Department of Behavioral Science, University of Kentucky College of Medicine, Lexington, Kentucky, USA.
Department of Psychology, University of Kentucky College of Arts and Sciences, Lexington, Kentucky, USA.
Am J Drug Alcohol Abuse. 2022 Mar 4;48(2):176-185. doi: 10.1080/00952990.2021.1984492. Epub 2022 Feb 15.
: The COVID-19 pandemic and subsequent economic crisis has provided a unique opportunity to investigate the effects of economic shifts on substance use. Existing literature on this relationship is limited and conflicting, warranting further exploration.: This study aimed to identify relationships between socioeconomic status (SES), demographic variables, and substance use patterns before and after government-mandated business closures due to COVID-19.: Participants were recruited based on self-reported substance use through Amazon's Mechanical Turk (MTurk). Qualifying participants (N = 315, 43% female, age = 35.35) reported their substance use and SES for two-week periods before and after pandemic-related business closures. Regression models analyzed relationships between substance use and study variables.: Regression models found that, during COVID-19 closures, greater financial strain predicted decreased benzodiazepine (β = -1.12) and tobacco (β = 1.59) use. Additionally, certain predictor variables (e.g., participants' age [β = 1.22], race [β = -4.43], psychiatric disorders including ADHD [β = -2.73] and anxiety [β = 1.53], and concomitant substance use [β = 3.38]) predicted changes in substance use patterns; however, the directionality of these associations varied across substances.: Specific substance use patterns were significantly and differentially impacted by economic strain, psychiatric diagnoses, and concomitant substance use. These results can help direct harm reduction efforts toward populations at greatest risk of harmful substance use following the pandemic.
: COVID-19 大流行和随后的经济危机为研究经济变化对物质使用的影响提供了一个独特的机会。关于这种关系的现有文献有限且存在冲突,需要进一步探讨。
: 本研究旨在确定社会经济地位(SES)、人口统计学变量与 COVID-19 相关的政府强制关闭企业前后物质使用模式之间的关系。
: 通过 Amazon 的 Mechanical Turk(MTurk),参与者根据自我报告的物质使用情况进行招募。符合条件的参与者(N=315,43%为女性,年龄=35.35)报告了他们在大流行相关企业关闭前后两周的物质使用情况和 SES。回归模型分析了物质使用与研究变量之间的关系。
: 回归模型发现,在 COVID-19 关闭期间,更大的经济压力预测了苯二氮䓬类药物(β=-1.12)和烟草(β=1.59)使用的减少。此外,某些预测变量(例如,参与者的年龄[β=1.22]、种族[β=-4.43]、包括注意力缺陷多动障碍[β=-2.73]和焦虑[β=1.53]在内的精神疾病)预测了物质使用模式的变化;然而,这些关联的方向性因物质而异。
: 特定的物质使用模式受到经济压力、精神疾病诊断和同时使用其他物质的显著和不同影响。这些结果可以帮助将减少伤害的努力针对大流行后最有可能有害物质使用的人群。