Evidence map›Paper›PMID 33347422›Full record

Observational studyJMIR public health and surveillance2021

Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data.

Yankun Gao, Zidian Xie, Dongmei Li

Open access · goldAbstract readObservational Study
In one paragraph

Observational study 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 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.1field-weighted citation impact, top 7% of its field
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

15 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Exploring Social Media Discourse on Cigars: Insights from Twitter/X Data.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
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  6. Observational
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  13. Vaping and COVID-19: Insights for Public Health and Clinical Care from Twitter.International journal of environmental research and public health · 2021
    Article
  14. Article
  15. 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

3 authors at 1 institution in 1 country.

Yankun GaoDepartment of Clinical & Translational Research, University of Rochester Medical Center, Rochester, NY, United States.ORCID 0000-0002-0585-967X
Zidian XieDepartment of Clinical & Translational Research, University of Rochester Medical Center, Rochester, NY, United States.ORCID 0000-0002-5149-7710
Dongmei LiDepartment of Clinical & Translational Research, University of Rochester Medical Center, Rochester, NY, United States.ORCID 0000-0001-9140-2483
University of Rochester Medical Center · US

Funding

WNY Center for Research on Flavored Tobacco Products (CRoFT)U54CA228110 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI OSSIP, DEBORAH J · 2018 to 2022
$19.8M
NCI NIH HHS U54 CA228110
6 · The paper itself

Abstract

backgroundPrevious studies have shown that electronic cigarette (e-cigarette) users might be more vulnerable to COVID-19 infection and could develop more severe symptoms if they contract the disease owing to their impaired immune responses to viral infections. Social media platforms such as Twitter have been widely used by individuals worldwide to express their responses to the current COVID-19 pandemic.

objectiveIn this study, we aimed to examine the longitudinal changes in the attitudes of Twitter users who used e-cigarettes toward the COVID-19 pandemic, as well as compare differences in attitudes between e-cigarette users and nonusers based on Twitter data.

methodsThe study dataset containing COVID-19-related Twitter posts (tweets) posted between March 5 and April 3, 2020, was collected using a Twitter streaming application programming interface with COVID-19-related keywords. Twitter users were classified into two groups: Ecig group, including users who did not have commercial accounts but posted e-cigarette-related tweets between May 2019 and August 2019, and non-Ecig group, including users who did not post any e-cigarette-related tweets. Sentiment analysis was performed to compare sentiment scores towards the COVID-19 pandemic between both groups and determine whether the sentiment expressed was positive, negative, or neutral. Topic modeling was performed to compare the main topics discussed between the groups.

resultsThe US COVID-19 dataset consisted of 4,500,248 COVID-19-related tweets collected from 187,399 unique Twitter users in the Ecig group and 11,479,773 COVID-19-related tweets collected from 2,511,659 unique Twitter users in the non-Ecig group. Sentiment analysis showed that Ecig group users had more negative sentiment scores than non-Ecig group users. Results from topic modeling indicated that Ecig group users had more concerns about deaths due to COVID-19, whereas non-Ecig group users cared more about the government's responses to the COVID-19 pandemic.

conclusionsOur findings show that Twitter users who tweeted about e-cigarettes had more concerns about the COVID-19 pandemic. These findings can inform public health practitioners to use social media platforms such as Twitter for timely monitoring of public responses to the COVID-19 pandemic and educating and encouraging current e-cigarette users to quit vaping to minimize the risks associated with COVID-19.

Indexed as

PandemicsPerceptionCOVID-19Electronic Nicotine Delivery SystemsHumansSmokersSocial MediaconcernCOVID-19Electronic cigaretteinfodemiologyobservationalperspectivesentiment analysissocial mediatopic modelingTwittervulnerable

Identifiers

PMID33347422
PMCPMC7787690
OpenAlexW3112862621

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.