Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data.

Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE

Publication: <2011- > : Toronto : JMIR Publications
Original Publication: [Pittsburgh, PA? : s.n., 1999-

Internet/*statistics & numerical data ; Pharmaceutical Services, Online/*statistics & numerical data ; Prescription Drug Misuse/*adverse effects ; Prescription Drugs/*adverse effects ; Social Media/*statistics & numerical data; Adolescent ; Humans

Background: Youth and adolescent non-medical use of prescription medications (NUPM) has become a national epidemic. However, little is known about the association between promotion of NUPM behavior and access via the popular social media microblogging site, Twitter, which is currently used by a third of all teens.
Objective: In order to better assess NUPM behavior online, this study conducts surveillance and analysis of Twitter data to characterize the frequency of NUPM-related tweets and also identifies illegal access to drugs of abuse via online pharmacies.
Methods: Tweets were collected over a 2-week period from April 1-14, 2015, by applying NUPM keyword filters for both generic/chemical and street names associated with drugs of abuse using the Twitter public streaming application programming interface. Tweets were then analyzed for relevance to NUPM and whether they promoted illegal online access to prescription drugs using a protocol of content coding and supervised machine learning.
Results: A total of 2,417,662 tweets were collected and analyzed for this study. Tweets filtered for generic drugs names comprised 232,108 tweets, including 22,174 unique associated uniform resource locators (URLs), and 2,185,554 tweets (376,304 unique URLs) filtered for street names. Applying an iterative process of manual content coding and supervised machine learning, 81.72% of the generic and 12.28% of the street NUPM datasets were predicted as having content relevant to NUPM respectively. By examining hyperlinks associated with NUPM relevant content for the generic Twitter dataset, we discovered that 75.72% of the tweets with URLs included a hyperlink to an online marketing affiliate that directly linked to an illicit online pharmacy advertising the sale of Valium without a prescription.
Conclusions: This study examined the association between Twitter content, NUPM behavior promotion, and online access to drugs using a broad set of prescription drug keywords. Initial results are concerning, as our study found over 45,000 tweets that directly promoted NUPM by providing a URL that actively marketed the illegal online sale of prescription drugs of abuse. Additional research is needed to further establish the link between Twitter content and NUPM, as well as to help inform future technology-based tools, online health promotion activities, and public policy to combat NUPM online.

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Keywords: cyberpharmacies; eHealth; illicit Internet pharmacies; infodemiology; infoveillance; prescription drug abuse; social media; surveillance; twitter

0 (Prescription Drugs)

Date Created: 20151219 Date Completed: 20160825 Latest Revision: 20190109

20250114

PMC4704982

10.2196/jmir.5144

26677966