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Anxiety, Bipolar, Depressive, and Schizophrenia Diagnoses Among Patients Receiving Addiction Treatment in the United States, 2006-2022: A Descriptive Study

Year: 2026

Type: article

Abstract: BACKGROUND: This study examined specific mental health diagnoses groupings among patients admitted to specialty addiction treatment in the United States from 2006 to 2022. METHODS: Joinpoint regression was used to examine annual data from the publicly available Treatment Episode Data Set - Admissions. Sample selection criteria included having a primary substance listed and any of the following conditions: (a) anxiety disorders, (b) bipolar disorders, (c) depressive disorders, and (d) schizophrenia and other psychotic disorders. RESULTS: Prior to sample selection, across the full dataset of 31 152 649, cases with anxiety disorders accounted for 0.1%, bipolar disorders accounted for 0.3%, depressive disorders accounted for 0.4%, and schizophrenia and other psychotic disorders accounted for 0.1%. The total sample size was N = 224 051 with: (a) 13% for anxiety disorders (n = 29 111), (b) 30.3% for bipolar disorders (n = 67 926), (c) 43.4% for depressive disorders (n = 97 293), and (d) 13.3% for schizophrenia and other psychotic disorders (n = 29 721). Count data identified significant decreases including the following: 12.29% from 2008 to 2022 among the bipolar disorder group, 16.69% from 2019 to 2022 among the depressive disorder group, and 6.96% from 2006 to 2022 among the schizophrenia and other psychotic disorders group. CONCLUSION: This study has important implications for future research and clinical care related to co-occurring mental health and substance use disorders. Its findings demonstrate the need for further studies to examine how addiction treatment facilities are screening for and recording mental health disorder diagnoses. Future research is needed to clarify the prevalence of specific mental health diagnoses in the addiction treatment setting, including diagnoses such as anorexia nervosa and generalized anxiety disorder. This research would help determine specific treatment needs by using epidemiological data to provide a snapshot of the prevalence of these co-occurring conditions.

Source: Substance Use &amp Addiction Journal

DOI: 10.1177/29767342261445244

Authors: Orrin D. Ware, David A. Fiellin, Mark P. McGovern

Institutions: University of North Carolina at Chapel Hill, Yale University, Stanford Medicine, Stanford University

Language: English

Topic: Substance Abuse Treatment and Outcomes

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funder: National Institute on Drug Abuse