Evidence map›Paper›PMID 34864788›Full record

ArticleJournal of addiction medicine

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

Rachel Lynn Graves, Jeanmarie Perrone, Mohammed Ali Al-Garadi, Yuan-Chi Yang, Jennifers Love, Karen O'Connor, Graciela Gonzalez-Hernandez, Abeed Sarker

Open access · hybridAbstract read
In one paragraph

Article in Journal of addiction medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.1field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 26 citations in OpenAlex.

  1. Curation and Extraction of Drug-Related Entities from Reddit Platform.Proceedings. IEEE International Conference on Healthcare Informatics · 2026
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  6. Large-Scale Analysis of Online Questions Related to Opioid Use Disorder on Reddit.Proceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media · 2025
    Article
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  12. Investigating Substance Use via Reddit: Systematic Scoping Review.Journal of medical Internet research · 2023
    Article
  13. Automatic Detection of Intimate Partner Violence Victims from Social Media for Proactive Delivery of Support.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  14. Article
  15. Article
  16. Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use.International journal of environmental research and public health · 2022
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Rachel Lynn GravesFrom the Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA (RLG, JP); Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Building, Atlanta, GA, USA (MAA-G, Y-CY, AS); Department of Emergency Medicine, School of Medicine, Oregon Health and Science University, Portland, OR, USA (JSL); Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (KC, GG-H); Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA (AS).
Jeanmarie Perrone
Mohammed Ali Al-Garadi
Yuan-Chi Yang
Jennifers Love
Karen O'Connor
Graciela Gonzalez-Hernandez
Abeed Sarker
GGG (France) · FR

Funding

Mining Social Media Big Data for Toxicovigilance: Automating the Monitoring of Prescription Medication Abuse via Natural Language Processing and Machine Learning MethodsR01DA046619 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI SARKER, ABEED H · 2018 to 2021
$1.4M
NIDA NIH HHS R01 DA046619
6 · The paper itself

Abstract

backgroundOpioid use disorder (OUD) is a major public health crisis for which buprenorphine-naloxone is an effective evidence-based treatment. Analysis of Reddit data yields detailed information about firsthand experiences with buprenorphine-naloxone that has the potential to inform treatment of OUD.

methodsWe conducted a thematic analysis of posts about buprenorphine-naloxone from a Reddit forum in which Reddit users anonymously discuss topics related to opioid use. We used an application programming interface to retrieve posts about buprenorphine-naloxone, then applied natural language processing to generate meta-information and curate samples of salient posts. We manually categorized posts according to their content and conducted natural language processing-aided analysis of posts about buprenorphine tapering strategies, withdrawal symptoms, and adjunctive substances/behaviors useful in the tapering process.

resultsA total of 16,146 posts from 1933 redditors were retrieved from the /r/suboxone subreddit. Thematic analysis of sample posts (N = 200) revealed descriptions of personal experiences (74%), nonpersonal accounts (24%), and other content (2%). Among redditors who reported tapering to termination (N = 40), 0.063 mg and 0.125 mg were the most common termination doses. Fatigue, gastrointestinal disturbance, and mood disturbance were the most frequent adverse effects, and loperamide and vitamins/dietary supplements the most frequently discussed adverse effects adjunctive substances/behaviors respectively.

conclusionsDiscussions on Reddit are rich in information about buprenorphine-naloxone. Information derived from analysis of Reddit posts about buprenorphine-naloxone may not be available elsewhere and may help providers improve treatment of people with OUD through better understanding of the experiences of people who have used buprenorphine-naloxone.

Indexed as

BuprenorphineOpioid-Related DisordersSubstance Withdrawal SyndromeBuprenorphine, Naloxone Drug CombinationHumansNarcotic AntagonistsNatural Language ProcessingBuprenorphineBuprenorphine, Naloxone Drug CombinationNarcotic Antagonists

Identifiers

PMID34864788
PMCPMC9365256
OpenAlexW4200143698

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.