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  • 标题:Chi-Square Automatic Interaction Detection Modeling for Predicting Depression in Multicultural Female Students
  • 本地全文:下载
  • 作者:Haewon Byeon
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2017
  • 卷号:8
  • 期号:12
  • DOI:10.14569/IJACSA.2017.081222
  • 出版社:Science and Information Society (SAI)
  • 摘要:This study developed a depression prediction model for female students from multicultural families by using a decision tree model based on Chi-squared automatic interaction detection (CHAID) algorithm. Subjects of the study were 9,024 female students between 12 and 15 years old among the children of surveyed marriage immigrants. Outcome variables were classified as presence of depression. Explanatory variables included sex, residing area, experience of career counseling, experience of social discrimination, experience of Korean language education, experience of using a multicultural family support center, Korean reading, Korean speaking, Korean writing, Korean listening, Korean society adjustment education experience, needs of Korean society adjustment education, needs of Korean language education, and rejoined entry. In the CHAID algorithm analysis, female students from multicultural families who experienced social discrimination within the past one year and had ordinary Korean speaking skill posed the highest risk of depression. It is necessary to pay social level interests to the mental health of adolescents from multicultural families for achieving successful social integration based on the results of this study.
  • 关键词:CHAID; data mining; multicultural family; risk factors; depression
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