Center for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, United States.
Center for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI 02903, United States.
Addict Behav. 2020 Jun;105:106329. doi: 10.1016/j.addbeh.2020.106329. Epub 2020 Jan 30.
Historically, cannabis researchers have assumed a single mode and product of cannabis (e.g., smoking plant). However, patterns of use, products (e.g., concentrates, edibles), and modes (e.g. blunts, vaporizers) are diversifying. This study sought to: 1) classify cannabis users into groups based on their use of the full range of cannabis products, and 2) examine user group differences on demographics, cannabis consequences and cannabis use disorder (CUD) symptomatology.
In a sample of college students (data collected in Fall 2017), who used cannabis in the past year (N = 1390), latent class analysis (LCA) was used to characterize cannabis users. We then added demographic characteristics, cannabis consequences, and CUD symptomatology scores separately to LCA models to examine class differences.
Five unique classes emerged: high-frequency all-product users, high-frequency plant/moderate-frequency edible and concentrate users, low-frequency plant users, moderate-frequency plant and edible users, and low-frequency edible users. Demographic characteristics, cannabis consequences, and CUD symptomatology differed across classes characterized by frequency as well as product.
Results reflect the increasing variety of cannabis products, modes, and use patterns among college students. In this sample, frequency of use remains a strong predictor of cannabis-related consequences, in addition to type of product. As variation in cannabis use patterns continue to evolve, it is essential for researchers to conduct comprehensive assessments.
从历史上看,大麻研究人员一直假设大麻只有一种模式和产品(例如,吸食大麻植物)。然而,使用模式、产品(例如,浓缩物、可食用物)和方式(例如, blunt、蒸发器)正在多样化。本研究旨在:1)根据大麻使用者使用全系列大麻产品的情况对其进行分类,2)研究使用者群体在人口统计学、大麻后果和大麻使用障碍(CUD)症状学方面的差异。
在一项对过去一年中使用过大麻的大学生样本(于 2017 年秋季收集的数据,N=1390)中,使用潜在类别分析(LCA)对大麻使用者进行特征描述。然后,我们分别向 LCA 模型中添加人口统计学特征、大麻后果和 CUD 症状学评分,以检查类别差异。
出现了五个独特的类别:高频率全产品使用者、高频率植物/中频率食用和浓缩物使用者、低频率植物使用者、中频率植物和食用物使用者以及低频率食用物使用者。特征为频率和产品的类别在人口统计学特征、大麻后果和 CUD 症状学方面存在差异。
结果反映了大学生中大麻产品、使用模式和使用频率的多样性不断增加。在这个样本中,除了产品类型外,使用频率仍然是与大麻相关后果的强有力预测因素。随着大麻使用模式的变化继续演变,研究人员进行全面评估至关重要。