Development of Internet Addiction Measurement Scales and Korean Internet Addiction Index

인터넷중독 측정도구와 한국형 인터넷중독지표의 개발

  • Park, Jae-Sung (Department of Health Care Administration, Kosin University)
  • 박재성 (고신대학교 인문사회복지대학 의료경영학부)
  • Published : 2005.09.01

Abstract

Objectives : 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 twostandard deviation approach of the K-IAI as the criteria of MMPI. The addiction group had a score ${\geq}70$ in the K-IAI, the pre-addiction group between ${\geq}50$ 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.

Keywords

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