ArticleJMIR public health and surveillance2021
How Health Care Workers Wield Influence Through Twitter Hashtags: Retrospective Cross-sectional Study of the Gun Violence and COVID-19 Public Health Crises.
Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Smokers' Likelihood to Engage With Information and Misinformation on Twitter About the Relative Harms of e-Cigarette Use: Results From a Randomized Controlled Trial.JMIR public health and surveillance · 2021Trial
- Global English-language-dominated discourse on artificial intelligence in healthcare: a three-year longitudinal analysis of the #AIinHealthcare movement on X.Frontiers in digital health · 2026Article
- Firearm Violence and Health in Policymaker Discourse: Mixed Methods Social Media Analysis.JMIR formative research · 2025Article
- How advocacy groups on Twitter and media coverage can drive US firearm acquisition: A causal study.PNAS nexus · 2025Article
- Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data.Journal of medical Internet research · 2024Article
- Surveillance of Gun-Related Conversations on Twitter.Prevention science : the official journal of the Society for Prevention Research · 2024Article
- Piecing together the narrative of #longcovid: an unsupervised deep learning of 1,354,889 X (formerly Twitter) posts from 2020 to 2023.Frontiers in public health · 2024Article
- Article
- A Scoping Review of Physician Advocacy on Twitter.Cureus · 2023Article
- Development and Assessment of a Social Media-Based Construct of Firearm Ownership: Computational Derivation and Benchmark Comparison.Journal of medical Internet research · 2023Article
- From Heroes to Scoundrels: Exploring the effects of online campaigns celebrating frontline workers on COVID-19 outcomes.Technology in society · 2023Article
- How Americans encounter guns: Mixed methods content analysis of YouTube and internet search data.Preventive medicine · 2022Article
- Sex and Location Differences in Verification Status of Physician-Held Social Media Platform Accounts.JAMA network open · 2022Article
- Global and Local Trends Affecting the Experience of US and UK Healthcare Professionals during COVID-19: Twitter Text Analysis.International journal of environmental research and public health · 2022Article
- How to Harness the Power of Social Media for Quality Drug Information in Infectious Diseases: Perspectives on Behalf of the Society of Infectious Diseases Pharmacists.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022Article
- Exploring Web-Based Twitter Conversations Surrounding National Healthcare Decisions Day and Advance Care Planning From a Sociocultural Perspective: Computational Mixed Methods Analysis.JMIR formative research · 2022Article
- Public communication about public health where we really need to go.NPJ digital medicine · 2022Article
- Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research.JMIR public health and surveillance · 2022Article
- The State of Mind of Health Care Professionals in Light of the COVID-19 Pandemic: Text Analysis Study of Twitter Discourses.Journal of medical Internet research · 2021Article
- Partisan Differences in Twitter Language Among US Legislators During the COVID-19 Pandemic: Cross-sectional Study.Journal of medical Internet research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundTwitter has emerged as a novel way for physicians to share ideas and advocate for policy change. #ThisIsOurLane (firearm injury) and #GetUsPPE (COVID-19) are examples of nationwide health care-led Twitter campaigns that went viral. Health care-initiated Twitter hashtags regarding major public health topics have gained national attention, but their content has not been systematically examined.
objectiveWe hypothesized that Twitter discourse on two epidemics (firearm injury and COVID-19) would differ between tweets with health care-initiated hashtags (#ThisIsOurLane and #GetUsPPE) versus those with non-health care-initiated hashtags (#GunViolence and #COVID19).
methodsUsing natural language processing, we compared content, affect, and authorship of a random 1% of tweets using #ThisIsOurLane (Nov 2018-Oct 2019) and #GetUsPPE (March-May 2020), compared to #GunViolence and #COVID19 tweets, respectively. We extracted the relative frequency of single words and phrases and created two sets of features: (1) an open-vocabulary feature set to create 50 data-driven-determined word clusters to evaluate the content of tweets; and (2) a closed-vocabulary feature for psycholinguistic categorization among case and comparator tweets. In accordance with conventional linguistic analysis, we used a P<.001, after adjusting for multiple comparisons using the Bonferroni correction, to identify potentially meaningful correlations between language features and outcomes.
resultsIn total, 67% (n=4828) of #ThisIsOurLane tweets and 36.6% (n=7907) of #GetUsPPE tweets were authored by health care professionals, compared to 16% (n=1152) of #GunViolence and 9.8% (n=2117) of #COVID19 tweets. Tweets using #ThisIsOurLane and #GetUsPPE were more likely to contain health care-specific language; more language denoting positive emotions, affiliation, and group identity; and more action-oriented content compared to tweets with #GunViolence or #COVID19, respectively.
conclusionsTweets with health care-led hashtags expressed more positivity and more action-oriented language than the comparison hashtags. As social media is increasingly used for news discourse, public education, and grassroots organizing, the public health community can take advantage of social media's broad reach to amplify truthful, actionable messages around public health issues.
Indexed as
Identifiers
What OpenQuestion holds
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.