J Korean Acad Psychiatr Ment Health Nurs.  2014 Mar;23(1):12-20.

Predictors of Protective Factors for Internet Game Addiction in Middle School Students using Data Mining Decision Tree Analysis

  • 1Department of Nursing, Chosun University, Gwangju, Korea.
  • 2Department of Nursing, Sehan University, Yeongam, Korea. seyeong77@sehan.ac.kr


This study was done to identify protective factors which predict internet game addition in middle school students using data mining decision tree analysis.
The participants were 557 (Male=233, Female=324) middle school students from G city. Data were collected using structured questionnaires from March, 25 to May, 4, 2013, and analyzed using the descriptive analysis, t-test, ANOVA, decision tree, using SPSS 20.0 program.
The result of this research showed the prediction model for protective factors related to internet game addiction. Causative factors included gender, family support and father's attitude as the family protective factor, and planning ability as the personal protective factor. Level of accuracy of the decision tree was 70.6%.
The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to gender and planning ability in internet game addiction.


Adolescent; Internet; Addictive behavior; Data mining; Decision trees

MeSH Terms

Behavior, Addictive
Data Mining*
Decision Trees*
Surveys and Questionnaires


  • Figure 1 The construction of decision tree.


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