Christine Anne Henriksen1, Murray B Stein, Tracie O Afifi, Murray W Enns, Lisa M Lix, Jitender Sareen. 1. Ms. Henriksen is with the Department of Psychology, Dr. Afifi and Dr. Lix are with the Department of Community Health Sciences, and Dr. Enns and Dr. Sareen are with the Department of Psychiatry, all at the University of Manitoba, Winnipeg, Manitoba, Canada (e-mail: umhenri5@cc.umanitoba.ca ). Dr. Stein is with the Departments of Psychiatry and Family and Preventive Medicine, University of California, San Diego.
Abstract
OBJECTIVE: Historically, meeting criteria for a mental disorder has been used as a proxy for the need for mental health services, yet research suggests that a significant proportion of disorders remit without treatment. In this study, risk factors for poor longitudinal outcomes of individuals with untreated common mental disorders were determined, with the goal of identifying individuals with unmet need and informing the development of targeted interventions. METHODS: Data came from the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC), a longitudinal, nationally representative survey of the adult U.S. population (age ≥18; N=34,653). Respondents were assessed for past-year depressive, anxiety, and substance use disorders and mental health service use via face-to-face interviews conducted at two time points, three years apart. Among respondents without a history of mental health treatment, logistic regression analyses examined factors associated with persistence of the disorder, comorbidity, or suicide attempt (that is, presence of any axis I disorder in the past year at wave 2 or any suicide attempt during the follow-up) versus spontaneous recovery of baseline disorders. RESULTS: Certain sociodemographic factors, comorbid mental disorders at baseline (such as three or more axis I disorders, adjusted odds ratio [AOR]=1.64, 95% confidence interval [CI]=1.27-2.12), and childhood maltreatment (AOR=1.47, CI=1.23-1.75) were predictors of disorder persistence, comorbidity, or suicide attempt in depressive, anxiety, and substance use disorders during the follow-up. CONCLUSIONS: In addition to considering the presence of a mental disorder, policy makers should consider other variables, such as childhood maltreatment and comorbidity, in estimating treatment need.
OBJECTIVE: Historically, meeting criteria for a mental disorder has been used as a proxy for the need for mental health services, yet research suggests that a significant proportion of disorders remit without treatment. In this study, risk factors for poor longitudinal outcomes of individuals with untreated common mental disorders were determined, with the goal of identifying individuals with unmet need and informing the development of targeted interventions. METHODS: Data came from the National Epidemiologic Survey of Alcohol and Related Conditions (NESARC), a longitudinal, nationally representative survey of the adult U.S. population (age ≥18; N=34,653). Respondents were assessed for past-year depressive, anxiety, and substance use disorders and mental health service use via face-to-face interviews conducted at two time points, three years apart. Among respondents without a history of mental health treatment, logistic regression analyses examined factors associated with persistence of the disorder, comorbidity, or suicide attempt (that is, presence of any axis I disorder in the past year at wave 2 or any suicide attempt during the follow-up) versus spontaneous recovery of baseline disorders. RESULTS: Certain sociodemographic factors, comorbid mental disorders at baseline (such as three or more axis I disorders, adjusted odds ratio [AOR]=1.64, 95% confidence interval [CI]=1.27-2.12), and childhood maltreatment (AOR=1.47, CI=1.23-1.75) were predictors of disorder persistence, comorbidity, or suicide attempt in depressive, anxiety, and substance use disorders during the follow-up. CONCLUSIONS: In addition to considering the presence of a mental disorder, policy makers should consider other variables, such as childhood maltreatment and comorbidity, in estimating treatment need.
Authors: Alessandra Diehl; Jales Clemente; Sandra C Pillon; Paulo R H Santana; Claudio J da Silva; Jair de J Mari Journal: Braz J Psychiatry Date: 2018-12-06 Impact factor: 2.697
Authors: Ryan D Burns; Yang Bai; Christopher D Pfledderer; Timothy A Brusseau; Wonwoo Byun Journal: Int J Environ Res Public Health Date: 2020-09-20 Impact factor: 3.390