Evidence map›Paper›PMID 33001829›Full record

ArticleJournal of medical Internet research2020

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study.

Kamila Janmohamed, Abdul-Nasah Soale, Laura Forastiere, Weiming Tang, Yongjie Sha, Jakob Demant, Edoardo Airoldi, Navin Kumar

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
45.9field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 30 citations in OpenAlex.

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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

8 authors at 4 institutions in 3 countries.

Kamila JanmohamedHuman Nature Lab, Department of Sociology, Yale University, New Haven, CT, United States.ORCID 0000-0003-4858-6701
Abdul-Nasah SoaleDepartment of Statistical Science, Fox School of Business, Temple University, Philadelphia, PA, United States.ORCID 0000-0003-2093-7645
Laura ForastiereHuman Nature Lab, Department of Sociology, Yale University, New Haven, CT, United States.ORCID 0000-0003-3721-9826
Weiming TangUNC Project-China, University of North Carolina at Chapel Hill, Guangzhou, China.ORCID 0000-0002-9026-707X
Yongjie ShaUNC Project-China, University of North Carolina at Chapel Hill, Guangzhou, China.ORCID 0000-0003-2946-7483
Jakob DemantUniversity of Copenhagen, Copenhagen, Denmark.ORCID 0000-0003-3333-224X
Edoardo AiroldiDepartment of Statistical Science, Fox School of Business, Temple University, Philadelphia, PA, United States.ORCID 0000-0002-3512-0542
Navin KumarHuman Nature Lab, Department of Sociology, Yale University, New Haven, CT, United States.ORCID 0000-0003-4502-069X
Yale University · USTemple University · USUniversity of North Carolina at Chapel Hill · USUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 outbreak was designated a global pandemic on March 11, 2020. The relationship between vaping and contracting COVID-19 is unclear, and information on the internet is conflicting. There is some scientific evidence that vaping cannabidiol (CBD), an active ingredient in cannabis that is obtained from the hemp plant, or other substances is associated with more severe manifestations of COVID-19. However, there is also inaccurate information that vaping can aid COVID-19 treatment, as well as expert opinion that CBD, possibly administered through vaping, can mitigate COVID-19 symptoms. Thus, it is necessary to study the spread of inaccurate information to better understand how to promote scientific knowledge and curb inaccurate information, which is critical to the health of vapers. Inaccurate information about vaping and COVID-19 may affect COVID-19 treatment outcomes.

objectiveUsing structural topic modeling, we aimed to map temporal trends in the web-based vaping narrative (a large data set comprising web-based vaping chatter from several sources) to indicate how the narrative changed from before to during the COVID-19 pandemic.

methodsWe obtained data using a textual query that scanned a data pool of approximately 200,000 different domains (4,027,172 documents and 361,100,284 words) such as public internet forums, blogs, and social media, from August 1, 2019, to April 21, 2020. We then used structural topic modeling to understand changes in word prevalence and semantic structures within topics around vaping before and after December 31, 2019, when COVID-19 was reported to the World Health Organization.

resultsBroadly, the web-based vaping narrative can be organized into the following groups or archetypes: harms from vaping; Vaping Regulation; Vaping as Harm Reduction or Treatment; and Vaping Lifestyle. Three archetypes were observed prior to the emergence of COVID-19; however, four archetypes were identified post-COVID-19 (Vaping as Harm Reduction or Treatment was the additional archetype). A topic related to CBD product preference emerged after COVID-19 was first reported, which may be related to the use of CBD by vapers as a COVID-19 treatment.

conclusionsOur main finding is the emergence of a vape-administered CBD treatment narrative around COVID-19 when comparing the web-based vaping narratives before and during the COVID-19 pandemic. These results are key to understanding how vapers respond to inaccurate information about COVID-19, optimizing treatment of vapers who contract COVID-19, and possibly minimizing instances of inaccurate information. The findings have implications for the management of COVID-19 among vapers and the monitoring of web-based content pertinent to tobacco to develop targeted interventions to manage COVID-19 among vapers.

Indexed as

CannabidiolCoronavirus InfectionsCOVID-19COVID-19 Drug TreatmentHumansInternetPandemicsPneumonia, ViralSmokersSocial MediaTobacco ProductsVapingCannabidiolCOVID-19internetmodelingnarrativesocial mediatopic modelingtrendvapingweb-based health informationweb-based narrative

Identifiers

PMID33001829
PMCPMC7641646
OpenAlexW3091191787

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.