• Addictive behaviors · Nov 2012

    Pain depression and sleep disorders among methadone maintenance treatment patients.

    • Dorit Pud, Cheryl Zlotnick, and Eli Lawental.
    • The Cheryl Spencer Department of Nursing, Faculty of Welfare and Health Sciences, University of Haifa, Mt Carmel, Haifa Israel 31905. doritpud@research.haifa.ac.il
    • Addict Behav. 2012 Nov 1; 37 (11): 1205-10.

    BackgroundThe success of rehabilitation is not influenced solely by drug abstinence, but also by the state of general health and well-being, which for patients in methadone maintenance treatment (MMT) frequently is compromised by experiencing pain, depression and sleep disorders. Accordingly, this study sought to (1) characterize clusters of MMT patients who experienced different levels of these symptoms and (2) examine the association between these clusters and quality of life (QOL) measures.MethodsA convenience sample of MMT patients (n=73) completed surveys containing four scales (Numeric Rating Scale on Pain, Center for Epidemiological Studies-Depression Scale, General Sleep Disturbance Scale, and Short Form-36 QOL). Homogenous clusters based on the symptom severity of pain, depression and sleep disturbances were created using a two-stage process of: hierarchical clustering and K-means cluster analysis.ResultsBased on the levels of symptoms, MMT patients were grouped as High (n=29), Moderate (n=26) or Low (n=18) symptom cluster members. The High symptom cluster group reported the highest severity levels of pain, depression and sleep disorders. Also, this group had the lowest scores on all QOL indices (p<0.05). Although pain, depression and sleep disorders effectively distinguish symptom clusters of MMT patients, pain was the single most important symptom differentiating MMT patients.ConclusionsSuccessful rehabilitation will necessitate interventions that target MMT patients with high levels of pain, depression and sleep disorders. To the best of our knowledge this study was innovative in its approach to identify the presence of this high risk group by using cluster methodology in the MMT population.Copyright © 2012 Elsevier Ltd. All rights reserved.

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