Ethan Sahker1, Saba Rasheed Ali2, Stephan Arndt3. 1. Department of Psychological and Quantitative Foundations, Counseling Psychology Program, College of Education, University of Iowa, 361 Lindquist Center, Iowa City, IA, 52242, USA; Department of Psychiatry, University of California San Diego, VA San Diego Healthcare System, 2121 San Diego Avenue, San Diego, CA, 92110, USA. Electronic address: ethansahker@gmail.com. 2. Department of Psychological and Quantitative Foundations, Counseling Psychology Program, College of Education, University of Iowa, 361 Lindquist Center, Iowa City, IA, 52242, USA. Electronic address: saba-ali@uiowa.edu. 3. Department of Psychiatry, Carver College of Medicine, University of Iowa, 451 Newton Road 200 Medicine Administration Building, Iowa City, IA, 52242, USA; Department of Biostatistics, College of Public Health, University of Iowa, 145 N. Riverside Drive 100 CPHB, Iowa City, IA, 52242, USA. Electronic address: stephan-arndt@uiowa.edu.
Abstract
BACKGROUND: Recovery capital represents client strengths associated with substance use disorder (SUD) recovery. Employment is part of recovery capital supporting long-term recovery. However, specific employment recovery capital (ERC) factors associated with SUD recovery are not well understood. METHODS: The present study used retrospective logistic regression modeling to predict treatment completion at discharge and substance use at six-month follow-up from employment variables at intake and follow-up. An additional exploratory follow-up of ERC Change is further investigated. Existing clinical data from a random selection of all Iowa SUD treatment facilities receiving public funding from 1999-2016. Clients in the study (N = 8,925) were a mean age of 31.7 (SD = 11.8), mostly male (67.2%), and primarily White (86.6%). Measurements included substance use, treatment completion, ERC Change, demographic, and treatment statistical control variables. RESULTS: Results demonstrated that employment variables at intake predicted greater successful treatment completion, p < 0.0001. However, the same employment variables were predictive of maintained and increased use at six-month follow-up. Further investigation showed the best predictors of post-treatment recovery was a change in employment variables including months employed increase (AOR = 1.53, 95% CI = 1.34-1.75) and days missed from work due to substance use decrease (AOR = 2.43, 95% CI = 2.00-2.96). CONCLUSIONS: Researchers and providers can help improve client recovery with intervention design, consultation, and policies focused on vocational growth in addition to employment benchmarks of gross income, full-time employment, occupation, primary support, months employed, and work missed. ERC is a promising route to improve the lives for those involved with substance use disorders.
BACKGROUND: Recovery capital represents client strengths associated with substance use disorder (SUD) recovery. Employment is part of recovery capital supporting long-term recovery. However, specific employment recovery capital (ERC) factors associated with SUD recovery are not well understood. METHODS: The present study used retrospective logistic regression modeling to predict treatment completion at discharge and substance use at six-month follow-up from employment variables at intake and follow-up. An additional exploratory follow-up of ERC Change is further investigated. Existing clinical data from a random selection of all Iowa SUD treatment facilities receiving public funding from 1999-2016. Clients in the study (N = 8,925) were a mean age of 31.7 (SD = 11.8), mostly male (67.2%), and primarily White (86.6%). Measurements included substance use, treatment completion, ERC Change, demographic, and treatment statistical control variables. RESULTS: Results demonstrated that employment variables at intake predicted greater successful treatment completion, p < 0.0001. However, the same employment variables were predictive of maintained and increased use at six-month follow-up. Further investigation showed the best predictors of post-treatment recovery was a change in employment variables including months employed increase (AOR = 1.53, 95% CI = 1.34-1.75) and days missed from work due to substance use decrease (AOR = 2.43, 95% CI = 2.00-2.96). CONCLUSIONS: Researchers and providers can help improve client recovery with intervention design, consultation, and policies focused on vocational growth in addition to employment benchmarks of gross income, full-time employment, occupation, primary support, months employed, and work missed. ERC is a promising route to improve the lives for those involved with substance use disorders.
Authors: David Eddie; Corrie L Vilsaint; Lauren A Hoffman; Brandon G Bergman; John F Kelly; Bettina B Hoeppner Journal: J Subst Abuse Treat Date: 2020-03-09
Authors: Akila R Jayamaha; Nimesha D M Herath; Nishadi D Dharmarathna; Hasini S Sandakumari; Nadeeka D K Ranadeva; Medhavi M Fernando; Nirmani A W Samarakoon; Priyangi N Amarabandu; Bhadrani Senanayake; Thamara Darshana; Nilani Renuka; Kerstin L Samarasinghe; Neluka Fernando Journal: Qual Life Res Date: 2022-10-16 Impact factor: 3.440