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美国印第安青少年大麻使用的相关风险和促进因素。

Risk and Promotive Factors Related to Cannabis Use Among American Indian Adolescents.

机构信息

Department of Psychology and Colorado School of Public Health, Colorado State University, Behavioral Sciences Building, Fort Collins, CO, 80524-1876, USA.

Tri-Ethnic Center for Prevention Research, Colorado State University, Fort Collins, USA.

出版信息

Prev Sci. 2024 Jul;25(5):734-748. doi: 10.1007/s11121-024-01649-y. Epub 2024 Mar 7.

Abstract

Reservation-dwelling American Indian adolescents are at exceedingly high risk for cannabis use. Prevention initiatives to delay the onset and escalation of use are needed. The risk and promotive factors approach to substance use prevention is a well-established framework for identifying the timing and targets for prevention initiatives. This study aimed to develop predictive models for the usage of cannabis using 22 salient risk and promotive factors. Models were developed using data from a cross-sectional study and further validated using data from a separate longitudinal study with three measurement occasions (baseline, 6-month follow-up, 1-year follow-up). Application of the model to longitudinal data showed an acceptable performance contemporaneously but waning prospective predictive utility over time. Despite the model's high specificity, the sensitivity was low, indicating an effective prediction of non-users but poor performance in correctly identifying users, particularly at the 1-year follow-up. This divergence can have significant implications. For example, a model that misclassifies future adolescent cannabis use could fail to provide necessary intervention for those at risk, leading to negative health and social consequences. Moreover, supplementary analysis points to the importance of considering change in risk and promotive factors over time.

摘要

居住在保留地的美国印第安青少年极有可能使用大麻。需要采取预防措施来延迟大麻使用的开始和升级。风险和促进因素方法是预防物质使用的一个既定框架,用于确定预防措施的时机和目标。本研究旨在使用 22 个显著的风险和促进因素来开发大麻使用的预测模型。模型是使用横断面研究的数据开发的,并使用具有三个测量时间点(基线、6 个月随访和 1 年随访)的单独纵向研究的数据进一步验证。该模型在纵向数据中的应用显示出可接受的同期表现,但随着时间的推移,其前瞻性预测效用逐渐减弱。尽管该模型的特异性很高,但灵敏度较低,这表明对非使用者的预测效果很好,但对使用者的预测效果不佳,尤其是在 1 年随访时。这种差异可能会产生重大影响。例如,一个错误分类未来青少年大麻使用的模型可能无法为那些处于风险中的人提供必要的干预,从而导致健康和社会后果的负面后果。此外,补充分析表明,考虑随时间变化的风险和促进因素的重要性。

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