Evidence map›Paper›PMID 34042824›Full record

ArticleStudies in health technology and informatics2021

Transitions Between Electronic and Combustible Cigarettes: A Mixed Methods Analysis of Peer Interactions in an Online Community for Tobacco Cessation.

Tavleen Singh, Nathan Cobb, Trevor Cohen, Sahiti Myneni

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tavleen SinghUniversity of Texas Health Science Center School of Biomedical Informatics, Houston, TX, USA.
Nathan CobbGeorgetown University Medical Center, Washington, DC, USA.
Trevor CohenBiomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
Sahiti MyneniUniversity of Texas Health Science Center School of Biomedical Informatics, Houston, TX, USA.

Funding

Pragmatics to Reveal Intention in Social Media (PRISM) for Health PromotionR01LM012974 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MYNENI, SAHITI · 2019 to 2022
$1.5M
NLM NIH HHS R01 LM012974
6 · The paper itself

Abstract

The growing popularity of e-cigarettes is a public health concern. There is an emerging need to understand the pathways between electronic and combustible modes due to the specialized nature of risks associated with each transition. Online social media has become the most dominant knowledge space for these evolving behaviors, and as such, can provide unique opportunities for modeling switching patterns. In this paper, we describe the utility of online peer interactions using qualitative inquiry and network visualizations using 500 messages to characterize (a) transition pathways and (b) psychosocial attributes as individuals contemplate and act on such transitions. Our results indicate that the E2A pathway is the most prevalent in e-cigarette-related transitions, where most of the individuals are in the "active e-cig use" stage. Perceived benefits and barriers are the most commonly held health beliefs, while counterconditioning and stimulus control behavior change processes are frequently manifested. Such insights can help in the design of personalized pathway-specific behavior change interventions.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsTobacco Use CessationElectronicsHumansPeer Groupbehavior changee-cigaretteshealth beliefssocial media

Identifiers

PMID34042824
PMCPMC9134573

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.