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Gaming Disorder was included as an addictive disorder in the latest version of the International Classification of Diseases (ICD-11), published in 2022. The present study aimed to develop a screening tool for Gaming Disorder, the Gaming Disorder Identification Test (GADIT), based on the four ICD-11 diagnostic criteria: impaired control, increasing priority, continued gaming despite harm, and functional impairment. We reviewed 297 questionnaire items from 48 existing gaming addiction scales and selected 68 items based on content validity. Two datasets were collected: 1) an online panel (N = 803) from Australia, United States, United Kingdom and Canada, split into a development set (N = 589) and a validation dataset (N = 214); and 2) a university sample (N = 408) from Australia. Item response theory and confirmatory factor analyses were conducted to select eight items to form the GADIT. Validity was established by regressing the GADIT against known correlates of Gaming Disorder. Confirmatory factor analyses of the GADIT showed good model fit (RMSEA=<0.001–0.108; CFI = 0.98–1.00), and internal consistency was excellent (Cronbach's alphas = 0.77–0.92). GADIT scores were strongly associated with the Internet Gaming Disorder Test (IGDT-10), and significantly associated with gaming intensity, eye fatigue, hand pain, wrist pain, back or neck pain, and excessive in-game purchases, in both the validation and the university sample datasets. The GADIT has strong psychometric properties in two independent samples from four English-speaking countries collected through different channels, and shown validity against existing scales and variables that are associated with Gaming Disorder. A cut-off of 5 is tentatively recommended for screening for Gaming Disorder. [ABSTRACT FROM AUTHOR]

Background and Aims: 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. Methods: 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. Results: 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. [ABSTRACT FROM AUTHOR]

Background: Gaming Disorder (GD) is a newly listed addictive disorder in ICD-11. Its diagnosis requires the presence of (i) impaired control (IC) over gaming, (ii) increasing priority (IP) over other activities, (iii) continued gaming (CG) despite adverse consequences, (iv) demonstrable impairment (IM), and (v) a course of 12 months or more. This presentation will describe the nature and characteristics of GD, how it compares with substance use disorders in ICD-11, and will present the findings from a four-country study which aimed to identify key features that contribute to the assessment and diagnosis of GD. Method: A sample of 796 adults who played online games for at least three hours per week was recruited from Australia, Canada, the United States and the United Kingdom. Participants completed a survey of GD features (76 items) and measures of duration and frequency of gaming. After exploratory factor analysis, GD domains were appraised by Item Response Theory (IRT) analyses. Results: Items which reflected the more severe end of the IC spectrum included (i) gaming despite others pleading, and (ii) spending more money than was affordable (IRT coefficients >0.5), whereas longer duration or more frequent gaming reflected the milder end (~0.2). IP items reflecting more severe gaming included (i) losing an important relationship and (ii) forgetting to eat (0.6-0.7). For CG this was continued gaming despite evident problems with family or friends (0.6). The most severe IM items included (i) trouble at school or work and (ii) lost relationships (0.9-1.0), whereas sleep disturbance and physical pain represented the less severe end (0.5). Conclusions: Within the GD symptom domains, there is a wide spectrum of severity. Caution must be taken in devising screening and diagnostic instruments not to include items that are commonly seen across a spectrum of videogamers in order to avoid diagnostic hyperinflation. [ABSTRACT FROM AUTHOR]

A coherent framework for addressing risk arising from new technologies is needed. In proposing a framework of broad application and future focus, where empirical evidence is scarce, reliance on strong theory becomes all the more important. Some technologies are more prone to excessive engagement than others (i.e. more addictive). Some users are also more susceptible to excessive engagement than others. Impulsivity theory emphasises the importance of reinforcement magnitude in determining the risk associated with a new technology, and that an individual's sensitivity to reinforcement (reward drive) and capacity to inhibit previously reinforced behaviour (rash impulsiveness) determines their susceptibility to problematic engagement. Online gaming provides a good example of how such theory can be applied to facilitate intervention efforts and develop policy. [ABSTRACT FROM AUTHOR]

It has already been more than three years since it was decided that gaming disorder be included in ICD-11. At that time, there were objections from the game industry and some related academia, and it was a social issue. However, such discussions were not conducted in scientific ways or produced productive conclusions. This is also due to the lack of a basis for the biological pathophysiology of behavioral addiction, but there was also a limitation that the opposition originated from the interests of the digital media industry such as games. In any case, health problems caused by excessive use of games are an existential problem, so mental and behavioral health experts in each country, including the WHO consultation team, have continued to make their own efforts to develop the diagnosis, prevention, and treatment system of gaming disorders. In particular, in the area of the diagnostic system, the WHO consultation team conducted well-designed research internationally, and standardized diagnostic interview tools were almost developed. In addition, a similar type of behavioral addiction-related monitoring system to the Global Information System on Alcohol and Health is being discussed. In addition, there are cases in which prevention policies and responses to game addiction are well underway in various countries such as Indonesia, Japan, and Switzerland. The WHO Symposium introduces these efforts, and aims to help behavioral addiction experts from each country share information with each other and effectively cope with game addiction problems. [ABSTRACT FROM AUTHOR]