Researchers have shown a relationship between mental health disorders and alcohol dependence. However, only 5-10% of individuals with substance use problems co-occurring with mental health problems are correctly identified. The purpose of this research was to identify predictors of relapse using three different instruments of varying complexity: the Patient Health Questionnaire-9 (PHQ-9), the Modified Mini Screen (MMS), and the Millon Clinical Multiaxial Inventory-III (MCMI-III). Researchers have found that using alcohol produces relief, similar to a pharmacological intervention, from troublesome mental health symptoms that individuals experience. Considering this association, the self-medication hypothesis was the conceptual lens used for the study as it provides a practical framework for analyzing the relationship between mental health disorders and relapse. At the request of this researcher, data were collected on 45 individuals who were provided detoxification services at a public treatment facility in central Wisconsin. Regression analyses were conducted and identified a statistically significant, although weak, predictive relationship between relapse and the variable of depression as measured by the PHQ-9 (R = .311a, R2 = .097, p = .037), and depression as measured by the MCMI-III (R = .364a, R2 = .133, p = .014). The implications for positive social change from this study include the potential to increase the effectiveness and efficiency in identifying co-occurring mental health disorders among individuals who are treated for alcohol detoxification, enhancing the accuracy of referrals for aftercare, and reducing readmissions for detoxification amongst the individuals served.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-1502 |
Date | 01 January 2015 |
Creators | Simonson, Toni Lee |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
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