ArticleInternet interventions2021
Detecting risk level in individuals misusing fentanyl utilizing posts from an online community on Reddit.
Article in Internet interventions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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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.
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.
Who cites it
15 citing papers in PubMed, 37 citations in OpenAlex.
- "I Don't Know for Certain": A Content Analysis of Reddit Posters' Accounts of Drink Spiking.Violence against women · 2026Article
- Automated Risk Assessment of Opioid Use: Analysis Using Pre-Trained Transformers on Social Media Data.JMIR infodemiology · 2026Article
- Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis.JMIR infodemiology · 2025Article
- Monitoring the opioid epidemic via social media discussions.NPJ digital medicine · 2025Article
- Which social media platforms facilitate monitoring the opioid crisis?PLOS digital health · 2025Article
- Self-Reported Advantages and Disadvantages of Online Networking About Opioid Misuse Among Those Who Have or Are Currently Misusing Opioids.Substance use & misuse · 2025Article
- Large-scale longitudinal analysis of the progression of alcohol use among members of a social media platform: an observational study.The American journal of drug and alcohol abuse · 2024Article
- Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach.JMIR formative research · 2024Article
- Using #ActuallyAutistic on Twitter for Precision Diagnosis of Autism Spectrum Disorder: Machine Learning Study.JMIR formative research · 2024Article
- Investigating Substance Use via Reddit: Systematic Scoping Review.Journal of medical Internet research · 2023Article
- Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder.Journal of medical Internet research · 2023Article
- Using Social Media to Examine Themes Surrounding Fentanyl Misuse and Risk Indicators.Substance use & misuse · 2023Article
- Interpol Review of Drug Analysis 2019-2022.Forensic science international. Synergy · 2023Review
- Signals of increasing co-use of stimulants and opioids from online drug forum data.Harm reduction journal · 2022Article
- Examining Symptoms of Stimulant Misuse and Community Support Among Members of a Recovery-Oriented Online Community.Journal of psychoactive drugsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
introductionOpioid misuse is a public health crisis in the US, and misuse of synthetic opioids such as fentanyl have driven the most recent waves of opioid-related deaths. Because those who misuse fentanyl are often a hidden and high-risk group, innovative methods for identifying individuals at risk for fentanyl misuse are needed. Machine learning has been used in the past to investigate discussions surrounding substance use on Reddit, and this study leverages similar techniques to identify risky content from discussions of fentanyl on this platform.
methodsA codebook was developed by clinical domain experts with 12 categories indicative of fentanyl misuse risk, and this was used to manually label 391 Reddit posts and comments. Using this data, we built machine learning classification models to identify fentanyl risk.
resultsOur machine learning risk model was able to detect posts or comments labeled as risky by our clinical experts with 76% accuracy and 76% sensitivity. Furthermore, we provide a vocabulary of community-specific, colloquial words for fentanyl and its analogues. DISCUSSION: This study uses an interdisciplinary approach leveraging machine learning techniques and clinical domain expertise to automatically detect risky discourse, which may elicit and benefit from timely intervention. Moreover, our vocabulary of online terms for fentanyl and its analogues expands our understanding of online "street" nomenclature for opiates. Through an improved understanding of substance misuse risk factors, these findings allow for identification of risk concepts among those misusing fentanyl to inform outreach and intervention strategies tailored to this at-risk group.
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What OpenQuestion holds
Registered trials
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.