Ware Orrin D, Lee Kerry A, Lombardi Brianna, Buccino Daniel L, Lister Jamey J, Park Eunsong, Roberts Kate, Estreet Anthony, Van Deinse Tonya, Neukrug Hannah, Wilson Amy Blank, Park Daejun, Lanier Paul
School of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Graduate School of Social Work and Social Research, Bryn Mawr College, Bryn Mawr, Pennsylvania, USA.
J Dual Diagn. 2024 May 26:1-12. doi: 10.1080/15504263.2024.2357623.
The co-occurrence of anxiety disorders, depressive disorders, and substance use problems was examined. The Mental Health Client-Level Data dataset was used to conduct logistic regression models and an artificial neural network analysis. Logistic regression analyses were conducted among adults with anxiety ( = 547,473) or depressive disorders ( = 1,610,601) as their primary diagnosis who received treatment in a community mental health center. The artificial neural network analysis was conducted with the entire sample ( = 2,158,074). Approximately 30% of the sample had co-occurring high-risk substance use or substance use disorder. Characteristics including region of treatment receipt, age, education, gender, race and ethnicity, and the presence of co-occurring anxiety and depressive disorders were associated with the co-occurring high-risk substance use or a substance use disorder. Findings from this study highlight the importance of mental health facilities to screen for and provide integrated treatment for co-occurring disorders.
研究了焦虑症、抑郁症和物质使用问题的共现情况。使用心理健康客户层面数据数据集进行逻辑回归模型和人工神经网络分析。对在社区心理健康中心接受治疗、以焦虑症（n = 547,473）或抑郁症（n = 1,610,601）作为主要诊断的成年人进行逻辑回归分析。对整个样本（n = 2,158,074）进行人工神经网络分析。约30%的样本存在共现的高风险物质使用或物质使用障碍。包括治疗接受地区、年龄、教育程度、性别、种族和民族以及共现的焦虑症和抑郁症等特征与共现的高风险物质使用或物质使用障碍相关。本研究结果凸显了心理健康机构筛查并提供共病综合治疗的重要性。
