Margo Huffman, M. Cloeren, Orrin D. Ware, J. Frey, A. Greenblatt, Amanda Mosby, M. Oliver, R. Imboden, Alicia T. Bazell, Jean M. Clement, M. Diaz-Abad
{"title":"Poor Sleep Quality and Other Risk Factors for Unemployment Among Patients on Opioid Agonist Treatment","authors":"Margo Huffman, M. Cloeren, Orrin D. Ware, J. Frey, A. Greenblatt, Amanda Mosby, M. Oliver, R. Imboden, Alicia T. Bazell, Jean M. Clement, M. Diaz-Abad","doi":"10.1177/11782218221098418","DOIUrl":null,"url":null,"abstract":"Purpose: Patients with opioid use disorder (OUD) face high rates of unemployment, putting them at higher risk of treatment nonadherence and poor outcomes, including overdose death. The objective of this study was to investigate sleep quality and its association with other biopsychosocial risk factors for unemployment in patients receiving opioid agonist treatment (OAT) for OUD. Methods: Using a cross-sectional survey design, participants from 3 OAT programs for OUD completed questionnaires to measure sleep quality (Pittsburgh Sleep Quality Index [PSQI]); pain disability; catastrophic thinking; injustice experience; quality of life; and self-assessed disability. Spearman’s rank correlation was used to test for associations between sleep quality and other study variables. Results: Thirty-eight participants completed the study, with mean age 45.6 ± 10.9 years, 27 (71.1%) males, and 16 (42.1%) reporting a high school diploma/equivalent certification as the highest level of academic attainment. Poor sleep quality (defined as PSQI > 5) was identified in 29 participants (76.3%) and was positively correlated with pain disability (r = 0.657, P < .01), self-assessed disability (r = 0.640, P < .001), symptom catastrophizing (r = 0.499, P < .001), and injustice experience (r = 0.642, P < .001), and negatively correlated with quality of life (r = −0.623, P < .001). Conclusions: There was a high prevalence of poor sleep quality in patients with OUD on OAT and this was associated with multiple known risk factors for unemployment. These findings warrant the consideration of regular screening for sleep problems and the inclusion of sleep-related interventions to improve sleep quality, decrease the unemployment rate, and enhance the recovery process for individuals with OUD undergoing OAT.","PeriodicalId":22185,"journal":{"name":"Substance Abuse: Research and Treatment","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Substance Abuse: Research and Treatment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11782218221098418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SUBSTANCE ABUSE","Score":null,"Total":0}
引用次数: 1
Abstract
Purpose: Patients with opioid use disorder (OUD) face high rates of unemployment, putting them at higher risk of treatment nonadherence and poor outcomes, including overdose death. The objective of this study was to investigate sleep quality and its association with other biopsychosocial risk factors for unemployment in patients receiving opioid agonist treatment (OAT) for OUD. Methods: Using a cross-sectional survey design, participants from 3 OAT programs for OUD completed questionnaires to measure sleep quality (Pittsburgh Sleep Quality Index [PSQI]); pain disability; catastrophic thinking; injustice experience; quality of life; and self-assessed disability. Spearman’s rank correlation was used to test for associations between sleep quality and other study variables. Results: Thirty-eight participants completed the study, with mean age 45.6 ± 10.9 years, 27 (71.1%) males, and 16 (42.1%) reporting a high school diploma/equivalent certification as the highest level of academic attainment. Poor sleep quality (defined as PSQI > 5) was identified in 29 participants (76.3%) and was positively correlated with pain disability (r = 0.657, P < .01), self-assessed disability (r = 0.640, P < .001), symptom catastrophizing (r = 0.499, P < .001), and injustice experience (r = 0.642, P < .001), and negatively correlated with quality of life (r = −0.623, P < .001). Conclusions: There was a high prevalence of poor sleep quality in patients with OUD on OAT and this was associated with multiple known risk factors for unemployment. These findings warrant the consideration of regular screening for sleep problems and the inclusion of sleep-related interventions to improve sleep quality, decrease the unemployment rate, and enhance the recovery process for individuals with OUD undergoing OAT.