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Abstract
Introduction: Bullying is a pervasive issue among Indonesian youth, with far-reaching consequences for victims, perpetrators, and society. This study aimed to identify risk factors associated with bullying tendencies and develop a predictive scoring system to aid early identification and intervention.
Methods: A mixed-methods approach was employed. A nationwide survey was conducted with 3,500 Indonesian youth (aged 12-18) to collect data on sociodemographic factors, family environment, peer relationships, personal traits, and bullying behaviors. Qualitative interviews were conducted with 30 participants to gain deeper insights into their experiences. Risk factors were analyzed using regression models, and a predictive scoring system was developed using a machine learning algorithm.
Results: The study identified several significant risk factors for bullying tendencies, including male gender, low socioeconomic status, exposure to violence at home, poor parent-child communication, negative peer influence, low self-esteem, and high impulsivity. The developed predictive scoring system demonstrated good accuracy in identifying individuals at high risk of engaging in bullying behavior.
Conclusion: This study provides valuable insights into the complex interplay of risk factors contributing to bullying tendencies in Indonesian youth. The predictive scoring system offers a promising tool for early identification and targeted intervention, potentially mitigating the negative consequences of bullying.
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