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Psychometric Properties of the Internet Addiction Test: A Systematic Review and Meta-Analysis.

Authors :
Moon, Sun Jae
Hwang, Jin Seub
Kim, Jae Yup
Shin, Ah Lahm
Bae, Seung Min
Kim, Jung Won
Source :
CyberPsychology, Behavior & Social Networking. Aug2018, Vol. 21 Issue 8, p473-484. 12p. 1 Diagram, 5 Charts, 1 Graph.
Publication Year :
2018

Abstract

This article performs a systemic review of psychometric properties of Internet Addiction Test (IAT)--the most widely used tool for assessing Internet addiction in clinic and research field. Studies measuring psychometric properties of IAT (original version) were searched through MEDLINE, The Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, and Embase. A total of 25 studies including 18,421 subjects were reviewed in our study. Based on meta-analysis for internal consistency, the pooled Cronbach's alpha coefficient from college/university students with a single department subgroup was 0.90 (95percent confidence interval [CI], 0.89-0.91), and that from middle-/high-school students (older than 15 years) subgroup was 0.93 (95 percent CI, 0.92-0.93). According to test-retest analysis, the pooled Spearman's correlation coefficient from college/university students with a single department subgroup was high at 0.83 (95 percent CI, 0.81-0.85), along with low publication bias. Convergent validity showed correlation coefficients of 0.62-0.84, as compared with major tools. For construct validity, the number of factors is believed to be 1-2, only considering studies that followed the guidelines. IAT appears to have acceptable internal consistency, test-retest reliability, and convergent validity in specific groups. To verify these values, well-designed evidence-based studies assessing psychometric properties of IAT across diverse populations are warranted. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21522715
Volume :
21
Issue :
8
Database :
Academic Search Index
Journal :
CyberPsychology, Behavior & Social Networking
Publication Type :
Academic Journal
Accession number :
131267047
Full Text :
https://doi.org/10.1089/cyber.2018.0154