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Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study.

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  • Additional Information
    • Source:
      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 Information:
      Publication: <2011- > : Toronto : JMIR Publications
      Original Publication: [Pittsburgh, PA? : s.n., 1999-
    • Subject Terms:
      COVID-19* ; Language* ; Public Opinion* ; Social Media* ; Telemedicine*; Humans ; Longitudinal Studies ; Pandemics ; SARS-CoV-2
    • Abstract:
      Background: The COVID-19 pandemic has necessitated a rapid shift in how individuals interact with and receive fundamental services, including health care. Although telemedicine is not a novel technology, previous studies have offered mixed opinions surrounding its utilization. However, there exists a dearth of research on how these opinions have evolved over the course of the current pandemic.
      Objective: This study aims to evaluate how the language and sentiment surrounding telemedicine has evolved throughout the COVID-19 pandemic.
      Methods: Tweets published between January 1, 2020, and April 24, 2021, containing at least one telemedicine-related and one COVID-19-related search term ("telemedicine-COVID") were collected from the Twitter full archive search (N=351,718). A comparator sample containing only COVID-19 terms ("general-COVID") was collected and sampled based on the daily distribution of telemedicine-COVID tweets. In addition to analyses of retweets and favorites, sentiment analysis was performed on both data sets in aggregate and within a subset of tweets receiving the top 100 most and least retweets.
      Results: Telemedicine gained prominence during the early stages of the pandemic (ie, March through May 2020) before leveling off and reaching a steady state from June 2020 onward. Telemedicine-COVID tweets had a 21% lower average number of retweets than general-COVID tweets (incidence rate ratio 0.79, 95% CI 0.63-0.99; P=.04), but there was no difference in favorites. A majority of telemedicine-COVID tweets (180,295/351,718, 51.3%) were characterized as "positive," compared to only 38.5% (135,434/351,401) of general-COVID tweets (P<.001). This trend was also true on a monthly level from March 2020 through April 2021. The most retweeted posts in both telemedicine-COVID and general-COVID data sets were authored by journalists and politicians. Whereas the majority of the most retweeted posts within the telemedicine-COVID data set were positive (55/101, 54.5%), a plurality of the most retweeted posts within the general-COVID data set were negative (44/89, 49.4%; P=.01).
      Conclusions: During the COVID-19 pandemic, opinions surrounding telemedicine evolved to become more positive, especially when compared to the larger pool of COVID-19-related tweets. Decision makers should capitalize on these shifting public opinions to invest in telemedicine infrastructure and ensure its accessibility and success in a postpandemic world.
      (©Catherine C Pollack, Diane Gilbert-Diamond, Jennifer A Alford-Teaster, Tracy Onega. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 21.06.2021.)
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    • Grant Information:
      P30 CA023108 United States CA NCI NIH HHS; T32 LM012204 United States LM NLM NIH HHS
    • Contributed Indexing:
      Keywords: COVID-19; COVID-19 pandemic; Twitter; pandemic; sentiment analysis; social media; telehealth; telemedicine
    • Publication Date:
      Date Created: 20210604 Date Completed: 20210630 Latest Revision: 20210704
    • Publication Date:
      20240513
    • Accession Number:
      PMC8218898
    • Accession Number:
      10.2196/28648
    • Accession Number:
      34086591