A prediction model for peer attachment in KOREAN female adolescents using back propagation neural network

  • Authors

    • Haewon Byeon
    • . .
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.13847
  • Datamining, Back Propagation Neural Network, Peer Attachment, Risk Factors, Female Students.
  • Background/Objectives: This study used data mining technique to explore the potential factors affecting the peer attachment of South Korean female students.

    Methods/Statistical analysis: This study analyzed 2009 9th grade female students, who attended Panel Study on Korean Children in 2016. Peer attachment was defined as a dependent variable. The explanatory variables included gender, academic achievement satisfaction, subjective household economy level, parent-child dialogue frequency, subjective health status, depression symptom, self-esteem, subjective life satisfaction, and mobile phone dependence. The predictors of peer attachment were analyzed by using back propagation neural network (BPN).

    Findings: Analysis results showed that depression, self-esteem, dialogue level between parent and child regarding school life, subjective health condition were highly related to the peer attachment of female students.

    Improvements/Applications: It is required to develop a customized educational program to form a successful social relationship between adolescent female students.

     

     

  • References

    1. [1] Arnett J J, Adolescence and emerging adulthood, Pearson, Boston, MA, 2014.

      [2] Lee H, Jung E, A study on prediction models for adolescent attachment types of parents, teachers and peers using data mining, The Korean Journal Child Education, 2016, 25, pp. 23–38.

      [3] Rueger SY, Malecki CK, Demaray M K, Relationship between multiple sources of perceived social support and psychological and academic adjustment in early adolescence: Comparisons across gender, Journal of Youth and Adolescence, 2010, 39, pp. 47.

      [4] Armsden GC, Greenberg M T, The inventory of parent and peer attachment: Individual differences and their relationship to psychological well-being in adolescence, Journal of youth and adolescence, 1987, 16, pp. 427–54.

      [5] Min WS, Park WM, Cheon SM, Lee Y S, The relationships among social anxiety, aggression and peer relations affected by adult attachment types for the 5th and 6th graders in elementary school, Journal of Emotional & Behavioral Disorders, 2007, 23, pp. 115-40.

      [6] Pallini S, Baiocco R, Schneider B H, Madigan S, Atkinson L, Early child–parent attachment and peer relations: A meta-analysis of recent research, Journal of Family Psychology, 2014, 28, pp. 118–23.

      [7] Buist K L, Deković M, Prinzie P, Sibling relationship quality and psychopathology of children and adolescents: A meta-analysis, Clinical Psychology Review, 2013, 33, pp. 97–106.

      [8] Ma CQ, Huebner ES, Attachment relationships and adolescents' life satisfaction: Some relationships matter more to girls than boys, Psychology in the Schools, 2008; 45, pp. 177–90.

      [9] Gorrese A, Ruggieri R, Peer attachment: A meta-analytic review of gender and age differences and associations with parent attachment, Journal of youth and adolescence, 2002, 41, pp. 650–72.

      [10] Kim JC, Gyeong JS, Choe WH, Effects of parents, teachers and friends` attachment on aggression in early adolescence, The Korean Journal Child Education, 2010, 19, pp. 97–113.

      [11] Pradhan B, Lee S, Buchroithner M F, A GIS-based back-propagation neural network model and its cross application and validation for landslide susceptibility analyses. Computers, Environment and Urban Systems, 2010, 34, pp. 216–35.

      [12] Korea Youth Policy Institute, Panel survey of local children's centers, Korea Youth Policy Institute, Seoul, 2015.

      [13] Hwang M K, The relationship between parent-peer attachment of multi-culture children and social anxiety, Pukyong University, Med. thesis, Korea, 2010.

      [14] Byeon H, Cho S, The Factors of Subjective Voice Disorder Using Integrated Method of Decision Tree and Multi-Layer Perceptron Artificial Neural Network Algorithm, International Journal of Advanced Computer Science and Applications, 2016; 7, pp. 112–16.

      [15] Ko Y, The relationship among father, mother, peer attachment and subjective well-being in middle school students, The Journal of Yeolin Education, 2008, 16, pp. 111–31.

      [16] Meeus WI M, Oosterwegel A, Vollebergh W, Parental and peer attachment and identity development in adolescence, Journal of adolescence, 2002, 25, pp. 93–106.

      [17] No B O, Park S, Yi S, Park H J, Trajectories of adolescents’ peer attachment and their predictors: A multiple group analysis according to gender,Studies on Korean Youth, 2016, 27, pp. 149–77.

      [18] Millings A, Buck R, Montgomery A, Spears M, Stallard P, School connectedness, peer attachment, and self-esteem as predictors of adolescent depression, Journal of adolescence, 2012, 35, pp. 1061–67.

      [19] Kwon H I, Ham B J, Paik JW, Suh SY, Kwon J H, Psychosocial functioning in depression, Korean Journal of Clinical Psychology, 2010, 29, pp. 1117–33.

      [20] Nelis S M, Rae G, Brief report: Peer attachment in adolescents, Journal of adolescence, 2009, 32, pp. 443–7.

  • Downloads

  • How to Cite

    Byeon, H., & ., . (2018). A prediction model for peer attachment in KOREAN female adolescents using back propagation neural network. International Journal of Engineering & Technology, 7(2.33), 27-30. https://doi.org/10.14419/ijet.v7i2.33.13847