scholarly journals Identifying Online Advice-Seekers for Recovering from Opioid Use Disorder

2021 ◽  
Author(s):  
Gian-Gabriel P. Garcia ◽  
Ramin Dehghanpoor ◽  
Erin J. Stringfellow ◽  
Marichi Gupta ◽  
Jillian Rochelle ◽  
...  
Keyword(s):  
Social Support ◽  
Social Network ◽  
Network Analysis ◽  
Medication Use ◽  
Opioid Use Disorder ◽  
Medical Advice ◽  
Opioid Use ◽  
Explanatory Variables ◽  
Advice Seeking ◽  
Use Stage

AbstractBackgroundOnline communities can provide social support for those recovering from opioid use disorder. However, advice-seekers on these platforms risk exposure to uncurated medical advice, potentially harming their health or recovery efforts. The objective of this analysis is to combine text annotation, social network analysis, and statistical modeling to identify advice-seekers on online social media for buprenorphine-naloxone use and study their characteristics.MethodsWe collected 5,258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking (n=137) and not advice-seeking (n=65). We also annotated each posting user’s medication use stage and quantified their connectedness using social network analysis. In order to analyze the relationship between advice-seeking with a user’s social connectivity and medication use stage, we constructed four models which varied in explanatory variables.ResultsThe stepwise model (containing “total degree” (P=0.002), “using: inducting/tapering” (P<0.001), and “using: other” (P=0.01) as significant explanatory variables) outperformed all other models. We found that users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than users who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone.ConclusionsOur findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.

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

2020 ◽  
Author(s):  
Navin Kumar ◽  
William Oles ◽  
Benjamin A. Howell ◽  
Kamila Janmohamed ◽  
Selena T. Lee ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Treatment Outcomes ◽  
Opioid Use Disorder ◽  
Social Connections ◽  
Opioid Use ◽  
Network Support ◽  
Social Network Support ◽  
Partner Relationships

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.

scholarly journals Social Network Analysis of the Effects of a Social Media–Based Weight Loss Intervention Targeting Adults of Low Socioeconomic Status: Single-Arm Intervention Trial

10.2196/24690 ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. e24690
Author(s):  
Ran Xu ◽  
David Cavallo
Keyword(s):  
Social Support ◽  
Social Media ◽  
Weight Loss ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Self Efficacy ◽  
Web Based ◽  
Network Characteristics ◽  
Using Data

Background Obesity is a known risk factor for cardiovascular disease risk factors, including hypertension and type II diabetes. Although numerous weight loss interventions have demonstrated efficacy, there is considerably less evidence about the theoretical mechanisms through which they work. Delivering lifestyle behavior change interventions via social media provides unique opportunities for understanding mechanisms of intervention effects. Server data collected directly from web-based platforms can provide detailed, real-time behavioral information over the course of intervention programs that can be used to understand how interventions work. Objective The objective of this study was to demonstrate how social network analysis can facilitate our understanding of the mechanisms underlying a social media–based weight loss intervention. Methods We performed secondary analysis by using data from a pilot study that delivered a dietary and physical activity intervention to a group of participants via Facebook. We mapped out participants’ interaction networks over the 12-week intervention period and linked participants’ network characteristics (eg, in-degree, out-degree, network constraint) to participants’ changes in theoretical mediators (ie, dietary knowledge, perceived social support, self-efficacy) and weight loss by using regression analysis. We also performed mediation analyses to explore how the effects of social network measures on weight loss could be mediated by the aforementioned theoretical mediators. Results In this analysis, 47 participants from 2 waves completed the study and were included. We found that increases in the number of posts, comments, and reactions significantly predicted weight loss (β=–.94, P=.04); receiving comments positively predicted changes in self-efficacy (β=7.81, P=.009), and the degree to which one’s network neighbors are tightly connected with each other weakly predicted changes in perceived social support (β=7.70, P=.08). In addition, change in self-efficacy mediated the relationship between receiving comments and weight loss (β=–.89, P=.02). Conclusions Our analyses using data from this pilot study linked participants’ network characteristics with changes in several important study outcomes of interest such as self-efficacy, social support, and weight. Our results point to the potential of using social network analysis to understand the social processes and mechanisms through which web-based behavioral interventions affect participants’ psychological and behavioral outcomes. Future studies are warranted to validate our results and to further explore the relationship between network dynamics and study outcomes in similar and larger trials.

scholarly journals Using Social Network Analysis to Understand the Effects of a Social Media-based Weight Loss Intervention Targeting Low-SES Adults (Preprint)

2020 ◽  
Author(s):  
Ran Xu ◽  
David Cavallo
Keyword(s):  
Social Support ◽  
Social Media ◽  
Weight Loss ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Self Efficacy ◽  
Network Characteristics ◽  
Using Data ◽  
The Relationship

BACKGROUND Obesity is a known risk factor for cardiovascular disease (CVD) risk factors including hypertension and type II diabetes. Although numerous weight-loss interventions have demonstrated efficacy, there is considerably less evidence about the theoretical mechanisms through which they work. Delivering lifestyle behavior change interventions via social media provides unique opportunities for understanding mechanisms of intervention effects. Server data collected directly from online platforms can provide detailed, real-time behavioral information over the course of intervention programs that can be used to understand how interventions work. OBJECTIVE The objective of this study was to demonstrate how social network analysis can facilitate our understanding of the mechanisms underlying a social-media based weight loss intervention. METHODS This study performed secondary analysis using data from a pilot study that delivered a dietary and physical activity intervention to a group of low-SES participants via Facebook. We mapped out participants’ interaction networks over the 12-week intervention period, and linked participants’ network characteristics (e.g. in-degree, out-degree and network constraint) to participants’ changes in theoretical mediators (i.e. dietary knowledge, perceived social support, self-efficacy) and weight loss using regression analysis. This study also performed mediation analyses to explore how the effects of social network measures on weight loss could be mediated by the aforementioned theoretical mediators. RESULTS 47 participants from two waves completed the study and were included in the analysis. We found that participants creating posts, comments and reactions predicted weight-loss (β=-.94, P=.042); receiving comments positively predicted changes in self-efficacy (β=7.81, P=.009); the degree to which one’s network neighbors are tightly connected with each other weakly predicted changes in perceived social support (β=7.70, P=.08). In addition, change in self-efficacy mediated the relationship between receiving comments and weight-loss (Indirect effect=-.89, P=.017). CONCLUSIONS Our analyses using data from this pilot study have linked participants’ network characteristics with changes in several important study outcomes of interest, such as self-efficacy, social support and weight. Our results point to the potential of using social network analysis to understand the social processes and mechanisms through which online behavioral interventions affects participants’ psychological and behavioral outcomes. Future studies are warranted to validate our results and further explore the relationship between network dynamics and study outcomes in similar and larger trials.

Perceived risk of opioid use disorder secondary to opioid analgesic medication use by the general population in France

2021 ◽  
Author(s):  
Justine Lavergne ◽  
Marion Debin ◽  
Thierry Blanchon ◽  
Vittoria Colizza ◽  
Lise Dassieu ◽  
...  
Keyword(s):  
General Population ◽  
Perceived Risk ◽  
Opioid Analgesic ◽  
Medication Use ◽  
Opioid Use Disorder ◽  
Opioid Use ◽  
Analgesic Medication

scholarly journals Opioid Medication Use Among Chronic Non-Cancer Pain Patients Assessed with a Modified Drug Effects Questionnaire and the Association with Opioid Use Disorder

2020 ◽  
Vol Volume 13 ◽  
pp. 2697-2705
Author(s):  
Joseph A Boscarino ◽  
Carrie A Withey ◽  
Ryan J Dugan ◽  
Yirui Hu ◽  
Jessica Auciello ◽  
...  
Keyword(s):  
Cancer Pain ◽  
Medication Use ◽  
Drug Effects ◽  
Opioid Use Disorder ◽  
Opioid Use ◽  
Opioid Medication ◽  
Pain Patients

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
Keyword(s):  
Systematic Review ◽  
Social Network ◽  
Treatment Outcomes ◽  
Systematic Reviews ◽  
Opioid Use Disorder ◽  
Opioid Use ◽  
Support Functions ◽  
Network Support ◽  
Social Network Support

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.

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