Literature DB >> 35627818

Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use.

Gian-Gabriel P Garcia1, Ramin Dehghanpoor2, Erin J Stringfellow3, Marichi Gupta3, Jillian Rochelle3, Elizabeth Mason3, Toyya A Pujol4, Mohammad S Jalali3,5.   

Abstract

BACKGROUND: Online communities such as Reddit can provide social support for those recovering from opioid use disorder. However, it is unclear whether and how advice-seekers differ from other users. Our research addresses this gap by identifying key characteristics of r/suboxone users that predict advice-seeking behavior.
OBJECTIVE: The objective of this analysis is to identify and describe advice-seekers on Reddit for buprenorphine-naloxone use using text annotation, social network analysis, and statistical modeling techniques.
METHODS: We collected 5258 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) or not advice-seeking (n = 65). We also annotated each posting user's buprenorphine-naloxone use status (current versus formerly taking and, if currently taking, whether inducting or tapering versus other stages) and quantified their connectedness using social network analysis. To analyze the relationship between Reddit users' advice-seeking and their social connectivity and medication use status, we constructed four models which varied in their inclusion of explanatory variables for social connectedness and buprenorphine use status.
RESULTS: The stepwise model containing "total degree" (p = 0.002), "using: inducting/tapering" (p < 0.001), and "using: other" (p = 0.01) outperformed all other models. Reddit users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than those 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.
CONCLUSIONS: Our 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.

Entities:  

Keywords:  Suboxone; advice-seeking; buprenorphine-naloxone; opioid use disorder; social network analysis

Mesh:

Substances:

Year:  2022        PMID: 35627818      PMCID: PMC9141384          DOI: 10.3390/ijerph19106281

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   4.614


  25 in total

Review 1.  Recommendations for buprenorphine and methadone therapy in opioid use disorder: a European consensus.

Authors:  Maurice Dematteis; Marc Auriacombe; Oscar D'Agnone; Lorenzo Somaini; Néstor Szerman; Richard Littlewood; Farrukh Alam; Hannu Alho; Amine Benyamina; Julio Bobes; Jean Pierre Daulouede; Claudio Leonardi; Icro Maremmani; Marta Torrens; Stephan Walcher; Michael Soyka
Journal:  Expert Opin Pharmacother       Date:  2017-12-03       Impact factor: 3.889

2.  Primary Care and the Opioid-Overdose Crisis - Buprenorphine Myths and Realities.

Authors:  Sarah E Wakeman; Michael L Barnett
Journal:  N Engl J Med       Date:  2018-07-05       Impact factor: 91.245

Review 3.  Barriers and Facilitators to the Use of Medications for Opioid Use Disorder: a Rapid Review.

Authors:  Katherine Mackey; Stephanie Veazie; Johanna Anderson; Donald Bourne; Kim Peterson
Journal:  J Gen Intern Med       Date:  2020-11-03       Impact factor: 5.128

4.  Network measures of advice-seeking and resource sharing are related to well-being in recovery homes.

Authors:  Leonard A Jason; Mayra Guerrero; Meghan Salomon-Amend; Gabrielle Lynch; Ed Stevens; John M Light; Mike Stoolmiller; Nathan J Doogan
Journal:  Int J Drug Policy       Date:  2020-11-24

5.  Stroke survivors and their families receive information and support on an individual basis from an online forum: descriptive analysis of a population of 2348 patients and qualitative study of a sample of participants.

Authors:  Anna De Simoni; Andrew Shanks; Chantal Balasooriya-Smeekens; Jonathan Mant
Journal:  BMJ Open       Date:  2016-04-06       Impact factor: 2.692

6.  Interaction effects in the association between methadone maintenance therapy and experiences of racial discrimination in U.S. healthcare settings.

Authors:  George Pro; Nick Zaller
Journal:  PLoS One       Date:  2020-02-06       Impact factor: 3.240

7.  Thematic Analysis of Reddit Content About Buprenorphine-naloxone Using Manual Annotation and Natural Language Processing Techniques.

Authors:  Rachel Lynn Graves; Jeanmarie Perrone; Mohammed Ali Al-Garadi; Yuan-Chi Yang; Jennifers Love; Karen O'Connor; Graciela Gonzalez-Hernandez; Abeed Sarker
Journal:  J Addict Med       Date:  2021-12-23       Impact factor: 4.647

8.  Analysing the connectivity and communication of suicidal users on twitter.

Authors:  Gualtiero B Colombo; Pete Burnap; Andrei Hodorog; Jonathan Scourfield
Journal:  Comput Commun       Date:  2016-01-01       Impact factor: 3.167

9.  Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users' perceptions.

Authors:  Marichi Gupta; Aditya Bansal; Bhav Jain; Jillian Rochelle; Atharv Oak; Mohammad S Jalali
Journal:  Int J Med Inform       Date:  2020-11-10       Impact factor: 4.046

10.  Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach.

Authors:  Mai ElSherief; Steven A Sumner; Christopher M Jones; Royal K Law; Akadia Kacha-Ochana; Lyna Shieber; LeShaundra Cordier; Kelly Holton; Munmun De Choudhury
Journal:  J Med Internet Res       Date:  2021-12-22       Impact factor: 5.428

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  1 in total

1.  Temporal trends in health worker social media communication during the COVID-19 pandemic.

Authors:  Julian D Ford; Davide Marengo; Miranda Olff; Cherie Armour; Jon D Elhai; Zack Almquist; Emma S Spiro
Journal:  Res Nurs Health       Date:  2022-09-19       Impact factor: 2.238

  1 in total

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