Evidence map›Paper›PMID 30544163›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

Electronic cigarette usage patterns: a case study combining survey and social media data.

Yongcheng Zhan, Jean-François Etter, Scott Leischow, Daniel Zeng

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

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  7. Doing what matters most.Journal of the American Medical Informatics Association : JAMIA · 2019
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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

4 authors at 3 institutions in 2 countries.

Yongcheng ZhanDepartment of Management Information Systems, University of Arizona, Tucson, Arizona, USA.
Jean-François EtterInstitute of Global Health, Faculty of Medicine, University of Geneva, Switzerland.
Scott LeischowCollege of Health Solutions, Arizona State University, Phoenix, Arizona, USA.
Daniel ZengDepartment of Management Information Systems, University of Arizona, Tucson, Arizona, USA.
University of Arizona · USArizona State University · USUniversity of Geneva · CH

Funding

Understanding E-Cigarette Adoption and Marketing: A Social Media StudyR01DA037378 · NIDA · UNIVERSITY OF ARIZONA · PI LEISCHOW, SCOTT J, ZHANG, BIN · 2014 to 2018
$2.7M
NIDA NIH HHS R01 DA037378
6 · The paper itself

Abstract

Objective: To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions. Materials and Methods: We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. We analyzed online forum participation patterns using survey data. We compared e-cigarette use patterns, including brand and flavor types, ratings, and purchase approaches, between the 2 datasets. We used logistic regression to study intentions to use e-cigarettes using both datasets. Results: Male and younger e-cigarette users were the most likely to participate in e-cigarette-related discussion forums. Forum active survey participants were hardcore vapers. The e-cigarette use patterns were similar in the online survey data and the social media data. Intention to use e-cigarettes was positively related to e-liquid ratings and flavor ratings. Social media provided a valuable source of information on users' ratings of e-cigarette refill liquids. Discussion: For hardcore vapers, social media data were consistent with online survey data, which suggests that social media may be useful to study e-cigarette use behaviors and can serve as a useful complement to online survey research. We proposed an innovative framework for social media data triangulation in public health studies. Conclusion: We illustrated how social media data, combined with online survey data, can serve as a new and rich information source for public health research.

Indexed as

Social MediaSurveys and QuestionnairesAdolescentAdultConsumer BehaviorDatasets as TopicElectronic Nicotine Delivery SystemsFemaleHumansInternetLogistic ModelsMaleMiddle AgedPublic Health SurveillanceYoung Adult

Identifiers

PMID30544163
PMCPMC6308011
OpenAlexW2904840097

What OpenQuestion holds

Textmetadata
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.