Exploring Shared and Unique Predictors of Positive and Negative Risk-Taking Behaviors Among Chinese Adolescents Through Machine-Learning Approaches: Discovering Gender and Age Variations.

Despite extensive research on the impact of individual and environmental factors on negative risk-taking behaviors, the understanding of these factors' influence on positive risk-taking, and how it compares to negative risk taking, remains limited. This research employed machine-learning techniques...

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Published in:Journal of Youth & Adolescence Vol. 54; no. 5; pp. 1109 - 1128
Main Authors: Liu, Ying, Zou, Qifan, Xie, Ying, Dou, Kai
Format: Article
Published: Springer Nature May2025
Subjects:
Online Access:View this record in EBSCOhost
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      dt: May2025
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      pub: Springer Nature
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        10.1007/s10964-024-02120-5
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        atl: Exploring Shared and Unique Predictors of Positive and Negative Risk-Taking Behaviors Among Chinese Adolescents Through Machine-Learning Approaches: Discovering Gender and Age Variations.
      aug:
        au:
          Liu, Ying
          Zou, Qifan
          Xie, Ying
          Dou, Kai
        affil:
          https://ror.org/05ar8rn06 Department of Sociology, School of Public Administration, Guangzhou University, Guangzhou, China
          https://ror.org/05ar8rn06 Research Center of Adolescent Psychology and Behavior, School of Education, Guangzhou University, Guangzhou, China
      su:
        China
        Victims
        Risk-taking behavior
        Sex distribution
        Self-control
        Parenting
        Father-child relationship
        Metropolitan areas
        Middle schools
        Research funding
        Descriptive statistics
        Machine learning
      sug:
        subj:
          Victims
          Risk-taking behavior
          Sex distribution
          Self-control
          Parenting
          Father-child relationship
          Metropolitan areas
          Middle schools
          China
          Elementary and Secondary Schools
          Research funding
          Descriptive statistics
          Machine learning
      keyword:
        Adolescence
        Negative risk-taking
        Positive risk-taking
        Psychology and Cognitive Sciences Psychology
        Risk-taking
        Adolescence
        Negative risk-taking
        Positive risk-taking
        Psychology and Cognitive Sciences Psychology
        Risk-taking
      ab: Despite extensive research on the impact of individual and environmental factors on negative risk-taking behaviors, the understanding of these factors' influence on positive risk-taking, and how it compares to negative risk taking, remains limited. This research employed machine-learning techniques to identify shared and unique predictors across individual, family, and peer domains. Participants (N = 1012; 44% girls; Mage = 14.60 years, SD = 1.16 years) were drawn from three public middle schools in a large city in southern China (with 49.2% in grade 7 and 50.8% in grade 11). The findings indicate that positive risk-taking is significantly associated with general risk propensity, self-control, and negative parenting by father, while negative risk-taking is correlated with self-control, deviant peer affiliations, and peer victimization. Paternal negative parenting triggered positive risk-taking in boys, whereas self-control had a greater impact on girls. For negative risk-taking, boys were more affected by peer victimization, while girls were more influenced by deviant peer affiliations. This study further demonstrates that as progress from junior to senior high school, peer influence grows more significant in predicting positive risk taking; deviant peer affiliations exert a persistent pivotal influence, future positive time perspective replaces life satisfaction, and paternal negative parenting becomes increasingly impactful in predicting negative risk taking.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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