Observational studySubstance abuse treatment, prevention, and policy2022
Concerns among people who use opioids during the COVID-19 pandemic: a natural language processing analysis of social media posts.
Observational study in Substance abuse treatment, prevention, and policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- User profiles of young breast cancer survivors on Chinese social media: machine learning-based text mining analysis study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Automated Risk Assessment of Opioid Use: Analysis Using Pre-Trained Transformers on Social Media Data.JMIR infodemiology · 2026Article
- Mining Social Media for Barriers to Opioid Recovery with LLMs.Proceedings of the ... Workshop on Patient-Oriented Language Processing · 2025Article
- Large-Scale Deep Learning-Enabled Infodemiological Analysis of Substance Use Patterns on Social Media: Insights From the COVID-19 Pandemic.JMIR infodemiology · 2025Article
- Which social media platforms facilitate monitoring the opioid crisis?PLOS digital health · 2025Article
- The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review.JMIR infodemiology · 2024Article
- Detecting Substance Use Disorder Using Social Media Data and the Dark Web: Time- and Knowledge-Aware Study.JMIRx med · 2024Article
- First-hand accounts of structural stigma toward people who use opioids on Reddit.Social science & medicine (1982) · 2024Article
- Investigating Substance Use via Reddit: Systematic Scoping Review.Journal of medical Internet research · 2023Article
- Year 2022 in Medical Natural Language Processing: Availability of Language Models as a Step in the Democratization of NLP in the Biomedical Area.Yearbook of medical informatics · 2023Article
- Synthesising evidence of the effects of COVID-19 regulatory changes on methadone treatment for opioid use disorder: implications for policy.The Lancet. Public health · 2023Review
- Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature.Frontiers in public health · 2023Article
- Experiments with LDA and Top2Vec for embedded topic discovery on social media data-A case study of cystic fibrosis.Frontiers in artificial intelligence · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTimely data from official sources regarding the impact of the COVID-19 pandemic on people who use prescription and illegal opioids is lacking. We conducted a large-scale, natural language processing (NLP) analysis of conversations on opioid-related drug forums to better understand concerns among people who use opioids.
methodsIn this retrospective observational study, we analyzed posts from 14 opioid-related forums on the social network Reddit. We applied NLP to identify frequently mentioned substances and phrases, and grouped the phrases manually based on their contents into three broad key themes: (i) prescription and/or illegal opioid use; (ii) substance use disorder treatment access and care; and (iii) withdrawal. Phrases that were unmappable to any particular theme were discarded. We computed the frequencies of substance and theme mentions, and quantified their volumes over time. We compared changes in post volumes by key themes and substances between pre-COVID-19 (1/1/2019-2/29/2020) and COVID-19 (3/1/2020-11/30/2020) periods.
resultsSeventy-seven thousand six hundred fifty-two and 119,168 posts were collected for the pre-COVID-19 and COVID-19 periods, respectively. By theme, posts about treatment and access to care increased by 300%, from 0.631 to 2.526 per 1000 posts between the pre-COVID-19 and COVID-19 periods. Conversations about withdrawal increased by 812% between the same periods (0.026 to 0.235 per 1,000 posts). Posts about drug use did not increase (0.219 to 0.218 per 1,000 posts). By substance, among medications for opioid use disorder, methadone had the largest increase in conversations (20.751 to 56.313 per 1,000 posts; 171.4% increase). Among other medications, posts about diphenhydramine exhibited the largest increase (0.341 to 0.927 per 1,000 posts; 171.8% increase).
conclusionsConversations on opioid-related forums among people who use opioids revealed increased concerns about treatment and access to care along with withdrawal following the emergence of COVID-19. Greater attention to social media data may help inform timely responses to the needs of people who use opioids during COVID-19.
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