ArticlePloS one2014
Signs & symptoms of Dextromethorphan exposure from YouTube.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed.
- Curation and Extraction of Drug-Related Entities from Reddit Platform.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- High doses of dextromethorphan induced shock and convulsions in a 19-year-old female: A case report.World journal of clinical cases · 2023Article
- Article
- Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review.BMC medical informatics and decision making · 2018Article
- Candyflipping and Other Combinations: Identifying Drug-Drug Combinations from an Online Forum.Frontiers in psychiatry · 2018Article
- Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media.Journal of medical toxicology : official journal of the American College of Medical Toxicology · 2017Article
- Web-based textual analysis of free-text patient experience comments from a survey in primary care.JMIR medical informatics · 2015Article
- Nursing identity and patient-centredness in scholarly health services research: a computational text analysis of PubMed abstracts 1986-2013.BMC health services research · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Detailed data on the recreational use of drugs are difficult to obtain through traditional means, especially for substances like Dextromethorphan (DXM) which are available over-the-counter for medicinal purposes. In this study, we show that information provided by commenters on YouTube is useful for uncovering the toxicologic effects of DXM. Using methods of computational linguistics, we were able to recreate many of the clinically described signs and symptoms of DXM ingestion at various doses, using information extracted from YouTube comments. Our study shows how social networks can enhance our understanding of recreational drug effects.
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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.