Predictors of mental distress among substance abusers receiving inpatient treatment

Ellen Hoxmark,Rolf Wynn,Mary Nivison

doi:10.1186/1747-597x-5-15

Abstract

BackgroundMental distress measured by the HSCL-10 is used as an indicator of psychiatric disorders in population studies, where a higher level of mental distress has been shown to be related to demographic factors such as living conditions and level of education. The first aim of the study was to explore whether mental distress could be a valuable concept in substance use treatment. The second aim of the study was to explore to what degree mental distress among substance users at admission to treatment could be explained by the same demographic factors as in population studies, or whether treatment differences or differences in substance use would be better predictors of mental distress in this population.MethodsPatients (N = 185) who received inpatient substance use treatment in five different settings in Northern Norway participated in the study. HSCL-10 was used as a measure for mental distress at admission to treatment. The self-report measures AUDIT, DUDIT and DUDIT-E were used for measuring substance use and readiness for treatment. The patients' clinicians reported demographic and treatment factors. A three-block hierarchical multiple regression analysis was conducted to determine potential predictors of mental distress. Block 1 included demographic variables, Block 2 included treatment variables, and Block 3 substance use variables.ResultsPatients generally reported a high level of mental distress at admission to treatment, and 83% reported mental distress higher than the established cut-off level. Being female, having previously received psychiatric treatment, having a higher score on DUDIT and AUDIT, and using a larger number of substances all predicted a higher level of mental distress. The model explained 32% of the variance in mental distress.ConclusionsMental distress measured by the HSCL-10 can be a valuable concept in substance use treatment. The HSCL-10 can be useful in screening for patients who are in need of further assessment for psychiatric disorders. Female gender, previous psychiatric treatment, and higher use of substances all predicted a higher level of mental distress. The study underlines the importance of assessing the mental health of patients in substance use treatment.

Highlights

Clinical and epidemiological studies indicate high rates of co-occurring psychiatric disorders among people with substance use disorders (SUD) [1,2,3,4,5,6]
The patients in the short term unit reported a lower score on Alcohol Use Disorders Identification Test (AUDIT) and a higher score on Drug Use Disorders Identification Test (DUDIT) than the rest of the sample whereas patients in the dual diagnosis ward reported a higher score on DUDIT than the rest of the sample
The patients in the two long term units reported a higher score on AUDIT, a lower score on DUDIT and a lower number of substances used than the rest of the sample

Summary

Introduction

Clinical and epidemiological studies indicate high rates of co-occurring psychiatric disorders among people with substance use disorders (SUD) [1,2,3,4,5,6]. In a follow-up six years after treatment, Landheim et al [17] found that major depression together with early onset of SUD were independent predictors of relapse. In another recent longitudinal study of patients with heroin dependence, major depression was the diagnosis most consistently associated with poor outcomes after three years [18]. Mental distress measured by the HSCL-10 is used as an indicator of psychiatric disorders in population studies, where a higher level of mental distress has been shown to be related to demographic factors such as living conditions and level of education. The second aim of the study was to explore to what degree mental distress among substance users at admission to treatment could be explained by the same demographic factors as in population studies, or whether treatment differences or differences in substance use would be better predictors of mental distress in this population

Methods

Results

Discussion

Conclusion