...
【24h】

Using latent class analysis to identify aggressors and victims of peer harassment

机译:使用潜在类别分析来确定攻击者和同伴骚扰的受害者

获取原文
获取原文并翻译 | 示例
           

摘要

This study used latent class analysis (LCA) to identify and classify individuals into aggressor and victim latent classes. Participants were over 2,000 sixth grade students who completed peer nomination procedures that identified students who had reputations as perpetrators and/or victims of physical, verbal, or relational harassment. Results showed five latent classes. Consistent with previous research, LCA identified latent classes of victims, aggressors, and socially adjusted students. However, rather than a single aggressive-victim subgroup, LCA identified latent classes of highly-victimized aggressive-victims and highly-aggressive aggressive-victims. Comparisons showed differences in mean profiles and classification criteria between LCA and traditional dichotomization approaches. Adjustment outcomes showed that highly-victimized aggressive-victims generally experienced greater negative psychological and social adjustment outcomes than highly-aggressive aggressive-victims. Implications of these findings for better assessment of victim and aggressor subgroups were discussed.
机译:这项研究使用潜在类别分析(LCA)来识别个人并将其分类为侵略者和受害者潜在类别。参与者超过2,000名六年级学生,他们完成了同行提名程序,这些程序确定了声誉卓著的学生,这些学生是身体,语言或关系骚扰的肇事者和/或受害者。结果显示五个潜在类别。与先前的研究一致,LCA确定了潜在的受害者,侵略者和适应社会的学生类别。但是,LCA并没有确定潜在类别的高度受攻击的积极受害者和高度侵略的积极受害者。比较表明,LCA和传统的二分法之间在均值轮廓和分类标准方面存在差异。适应结果表明,高度受攻击的积极进取的受害者普遍比高度积极进取的积极进取的受害者遭受更大的负面心理和社会适应结果。讨论了这些发现对更好地评估受害者和侵略者亚组的意义。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号