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HOME > J Prev Med Public Health > Volume 38(3); 2005 > Article
Validation Studies Development of Internet Addiction Measurement Scales and Korean Internet Addiction Index.
Jae Sung Park
Journal of Preventive Medicine and Public Health 2005;38(3):298-306
DOI: https://doi.org/
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Department of Health Care Administration, Kosin University, Korea. jpark@kosin.ac.kr
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OBJECTIVE
To develop measurement scales of Internet addiction, and propose a Korean Internet Addiction Index (K-IAI) and classification criteria for Internet addiction from the threshold scores developed. METHODS: The identification of the concept of "Internet addiction" was based on the literature review. To select the scales, an exploratory factor analysis was applied. A construct validation was tested by a confirmatory factor analysis (CFA) with a structured equation model (SEM). In testing the validity of the classification criteria, ANOVA and non-recursive models with SEM were applied. RESULTS: Out of 1, 080 questionnaires distributed, 1, 037 were returned, ; a response rate of 96%. The Cronbach-alpha of all items was over 0.75. Using an exploratory factor analysis in the condition of a 6 factor constrain as the study model proposed, 23 of the initial 28 items were identified. In testing the discriminant and convergent validity of the selected 23 scales using CFA with SEM, the Internet addiction model explained about 93% of all variances of the data collected, and all the latent variables significantly explained the designated scales. A K-IAI was proposed using the T-scores of the sum of all factor averages. In the classification of users, the basic concept was a two standard deviation approach of the K-IAI as the criteria of MMPI. The addiction group had a score > or = 70 in the K-IAI, the pre-addiction group between > or = 50 and < 70, and the average user group < 50. The Internet use times of the classified groups were statistically different in the ANOVA and multiple comparisons. CONCLUSIONS: The K-IAI is a reliable and valid instrument for measuring Internet addiction. Moreover, the taxonomy of the groups was also verified using various methods.

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