十项网络游戏障碍测验简体中文版的修订及其诊断能力评估

doi:10.12139/j.1672-0628.2023.05.012

摘要/Abstract

摘要：

网络游戏障碍的诊断标准问题一直受到广泛关注。十项网络游戏障碍测验(IGDT-10)在多个国家具有较高的使用率，并且表现出良好的跨文化适用性。然而IGDT-10中文版在我国的使用率较低，其适用性也有待商榷。本研究对IGDT-10简体中文版量表的信效度进行评估，并采用潜在类别分析和受试者工作特征曲线确定了IGDT-10简体中文版的截断分数及诊断能力。结果发现，IGDT-10简体中文版具有良好的信效度及诊断能力，并且支持了DSM-5关于IGD截断分数的建议(认可五个或更多标准)。此外，本研究样本中的网络游戏障碍流行率为13.4%，且存在性别差异(男性高于女性)，但不存在年龄差异。结果表明，IGDT-10简体中文版可作为评估网络游戏障碍的有效工具。

关键词: 十项网络游戏障碍测验, 信度, 效度, 受试者工作特征曲线, 潜在类别分析

Abstract:

The criteria for identifying internet gaming disorder have been widely acknowledged and discussed. The Ten-Item Internet Gaming Disorder Test (IGDT-10) is frequently utilized in many countries, underscoring its high cross-cultural applicability. However, the Chinese version of IGDT-10 has lacked usage in China, sparking arguments about its applicability. In the current study, the reliability, validity, and diagnostic efficiency were assessed for the simplified Chinese IGDT-10. The cut-off point and diagnostic efficiency were determined through latent class analysis and receiver operating characteristic. The results demonstrated that the simplified Chinese IGDT-10 exhibited strong reliability, validity, and diagnostic efficiency, aligning with the DSM-5 recommendation of recognizing five or more criteria for internet gaming disorder. Moreover, this study revealed a 13.4% prevalence rate of internet gaming disorder in the samples, with a gender difference (higher prevalence among males than females) but no significant age difference. The results suggest that the simplified Chinese IGDT-10 is an effective tool for assessing internet gaming disorder.

Key words: Ten-Item Internet Gaming Disorder Test, reliability, validity, receiver operating characteristic, latent class analysis

中图分类号:

B849

杨海波, 张馨予. 十项网络游戏障碍测验简体中文版的修订及其诊断能力评估[J]. 心理与行为研究, 2023, 21(5): 658-666.

Haibo YANG, Xinyu ZHANG. Revision and Evaluation of Diagnostic Efficiency for the Simplified Chinese Version of the Ten-Item Internet Gaming Disorder Test[J]. Studies of Psychology and Behavior, 2023, 21(5): 658-666.

图/表 7

参考文献

	龚栩, 谢熹瑶, 徐蕊, 罗跃嘉. (2010). 抑郁-焦虑-压力量表简体中文版(DASS-21)在中国大学生中的测试报告. 中国临床心理学杂志, 18(4), 443–446.
	靳宇倡, 余梦, 胡云龙. 网络游戏成瘾研究的争议及趋势. 心理科学进展, 2019, 27 (1): 83- 95.
	American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5™. (5th ed.). Washington, DC: American Psychiatric Association.
	Bantis, L. E., Nakas, C. T., & Reiser, B.. Construction of confidence regions in the ROC space after the estimation of the optimal Youden index-based cut-off point. Biometrics, 2014, 70 (1): 212- 223. DOI
	Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N.. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews, 2019, 104, 1- 10.
	Broughton, M. (2020). Europe mobile game revenue hits record high; Riot acquires Hypixel. Retrieved May 23, 2023, from https://www.thegamingeconomy.exchangewire.com/news/page/26/
	Chang, C. I., Sit, H. F., Chao, T., Chen, C., Shen, J., Cao, B. L., ... Hall, B. J.. Exploring subtypes and correlates of internet gaming disorder severity among adolescents during COVID-19 in China: A latent class analysis. Current Psychology, 2023, 42 (23): 19915- 19926. DOI
	Chia, D. X. Y., Ng, C. W. L., Kandasami, G., Seow, M. Y. Y., Choo, C. C., Chew, P. K., ... Zhang, M. W. B.. Prevalence of internet addiction and gaming disorders in Southeast Asia: A meta-analysis. International Journal of Environmental Research and Public Health, 2020, 17 (7): 2582. DOI
	Chiu, Y. C., Pan, Y. C., & Lin, Y. H.. Chinese adaptation of the Ten-Item Internet Gaming Disorder Test and prevalence estimate of internet gaming disorder among adolescents in Taiwan. Journal of Behavioral Addictions, 2018, 7 (3): 719- 726. DOI
	Clark, S. L., & Muthén, B. (2009). Relating latent class analysis results to variables not included in the analysis. Retrieved May 3, 2023, from https://www.researchgate.net/publication/237346694_Relating_Latent_Class_Analysis_Results_to_Variables_not_Included_in_the_Analysis
	Clifford, T. (2020). Web traffic spiked 20% in one week amid coronavirus shutdown, Verizon CEO says. Retrieved May 23, 2023, from https://www.cnbc.com/2020/03/19/verizon-ceo-web-traffic-up-20percent-in-one-week-amid-coronavirus-shutdown.html
	Evren, C., Evren, B., Dalbudak, E., Topcu, M., & Kutlu, N.. Psychometric validation of the Turkish Ten-Item Internet Gaming Disorder Test (IGDT-10). Dusunen Adam The Journal of Psychiatry and Neurological Sciences, 2020, 33 (1): 19- 28.
	Fazeli, S., Zeidi, I. M., Lin, C. Y., Namdar, P., Griffiths, M. D., Ahorsu, D. K., & Pakpour, A. H.. Depression, anxiety, and stress mediate the associations between internet gaming disorder, insomnia, and quality of life during the COVID-19 outbreak. Addictive Behaviors Reports, 2020, 12, 100307. DOI
	Gao, Y. X., Wang, J. Y., & Dong, G. H.. The prevalence and possible risk factors of internet gaming disorder among adolescents and young adults: Systematic reviews and meta-analyses. Journal of Psychiatric Research, 2022, 154, 35- 43. DOI
	Giardina, A., Di Blasi, M., Schimmenti, A., King, D. L., Starcevic, V., & Billieux, J.. Online gaming and prolonged self-isolation: Evidence from Italian gamers during the Covid-19 outbreak. Clinical Neuropsychiatry, 2021, 18 (1): 65- 74.
	Gómez, P., Harris, S. K., Barreiro, C., Isorna, M., & Rial, A.. Profiles of internet use and parental involvement, and rates of online risks and problematic internet use among Spanish adolescents. Computers in Human Behavior, 2017, 75, 826- 833. DOI
	Huang, Y., Xu, L., Kuang, L., Wang, W., Cao, J., & Xiao, M. N.. Abnormal brain activity in adolescents with internet addiction who attempt suicide: An assessment using functional magnetic resonance imaging. Neural Regeneration Research, 2020, 15 (8): 1554- 1559. DOI
	King, D. L., Chamberlain, S. R., Carragher, N., Billieux, J., Stein, D., Mueller, K., ... Delfabbro, P. H.. Screening and assessment tools for gaming disorder: A comprehensive systematic review. Clinical Psychology Review, 2020, 77, 101831. DOI
	Király, O., Bőthe, B., Ramos-Diaz, J., Rahimi-Movaghar, A., Lukavska, K., Hrabec, O., ... Demetrovics, Z.. Ten-Item Internet Gaming Disorder Test (IGDT-10): Measurement invariance and cross-cultural validation across seven language-based samples. Psychology of Addictive Behaviors, 2019, 33 (1): 91- 103. DOI
	Király, O., Potenza, M. N., & Demetrovics, Z.. Gaming disorder: current research directions. Current Opinion in Behavioral Sciences, 2022, 47, 10120.
	Király, O., Sleczka, P., Pontes, H. M., Urbán, R., Griffiths, M. D., & Demetrovics, Z.. Validation of the Ten-Item Internet Gaming Disorder Test (IGDT-10) and evaluation of the nine DSM-5 internet gaming disorder criteria. Addictive Behaviors, 2017, 64, 253- 260. DOI
	Lemmens, J. S., Valkenburg, P. M., & Gentile, D. A.. The Internet Gaming Disorder Scale. Psychological Assessment, 2015, 27 (2): 567- 582. DOI
	Liao, Z. J., Chen, X. X., Huang, Q. P., & Shen, H. X.. Prevalence of gaming disorder in East Asia: A comprehensive meta-analysis. Journal of Behavioral Addictions, 2022, 11 (3): 727- 738. DOI
	Lovibond S. H., & Lovibond P. F. (1995). Manual for the depression anxiety stress scales (2nd ed.). Sydney: Psychology Foundation of Australia.
	Männikkö, N., Ruotsalainen, H., Tolvanen, A., & Kääriäinen, M.. Psychometric properties of the Internet Gaming Disorder Test (IGDT-10) and problematic gaming behavior among Finnish vocational school students. Scandinavian Journal of Psychology, 2019, 60 (3): 252- 260. DOI
	Marraudino, M., Bonaldo, B., Vitiello, B., Bergui, G. C., & Panzica, G.. Sexual differences in internet gaming disorder (IGD): From psychological features to neuroanatomical networks. Journal of Clinical Medicine, 2022, 11 (4): 1018. DOI
	Martins, M. V., Formiga, A., Santos, C., Sousa, D., Resende, C., Campos, R., ... Ferreira, S.. Adolescent internet addiction-role of parental control and adolescent behaviours. International Journal of Pediatrics and Adolescent Medicine, 2020, 7 (3): 116- 120. DOI
	Mazaherizadeh, A., Taherifar, Z., & Farahani, H.. Psychometric properties of the Farsi version of the Gaming Disorder Scale for Adolescents (GADIS-A). BMC Psychology, 2022, 10 (1): 195. DOI
	Mihara, S., Osaki, Y., Kinjo, A., Matsuzaki, T., Nakayama, H., Kitayuguchi, T., ... Higuchi, S.. Validation of the Ten-Item Internet Gaming Disorder Test (IGDT-10) based on the clinical diagnosis of IGD in Japan. Journal of Behavioral Addictions, 2022, 11 (4): 1024- 1034. DOI
	Muthén, L. K., & Muthén, B. O. (2012). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.
	Oka, T., Hamamura, T., Miyake, Y., Kobayashi, N., Honjo, M., Kawato, M., ... Chiba, T. (2021). Prevalence and risk factors of internet gaming disorder and problematic internet use before and during the COVID-19 pandemic: A large online survey of Japanese adults. Journal of Psychiatric Research, 142, 218–225.
	Ostinelli, E. G., Zangani, C., Giordano, B., Maestri, D., Gambini, O., D’Agostino, A., ... Purgato, M.. Depressive symptoms and depression in individuals with internet gaming disorder: A systematic review and meta-analysis. Journal of Affective Disorders, 2021, 284, 136- 142. DOI
	Pontes, H. M., & Griffiths, M. D.. Measuring DSM-5 Internet Gaming Disorder: Development and validation of a short psychometric scale. Computers in Human Behavior, 2015, 45, 137- 143. DOI
	Schettler, L. M., Thomasius, R., & Paschke, K. (2023). Emotional dysregulation predicts problematic gaming in children and youths: A cross-sectional and longitudinal approach. European Child & Adolescent Psychiatry, 1–12.
	Shand, T. A. (2022). Investigating risk factors for internet gaming disorder: Impulsivity, ADHD, behavioural inhibition/activation, weekly gameplay and inhibitory control (Unpublished doctorial dissertation). University of Tasmania, Australia.
	Siste, K., Hanafi, E., Sen, L. T., Damayanti, R., Beatrice, E., & Ismail, R. I.. Psychometric properties of the Indonesian Ten-Item Internet Gaming Disorder Test and a latent class analysis of gamer population among youths. PLoS One, 2022, 17 (6): e0269528. DOI
	Sit, H. F., Chang, C. I., Yuan, G. F., Chen, C., Cui, L. X., Elhai, J. D., & Hall, B. J.. Symptoms of internet gaming disorder and depression in Chinese adolescents: A network analysis. Psychiatry Research, 2023, 322, 115097. DOI
	Sun, S. Y., Pan, W., & Wang, L. L.. A comprehensive review of effect size reporting and interpreting practices in academic journals in education and psychology. Journal of Educational Psychology, 2010, 102 (4): 989- 1004. DOI
	Teng, Z. J., Pontes, H. M., Nie, Q., Griffiths, M. D., & Guo, C.. Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: A longitudinal study. Journal of Behavioral Addictions, 2021, 10 (1): 169- 180. DOI
	Vimalanathan, V., Kunasegaran, V., Alagenthran, K., Balamurugan, R. N. D., & Sandrasaigaran, P.. Integration of casual video games during online learning to relief stress in students. Malaysian Journal of Science and Advanced Technology, 2022, 2 (1): 36- 41.
	World Health Organization. (2019). ICD-11 for mortality and morbidity statistics. Retrieved May 10, 2023, from https://icd.who.int/ browse11/l-m/en
	Young, K. S. (1998). Caught in the net: How to recognize the signs of internet addiction—and a winning strategy for recovery. New York: John Wiley & Sons.

变量	总样本	N-IGD组	IGD组	卡方检验/t检验	效应量
n(占比)	2628(48.32)	2276(45.78)	352(64.77)	χ²=44.03; df=1; p<0.001	0.13
年龄(岁)				t=1.12; df=2626; p=0.262	0.06
M±SD	23.47±7.63	23.54±8.04	23.05±4.04
范围	12～68	12～68	15～59
学历				χ²=6.20; df=2; p=0.045	0.05
高中及以下	419(15.94)	378(16.61)	41(11.65)
本科/大专	2059(78.35)	1766(77.59)	293(83.24)
硕士及以上	150(5.71)	132(5.80)	18(5.11)
可支配金钱				χ²=168.13; df=2; p<0.001	0.25
2000元以下	1311(49.89)	1224(53.78)	87(24.72)
2001～5000元	1190(45.28)	980(43.06)	210(59.66)
5001元以上	127(4.83)	72(3.16)	55(15.62)
总游戏年限				χ²=102.44; df=3; p<0.001	0.20
不到1年	464(17.66)	460(20.21)	4(1.14)
1～2年	364(13.85)	277(12.17)	87(24.71)
3～4年	674(25.65)	564(24.78)	110(31.25)
5年以上	1126(42.84)	975(42.84)	151(42.90)
游戏设备				χ²=65.10; df=3; p<0.001	0.16
PC(台式电脑、笔记本)	405(15.41)	340(14.94)	65(18.47)
可移动(手机、平板)	2015(76.67)	1780(78.21)	235(66.76)
多媒体(电视、投影)	120(4.57)	104(4.57)	16(4.54)
其他	88(3.35)	52(2.28)	36(10.23)
每日游戏时长				χ²=230.05; df=5; p<0.001	0.30
0小时(不打游戏)	465(17.69)	463(20.34)	2(0.57)
1小时以内	491(18.68)	463(20.34)	28(7.95)
1～3小时	933(35.50)	803(35.28)	130(36.93)
3～6小时	413(15.72)	278(12.22)	135(38.35)
6小时以上	269(10.24)	221(9.71)	48(13.64)
不确定	57(2.17)	48(2.11)	9(2.56)

变量	总样本	N-IGD组	IGD组	卡方检验/t检验	效应量
n(占比)	2628(48.32)	2276(45.78)	352(64.77)	χ²=44.03; df=1; p<0.001	0.13
年龄(岁)				t=1.12; df=2626; p=0.262	0.06
M±SD	23.47±7.63	23.54±8.04	23.05±4.04
范围	12～68	12～68	15～59
学历				χ²=6.20; df=2; p=0.045	0.05
高中及以下	419(15.94)	378(16.61)	41(11.65)
本科/大专	2059(78.35)	1766(77.59)	293(83.24)
硕士及以上	150(5.71)	132(5.80)	18(5.11)
可支配金钱				χ²=168.13; df=2; p<0.001	0.25
2000元以下	1311(49.89)	1224(53.78)	87(24.72)
2001～5000元	1190(45.28)	980(43.06)	210(59.66)
5001元以上	127(4.83)	72(3.16)	55(15.62)
总游戏年限				χ²=102.44; df=3; p<0.001	0.20
不到1年	464(17.66)	460(20.21)	4(1.14)
1～2年	364(13.85)	277(12.17)	87(24.71)
3～4年	674(25.65)	564(24.78)	110(31.25)
5年以上	1126(42.84)	975(42.84)	151(42.90)
游戏设备				χ²=65.10; df=3; p<0.001	0.16
PC(台式电脑、笔记本)	405(15.41)	340(14.94)	65(18.47)
可移动(手机、平板)	2015(76.67)	1780(78.21)	235(66.76)
多媒体(电视、投影)	120(4.57)	104(4.57)	16(4.54)
其他	88(3.35)	52(2.28)	36(10.23)
每日游戏时长				χ²=230.05; df=5; p<0.001	0.30
0小时(不打游戏)	465(17.69)	463(20.34)	2(0.57)
1小时以内	491(18.68)	463(20.34)	28(7.95)
1～3小时	933(35.50)	803(35.28)	130(36.93)
3～6小时	413(15.72)	278(12.22)	135(38.35)
6小时以上	269(10.24)	221(9.71)	48(13.64)
不确定	57(2.17)	48(2.11)	9(2.56)

Model	BIC	SSA-BIC	Entropy	LMRT	p
1	21918.77	21890.18
2	18003.49	17943.12	0.88	3943.93	<0.001
3	17835.12	17742.98	0.92	244.01	<0.001
4	17698.10	17574.18	0.85	213.06	0.001

Model	BIC	SSA-BIC	Entropy	LMRT	p
1	21918.77	21890.18
2	18003.49	17943.12	0.88	3943.93	<0.001
3	17835.12	17742.98	0.92	244.01	<0.001
4	17698.10	17574.18	0.85	213.06	0.001

截断分数	TP	TN	FP	FN	Sensitivity	Specificity	PPV	NPV	DA(%)
1	45	1210	1373	0	1.00	0.47	0.97	1.00	45.46
2	45	1680	903	0	1.00	0.65	0.95	1.00	45.64
3	45	1920	663	0	1.00	0.74	0.94	1.00	45.73
4	45	2098	485	0	1.00	0.81	0.92	1.00	45.80
5	39	2270	313	6	0.87	0.88	0.89	1.00	39.86
6	1	2402	44	181	0.02	0.93	0.99	0.98	1.91
7	0	2489	45	94	0.00	0.96	1.00	0.98	0.95
8	0	2533	45	50	0.00	0.98	1.00	0.98	0.96
9	0	2556	45	27	0.00	0.99	1.00	0.98	0.97