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Accepted for/Published in: JMIR Formative Research

Date Submitted: Dec 1, 2022
Date Accepted: Nov 1, 2023

The final, peer-reviewed published version of this preprint can be found here:

Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study

ElSherief M, Sumner S, Krishnasamy V, Jones C, Law R, Kacha-Ochana A, Schieber L, De Choudhury M

Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study

JMIR Form Res 2024;8:e44726

DOI: 10.2196/44726

PMID: 38393772

PMCID: 10924265

Identification of Myths and Misinformation about Treatment for Opioid Use Disorder: Infodemiology Study of Social Media

  • Mai ElSherief; 
  • Steven Sumner; 
  • Vikram Krishnasamy; 
  • Christopher Jones; 
  • Royal Law; 
  • Akadia Kacha-Ochana; 
  • Lyna Schieber; 
  • Munmun De Choudhury

ABSTRACT

Background:

Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed.

Objective:

Assessing social media posts from Twitter, YouTube, Reddit, and Drugs-Forum.com for the presence of health misinformation about treatment for OUD.

Methods:

We developed a multi-stage analytic pipeline to assess social media posts from Twitter, YouTube, Reddit, and Drugs-Forum.com for the presence of health misinformation about treatment for OUD. Our approach first utilized document embeddings to identify potential new statements of misinformation from known myths. These statements were grouped into themes using hierarchical agglomerative clustering and public health experts then reviewed results for misinformation.

Results:

We collected a total of 19,953,599 posts discussing opioid-related content across the aforementioned platforms. Our multi-stage analytic pipeline identified seven main clusters or discussion themes. Among a high-yield dataset of posts (N=303) for further public health expert review, these included discussion about potential treatments for opioid use disorder (N=90, 29.8%), the nature of addiction (N=68, 22.5%), pharmacologic properties of substances (N=52, 16.88%), injection drug use (N=36, 11.9%), pain and opioids (N=28, 9.27%), physical dependence of medications (N=22, 7.2%), and tramadol use (N=7, 2.3%). Public health expert review of content within each cluster identified the presence of misinformation and myths beyond those used as seed myths to initialize the algorithm.

Conclusions:

Identifying and addressing misinformation through appropriate communication strategies could be an increasingly important component to preventing overdose deaths. To further this goal, we developed and tested an approach to aid in the identification of myths and misinformation about OUD from large-scale social media content.


 Citation

Please cite as:

ElSherief M, Sumner S, Krishnasamy V, Jones C, Law R, Kacha-Ochana A, Schieber L, De Choudhury M

Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study

JMIR Form Res 2024;8:e44726

DOI: 10.2196/44726

PMID: 38393772

PMCID: 10924265

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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