A prediction model for internet game addiction in adolescents: using a decision tree analysis

Journal of Korean Academy of Nursing
Ki Sook Kim, Kyung Hee Kim

Abstract

This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not...Continue Reading

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Citations

Aug 9, 2012·Computers, Informatics, Nursing : CIN·Mia SeoSun-Mi Chae
Nov 16, 2013·PloS One·Johannes KornhuberThomas Mößle
Jun 6, 2013·Japan Journal of Nursing Science : JJNS·Hyun Soo Oh, Wha Sook Seo
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Sep 4, 2019·Journal of Korean Academy of Nursing·Mi Jin You, Eun Mi Ham

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