Evidence map›Paper›PMID 36066939›Full record

ArticleJournal of medical Internet research2022

Twitter Usage Among Physicians From 2016 to 2020: Algorithm Development and Longitudinal Analysis Study.

Keisuke Nakagawa, Nuen Tsang Yang, Machelle Wilson, Peter Yellowlees

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. American Society for Gastrointestinal Endoscopy best practice statements on the sharing of endoscopic images and videos on social media.VideoGIE : an official video journal of the American Society for Gastrointestinal Endoscopy · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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

4 authors.

Keisuke NakagawaDepartment of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, Sacramento, CA, United States.ORCID 0000-0001-7589-2849
Nuen Tsang YangDivision of Biostatistics, Department of Public Health Sciences, University of California, Davis, Sacramento, CA, United States.ORCID 0000-0002-3074-5930
Machelle WilsonDivision of Biostatistics, Department of Public Health Sciences, University of California, Davis, Sacramento, CA, United States.ORCID 0000-0003-1734-2755
Peter YellowleesDepartment of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, Sacramento, CA, United States.ORCID 0000-0002-5238-7468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysicians are increasingly using Twitter as a channel for communicating with colleagues and the public. Identifying physicians on Twitter is difficult due to the varied and imprecise ways that people self-identify themselves on the social media platform. This is the first study to describe a reliable, repeatable methodology for identifying physicians on Twitter. By using this approach, we characterized the longitudinal activity of US physicians on Twitter.

objectiveWe aimed to develop a reliable and repeatable methodology for identifying US physicians on Twitter and to characterize their activity on Twitter over 5 years by activity, tweeted topic, and account type.

methodsIn this study, 5 years of Twitter data (2016-2020) were mined for physician accounts. US physicians on Twitter were identified by using a custom-built algorithm to screen for physician identifiers in the Twitter handles, user profiles, and tweeted content. The number of tweets by physician accounts from the 5-year period were counted and analyzed. The top 100 hashtags were identified, categorized into topics, and analyzed.

resultsApproximately 1 trillion tweets were mined to identify 6,399,146 (<0.001%) tweets originating from 39,084 US physician accounts. Over the 5-year period, the number of US physicians tweeting more than doubled (ie, increased by 112%). Across all 5 years, the most popular themes were general health, medical education, and mental health, and in specific years, the number of tweets related to elections (2016 and 2020), Black Lives Matter (2020), and COVID-19 (2020) increased.

conclusionsTwitter has become an increasingly popular social media platform for US physicians over the past 5 years, and their use of Twitter has evolved to cover a broad range of topics, including science, politics, social activism, and COVID-19. We have developed an accurate, repeatable methodology for identifying US physicians on Twitter and have characterized their activity.

Indexed as

COVID-19PhysiciansSocial MediaAlgorithmsData CollectionHumanshealth informaticsinternetinternet usephysicianpublic healthsocial mediaTwitter

Identifiers

PMID36066939
PMCPMC9490540

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.