Evidence map›Paper›PMID 27613918›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2017

Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems.

Rajani S Sadasivam, Sarah L Cutrona, Tana M Luger, Erik Volz, Rebecca Kinney, Sowmya R Rao, Jeroan J Allison, Thomas K Houston

Open access · greenAbstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.8field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 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 3 institutions in 2 countries.

Rajani S SadasivamDepartment of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA.
Sarah L CutronaDepartment of Medicine, University of Massachusetts Medical School, Worcester, MA.
Tana M LugerDepartment of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA.
Erik VolzImperial College London, London, UK.
Rebecca KinneyDepartment of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA.
Sowmya R RaoDepartment of Surgery, Boston University, Boston, MA.
Jeroan J AllisonDepartment of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA.
Thomas K HoustonDepartment of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA.
University of Massachusetts Chan Medical School · USBoston University · USImperial College London · GB

Funding

Developing Smokers for Smoker (S4S): A Collective Intelligence tailoring systemK07CA172677 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SADASIVAM, RAJANI · 2013 to 2017
$702k
NCI NIH HHS K07 CA172677
6 · The paper itself

Abstract

introductionAlthough technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook).

methodsWe recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers.

resultsOverall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons).

conclusionsPeer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research. IMPLICATIONS: This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.

Indexed as

InternetSmoking CessationSocial MarketingSocial MediaAdultFemaleHumansMale

Identifiers

PMID27613918
PMCPMC5896501
OpenAlexW2492856149

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.