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基于保留地的美国印第安高中生大麻使用的潜在类别分析及预测因素。

Latent Class Analysis and Predictors of Marijuana Use among Reservation-based American Indian High School Students.

机构信息

Department of Psychology, Colorado State University, Fort Collins, CO, USA.

出版信息

J Psychoactive Drugs. 2022 Apr-Jun;54(2):99-109. doi: 10.1080/02791072.2021.1918806. Epub 2021 May 4.

Abstract

American Indian (AI) youth residing on reservations report higher rates of marijuana use compared to national youth. Latent class analysis (LCA) was used to identify unique types of marijuana use among 2,884 AI high school students surveyed from 26 schools across six indigenous geographic regions. Predictors of class membership were then assessed using social, cultural, and individual measures relevant to adolescent substance use. Classes and predictors were examined separately for males and females. Four-class models fit the data best for both male and female AI students. Classes differed by sex, as did predictors. Overall, social predictors related to family and peers and the individual predictor, using marijuana to cope, were the best predictors of class membership. Based on these results, prevention and intervention efforts should provide alternative coping methods for these adolescents who often live in difficult situations, and should focus on encouraging parents to effectively monitor their adolescent children and communicate clear sanctions against marijuana use.

摘要

美国印第安青年(AI)在保留地的大麻使用率比全国青年高。对来自六个土著地理区域的 26 所学校的 2884 名 AI 高中生进行调查,使用潜在类别分析(LCA)来确定大麻使用的独特类型。然后使用与青少年物质使用相关的社会、文化和个人措施来评估类别成员的预测因素。分别为男性和女性检查类别和预测因素。对于男性和女性的 AI 学生来说,四类别模型最适合数据。类别的差异与性别有关,预测因素也是如此。总体而言,与家庭和同伴有关的社会预测因素以及使用大麻应对的个体预测因素是类别成员的最佳预测因素。基于这些结果,预防和干预措施应该为这些经常生活在困难环境中的青少年提供替代的应对方法,并应侧重于鼓励父母有效监督他们的青少年子女,并传达明确禁止使用大麻的规定。

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