scholarly journals The role of social network support on treatment outcomes for medication for opioid use disorder: a systematic review protocol

2020 ◽  
Author(s):  
Navin Kumar ◽  
Benjamin A. Howell ◽  
Marcus Alexander ◽  
Patrick G. O'Connor

Abstract Background Although medications for opioid use disorder (MOUD) models are the most efficacious evidence-based treatment for opioid use disorder, there remains a high percentage of patients experiencing unfavorable treatment outcomes. Greater understanding of how social network support functions with respect to MOUD treatment outcomes may possibly improve treatment outcomes. Social network support are the kinds of support, such as assistance or help, that people receive from friends, family, peers and neighbors, paid or unpaid, in their social network. We aim to provide quality evidence to understand the role of social network support on MOUD treatment outcomes. Methods A systematic review of experimental and observational studies will be conducted. PubMed, MEDLINE, Embase, PsycINFO and Sociological Abstracts will be searched. Primary outcomes will include adherence to MOUD, defined as continuation in or completion of an MOUD program; and opioid use, defined as the percentage of urine samples negative for opioids and/or self-reported drug use. The systematic review will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Quality assessments will be conducted using criteria from the Cochrane Handbook. A narrative synthesis will be conducted for all included studies. Discussion This systematic review seeks to provide policymakers, administrators, practitioners and researchers with a systematic and reproducible strategy to query the literature around the role of social network support on MOUD treatment outcomes. Systematic review registration International Prospective Register for Systematic Reviews (PROSPERO), CRD42018095645.

2020 ◽  
Author(s):  
Navin Kumar ◽  
Benjamin A. Howell ◽  
Marcus Alexander ◽  
Patrick G. O'Connor

Abstract Background Although medications for opioid use disorder (MOUD) models are the most efficacious evidence-based treatment for opioid use disorder, there remains a high percentage of patients experiencing unfavorable treatment outcomes. Greater understanding of how social network support functions with respect to MOUD treatment outcomes may possibly increase treatment outcomes. Social network support are the kinds of support, such as assistance or help, that people receive from friends, family, peers and neighbors, paid or unpaid, in their social network. We aim to provide quality evidence to understand the role of social network support on MOUD treatment outcomes. Methods A systematic review of experimental and observational studies will be conducted. PubMed, MEDLINE, Embase, PsycINFO and Sociological Abstracts will be searched, updated to capture current literature. Primary outcomes will include adherence to MOUD, defined as continuation in or completion of an MOUD program; and opioid use, defined as the percentage of urine samples negative for opioids and/or self-reported drug use. The systematic review will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Quality assessments will be conducted using criteria from the Cochrane Handbook. A narrative synthesis will be conducted for all included studies. Discussion This systematic review seeks to provide policymakers, administrators, practitioners and researchers with a systematic and reproducible strategy to query the literature around the role of social network support on MOUD treatment outcomes. Systematic review registration International Prospective Register for Systematic Reviews (PROSPERO), CRD42018095645.


2020 ◽  
Author(s):  
Navin Kumar ◽  
William Oles ◽  
Benjamin A. Howell ◽  
Kamila Janmohamed ◽  
Selena T. Lee ◽  
...  

AbstractBackgroundSocial connections can lead to contagion of healthy behaviors. Successful treatment of patients with opioid use disorder, as well as recovery of their communities from the opioid epidemic, may lay in rebuilding social networks. Strong social networks of support can reinforce the benefits of medication treatments that are the current standard of care and the most effective tool physicians have to fight the opioid epidemic.MethodsWe conducted a systematic review of electronic research databases, specialist journals and grey literature up to August 2020 to identify experimental and observational studies of social network support in patient populations receiving medication for opioid use disorder (MOUD). We place the studies into a conceptual framework of dynamic social networks, examining the role of networks before MOUD treatment is initiated, during the treatment, and in the long-term following the treatment. We analyze the results across three sources of social network support: partner relationships, family, and peer networks. We also consider the impact of negative social connections.ResultsOf 5193 articles screened, 46 studies were identified as meeting inclusion criteria (12 were experimental and 34 were observational). 39 studies indicated that social network support, or lack thereof, had a statistically significant relationship with improved MOUD treatment outcomes. We find the strongest support for the positive impact of family and partner relationships when integrated into treatment attempts. We also identify strong evidence for a negative impact of maintaining contacts with the drug-using network on treatment outcomes.ConclusionsSocial networks significantly shape effectiveness of opioid use disorder treatments. While negative social ties reinforce addiction, positive social support networks can amplify the benefits of medication treatments. Targeted interventions to reconstruct social networks can be designed as a part of medication treatment with their effects evaluated in improving patients’ odds of recovery from opioid use disorder and reversing the rising trend in opioid deaths.


2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Nitika Sanger ◽  
Meha Bhatt ◽  
Laura Zielinski ◽  
Stephanie Sanger ◽  
Hamnah Shahid ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Nitika Sanger ◽  
Meha Bhatt ◽  
Nikhita Singhal ◽  
Balpreet Panesar ◽  
Alessia D’Elia ◽  
...  

2021 ◽  
pp. 107026
Author(s):  
Sarah Meshberg-Cohen ◽  
R. Ross MacLean ◽  
Ashley M. Schnakenberg Martin ◽  
Mehmet Sofuoglu ◽  
Ismene L. Petrakis

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