Evidence map›Paper›PMID 29305342›Full record

ArticleJMIR public health and surveillance2018

Social Media Impact of the Food and Drug Administration's Drug Safety Communication Messaging About Zolpidem: Mixed-Methods Analysis.

Michael S Sinha, Clark C Freifeld, John S Brownstein, Macarius M Donneyong, Paula Rausch, Brian M Lappin, Esther H Zhou, Gerald J Dal Pan, Ajinkya M Pawar, Thomas J Hwang and 2 more

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Pharmacovigilance in the digital age: gaining insight from social media data.Experimental biology and medicine (Maywood, N.J.) · 2025
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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

12 authors.

Michael S SinhaProgram On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID http://orcid.org/0000-0002-9165-8611
Clark C FreifeldCollege of Computer and Information Science, Northeastern University, Boston, MA, United States.ORCID http://orcid.org/0000-0002-6281-219X
John S BrownsteinComputational Epidemiology Group, Boston Children's Hospital, Boston, MA, United States.ORCID http://orcid.org/0000-0001-8568-5317
Macarius M DonneyongHealth Services Management and Policy, College of Public Health, The Ohio State University, Columbus, OH, United States.ORCID http://orcid.org/0000-0003-2710-913X
Paula RauschFood and Drug Administration, Silver Spring, MD, United States.ORCID http://orcid.org/0000-0002-3016-241X
Brian M LappinFood and Drug Administration, Silver Spring, MD, United States.ORCID http://orcid.org/0000-0002-5120-1940
Esther H ZhouFood and Drug Administration, Silver Spring, MD, United States.ORCID http://orcid.org/0000-0003-4608-6850
Gerald J Dal PanFood and Drug Administration, Silver Spring, MD, United States.ORCID http://orcid.org/0000-0003-4874-5864
Ajinkya M PawarProgram On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID http://orcid.org/0000-0002-8585-9505
Thomas J HwangProgram On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID http://orcid.org/0000-0003-0717-1497
Jerry AvornProgram On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID http://orcid.org/0000-0003-0255-2346
Aaron S KesselheimProgram On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States.ORCID http://orcid.org/0000-0002-8867-2666

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Food and Drug Administration (FDA) issues drug safety communications (DSCs) to health care professionals, patients, and the public when safety issues emerge related to FDA-approved drug products. These safety messages are disseminated through social media to ensure broad uptake.

objectiveThe objective of this study was to assess the social media dissemination of 2 DSCs released in 2013 for the sleep aid zolpidem.

methodsWe used the MedWatcher Social program and the DataSift historic query tool to aggregate Twitter and Facebook posts from October 1, 2012 through August 31, 2013, a period beginning approximately 3 months before the first DSC and ending 3 months after the second. Posts were categorized as (1) junk, (2) mention, and (3) adverse event (AE) based on a score between -0.2 (completely unrelated) to 1 (perfectly related). We also looked at Google Trends data and Wikipedia edits for the same time period. Google Trends search volume is scaled on a range of 0 to 100 and includes "Related queries" during the relevant time periods. An interrupted time series (ITS) analysis assessed the impact of DSCs on the counts of posts with specific mention of zolpidem-containing products. Chow tests for known structural breaks were conducted on data from Twitter, Facebook, and Google Trends. Finally, Wikipedia edits were pulled from the website's editorial history, which lists all revisions to a given page and the editor's identity.

resultsIn total, 174,286 Twitter posts and 59,641 Facebook posts met entry criteria. Of those, 16.63% (28,989/174,286) of Twitter posts and 25.91% (15,453/59,641) of Facebook posts were labeled as junk and excluded. AEs and mentions represented 9.21% (16,051/174,286) and 74.16% (129,246/174,286) of Twitter posts and 5.11% (3,050/59,641) and 68.98% (41,138/59,641) of Facebook posts, respectively. Total daily counts of posts about zolpidem-containing products increased on Twitter and Facebook on the day of the first DSC; Google searches increased on the week of the first DSC. ITS analyses demonstrated variability but pointed to an increase in interest around the first DSC. Chow tests were significant (P<.0001) for both DSCs on Facebook and Twitter, but only the first DSC on Google Trends. Wikipedia edits occurred soon after each DSC release, citing news articles rather than the DSC itself and presenting content that needed subsequent revisions for accuracy.

conclusionsSocial media offers challenges and opportunities for dissemination of the DSC messages. The FDA could consider strategies for more actively disseminating DSC safety information through social media platforms, particularly when announcements require updating. The FDA may also benefit from directly contributing content to websites like Wikipedia that are frequently accessed for drug-related information.

Indexed as

drug safety communicationsepidemiologyFacebookFood and Drug AdministrationGoogle Trendssocial mediasurveillanceTwitter

Identifiers

PMID29305342
PMCPMC5775485

What OpenQuestion holds

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LicenceCC BY
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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.