Concerns among people who use opioids during the COVID-19 pandemic: a natural language processing analysis of social media posts

Abstract

Background Timely 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. Methods In 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. Results Seventy-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). Conclusions Conversations 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.

Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature

“…Using the Python Reddit Application Programming Interface (API) Wrapper (PRAW) ( 39 ), we collected all publicly available posts from three subreddits- r/methadone, r/suboxone (the primary subreddit for discussions about buprenorphine), r/naltrexone that were retrievable via the API. We chose these subreddits based on our familiarity with their contents from prior works on substance use ( 34 , 35 , 38 , 40 ). These subreddits typically contain discussions between people who are currently taking, have taken in the past, or are considering taking MOUDs.…”

“…In recent works closely related to ours, Chen et al examined stigma associated with substance use from discussions on Reddit, reporting that internalized stigma was the most commonly expressed, and temporal and affective factors were prominent ( 32 ). Reddit was also described as an important source of substance use-related information during COVID-19, particularly because subscribers often shared their concerns and provided social support to each other ( 33 , 34 ). Studies on specific substances such as cannabis and fentanyl based on Reddit data have also been reported ( 35 , 36 ).…”

Investigating Substance Use via Reddit: Systematic Scoping Review

“…Anonymous data [18,19,[21][22][23][26][27][28][29][30][31]33,34,38,45,55,57,60,61,65,[72][73][74][75] 24 (40) Reddit is one of the most popular social networking sites.…”

Year 2022 in Medical Natural Language Processing: Availability of Language Models as a Step in the Democratization of NLP in the Biomedical Area

“…• when other sources of information are not freely available, such as in languages other than English [7,9,19,20,22,38,43,47]; • when researchers investigate questions related to patients and population, while these questions are not discussed with medical doctors or require large population samples. We can mention for instance sentiment analysis on medication and vaccines [7,20,33,38,43,47], and adverse drug effects [76,77]; • when mental health of patients is concerned in cases like depression [9, 4, 78], eating disorders [79], suicide detection and prevention [19,80], quality of life of patients [31,81], and drug misuse [82][83][84].…”