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Development and Verification of an Internet Game Literacy Scale

BACKGROUND: Education on internet games for parents and internet game literacy are needed to prevent problematic internet game playing in Korea. We created an 18-item Internet Game Literacy Scale (IGLS). It is a valuable tool for assessing the positive and negative aspects of internet game play. We...

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Detalles Bibliográficos
Autores principales: Chung, Un Sun, Kim, Soyeon, Jin, Jaechan, Han, Doug Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Medical Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8422038/
https://www.ncbi.nlm.nih.gov/pubmed/34490753
http://dx.doi.org/10.3346/jkms.2021.36.e216
Descripción
Sumario:BACKGROUND: Education on internet games for parents and internet game literacy are needed to prevent problematic internet game playing in Korea. We created an 18-item Internet Game Literacy Scale (IGLS). It is a valuable tool for assessing the positive and negative aspects of internet game play. We aimed to determine the validity of the IGLS and the cut-off for the tendency for internet gameplay. METHODS: An online research company gathered data from 300 participants. Factor analysis, including Cronbach's α and consistency coefficient, exploratory factor analysis, and confirmatory factor analysis were conducted to verify the 18 items of the IGLS. Additionally, a K-means cluster analysis was performed to determine the cut-off values for positive and negative IGLS scores. RESULTS: The 18 items of the IGLS were proven to be reliable, as evidenced by a high Cronbach's alpha (α = 0.892). The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.903, and Bartlett's test of sphericity was good (χ(2) = 1,623.314, P < 0.001). All 18 items were segregated into two factors, with nine items each. The eigenvalue of all 18 items was significant at > 0.4. In the analysis of the validity of the 18-item IGLS with confirmatory factor analysis (CFA) (maximum likelihood estimation, with an oblique method), the fit indices of the standard three-factor model reached acceptable standards. The cut-off point of the total score between the low positive and average positive groups was 23, and the cut-off point of the total score between the average positive and high positive groups was 30. The cut-off point of the total score between the low negative and the average negative groups was 24. The cut-off point of the total score between the average negative group and the high negative group was 32. CONCLUSION: The study assessed the reliability and validity of the IGLS and suggested a cut-off for low, average, and high Internet game literacy degree with 300 Korean adults aged 21–49 years. The current results suggest that the IGLS has good internal consistency and a proper cut-off for positive and negative internet game literacy degrees.