Validating the Gaming Disorder Identification Test in English, Chinese, Dutch and Indonesian

Abstract Background and aims Gaming disorder has been formally recognised in the International Classification of Diseases , 11th Revision (ICD‐11), but purpose‐designed and internationally validated screening tools remain limited. We aimed to assess the psychometric properties of the Gaming Disorder Identification Test (GADIT) to screen for past 12 months gaming disorder across multiple languages and countries. Design Cross‐sectional multi‐country online survey. Setting and participants 1522 adults aged ≥18 who played video games at least 3 hours per week (303 from Australia; 314 from China; 300 from Indonesia; 303 from the Netherlands; and 302 from the USA). Measurements The (English) GADIT is an eight‐item self‐report questionnaire based on a selection from 25 items measuring the four ICD‐11 essential features of gaming disorder. The 25 items were translated into Chinese, Dutch and Indonesian. We conducted: (1) four item response theory (IRT) analyses and reliability assessments for the items of each of the four ICD‐11 criteria for gaming disorder based using the 25 items (inclusive of the eight GADIT items); (2) a multi‐group confirmatory factor analysis across countries using the 8 GADIT items (2 from each ICD criterion, same selection across all countries); (3) six separate IRT analyses for each of the five countries and one analysis for all countries combined using the 8 GADIT items; and (4) validity tests of the association between GADIT and measures with an expected correlation with it, including the Internet Gaming Disorder Test (IGDT‐10 total score), depression score (Patient Health Questionnaire‐2), anxiety score (GAD‐2), gaming intensity (high/low) and gaming‐related financial problems (yes/no). Results Items measuring the four gaming disorder criteria had good internal consistency (α ≥ 0.85). Multi‐group confirmatory factor analysis of the 8 items indicated factor loading invariance across countries [χ 2 (28) = 19.36, P = 0.886; root mean square error of approximation = 0.054; comparative fit index = 0.986; Tucker‐Lewis Index = 0.984]. There was lower sensitivity for the physical complaint items in China and Indonesia compared with Australia, Netherlands and USA. Overall, the 8‐item GADIT had strong concurrent validity with the IGDT‐10 [regression coefficient (b) = 0.67, coefficient of determination (R 2 ) = 52%] and was statistically significantly associated with depression (b = 0.38, R 2 = 21%), anxiety (b = 0.35, R 2 = 20%), gaming intensity [odds ratio (OR) = 3.11, 95% confidence interval (CI) = 2.72–3.60] and gaming‐related financial problems (OR = 3.11, 95% CI = 2.70–3.59). Summary The 8‐item Gaming Disorder Identification Test screening tool in Chinese, Dutch and Indonesian translation generally demonstrates robust psychometric properties and high validity, but cultural and/or language minor modifications may further improve international use.

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Publication Details

Journal
Addiction
Published
2026-09-17
DOI
https://doi.org/10.1111/add.70602
Primary Topic
Impact of Technology on Adolescents
Type
article
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article

Validating the Gaming Disorder Identification Test in English, Chinese, Dutch and Indonesian

Anne Marije Kaag, Kristiana Siste, Na Zhong, John B. Saunders et al.
Addiction
Impact of Technology on Adolescents
article

Validating the Gaming Disorder Identification Test in English, Chinese, Dutch and Indonesian

Anne Marije Kaag, Kristiana Siste, Na Zhong, John B. Saunders, Janni Leung, Daniel Stjepanović, Caitlin McClure‐Thomas, Wim van den Brink, Pim Widdershoven, Jiang Long, Gary Chung Kai Chan, Stephanie Fong, Min Zhao
article en

Abstract

Abstract Background and aims Gaming disorder has been formally recognised in the International Classification of Diseases , 11th Revision (ICD‐11), but purpose‐designed and internationally validated screening tools remain limited. We aimed to assess the psychometric properties of the Gaming Disorder Identification Test (GADIT) to screen for past 12 months gaming disorder across multiple languages and countries. Design Cross‐sectional multi‐country online survey. Setting and participants 1522 adults aged ≥18 who played video games at least 3 hours per week (303 from Australia; 314 from China; 300 from Indonesia; 303 from the Netherlands; and 302 from the USA). Measurements The (English) GADIT is an eight‐item self‐report questionnaire based on a selection from 25 items measuring the four ICD‐11 essential features of gaming disorder. The 25 items were translated into Chinese, Dutch and Indonesian. We conducted: (1) four item response theory (IRT) analyses and reliability assessments for the items of each of the four ICD‐11 criteria for gaming disorder based using the 25 items (inclusive of the eight GADIT items); (2) a multi‐group confirmatory factor analysis across countries using the 8 GADIT items (2 from each ICD criterion, same selection across all countries); (3) six separate IRT analyses for each of the five countries and one analysis for all countries combined using the 8 GADIT items; and (4) validity tests of the association between GADIT and measures with an expected correlation with it, including the Internet Gaming Disorder Test (IGDT‐10 total score), depression score (Patient Health Questionnaire‐2), anxiety score (GAD‐2), gaming intensity (high/low) and gaming‐related financial problems (yes/no). Results Items measuring the four gaming disorder criteria had good internal consistency (α ≥ 0.85). Multi‐group confirmatory factor analysis of the 8 items indicated factor loading invariance across countries [χ 2 (28) = 19.36, P = 0.886; root mean square error of approximation = 0.054; comparative fit index = 0.986; Tucker‐Lewis Index = 0.984]. There was lower sensitivity for the physical complaint items in China and Indonesia compared with Australia, Netherlands and USA. Overall, the 8‐item GADIT had strong concurrent validity with the IGDT‐10 [regression coefficient (b) = 0.67, coefficient of determination (R 2 ) = 52%] and was statistically significantly associated with depression (b = 0.38, R 2 = 21%), anxiety (b = 0.35, R 2 = 20%), gaming intensity [odds ratio (OR) = 3.11, 95% confidence interval (CI) = 2.72–3.60] and gaming‐related financial problems (OR = 3.11, 95% CI = 2.70–3.59). Summary The 8‐item Gaming Disorder Identification Test screening tool in Chinese, Dutch and Indonesian translation generally demonstrates robust psychometric properties and high validity, but cultural and/or language minor modifications may further improve international use.

Addiction
The University of Queensland (AU), Shanghai Jiao Tong University (CN), Shanghai Mental Health Center (CN), University of Indonesia (ID), Amsterdam University Medical Centers (NL), Vrije Universiteit Amsterdam (NL)
Partnerships for the goals
Openalex Percentile: Top 4%
Impact of Technology on Adolescents
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