for GD should be explored in future studies.
Although the Ten-Item Internet Gaming Disorder Test (IGDT-10) has been translated into Japanese and widely used, the Japanese version has not previously been validated. We used the clinical diagnosis of IGD as a gold standard for validating the test.
The Japanese version was validated using 244 gamers drawn from the general young population in Japan. Expert interviews using the Japanese version of the Structured Clinical Interview for Internet Gaming Disorder evaluated diagnoses of Internet gaming disorder (IGD). This resulted in a diagnosis of IGD for eight individuals, categorized as the gold standard group. The screening performance of the two Japanese versions with different scoring conditions was examined: the scoring method proposed by the original study (original version) and a less stringent scoring method where responses of either “often” or “sometimes” were regarded as affirmative (modified version).
The results of the sensitivity and specificity analyses, the Cronbach's alpha and the receiver operating characteristics analysis revealed a higher screening performance for the modified versus the original version. The optimum cutoff for the modified version was 5 or more – the sensitivity, specificity, and Youden's index were 87.5, 85.2, and 72.7%, respectively. The rate of probable IGD using the original and modified versions were 1.8% and 11.3%, respectively.
Discussion and conclusion
A less stringent scoring method for the Japanese version of IGDT-10 showed a higher screening performance than the original scoring method. Future studies comprising different ethnic groups and gaming cultures should further examine the suggested scoring method.
A definition of gaming disorder (GD) was introduced in ICD-11. The purpose of this study was to develop a short screening test for GD, utilizing a reference GD group. It also sought to estimate the prevalence of GD among individuals, representative of the general young population in Japan.
Two hundred eighty one men and women selected from the general population, aged between 10 and 29 years, and 44 treatment seekers at our center completed a self-reported questionnaire comprising candidate questions for the screening test. The reference group with ICD-11 GD was established, based on face-to-face interviews with behavioral addiction experts, using a diagnostic interview instrument. The questions in the screening test were selected to best differentiate those who had GD from those who did not, and the cutoff value was determined using the Youden index.
A nine-item screening test (GAMES test) was developed. The sensitivity and specificity of the test were both 98% and the positive predictive value in the study sample was 91%. The GAMES test comprised two factors, showed high internal consistency and was highly reproducible. The estimated prevalence of GD among the general young population was 7.6% (95% confidence interval; 6.6–8.7%) for males and 2.5% (1.9–3.2%) for females, with a combined prevalence of 5.1% (4.5–5.8%).
Discussion and Conclusion
The GAMES test shows high validity and reliability for screening of ICD-11 GD. The estimated prevalence of 5.1% among the general young population was comparable to the pooled estimates of young people globally.