Evidence map›Paper›PMID 24067329›Full record

ArticleJMIR research protocols2013

Share2Quit: Web-Based Peer-Driven Referrals for Smoking Cessation.

Rajani S Sadasivam, Erik M Volz, Rebecca L Kinney, Sowmya R Rao, Thomas K Houston

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2013. 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
2.2field-weighted citation impact, top 13% 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, 19 citations in OpenAlex.

  1. Article
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  6. Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2017
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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

5 authors at 2 institutions in 1 country.

Rajani S SadasivamDivision of Health Informatics & Implementation Science, Quantitative Health Sciences, The University of Massachusetts Medical School, Worcester, MA, United States. rajani.sadasivam@umassmed.edu.
Erik M Volz
Rebecca L Kinney
Sowmya R Rao
Thomas K Houston
Edith Nourse Rogers Memorial Veterans Hospital · USUniversity of Massachusetts Chan Medical School · US

Funding

University of Massachusetts Center for Clinical and Translational ScienceUL1TR000161 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2012 to 2015
$11.0M
Developing Smokers for Smoker (S4S): A Collective Intelligence tailoring systemK07CA172677 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SADASIVAM, RAJANI · 2013 to 2017
$702k
Share2Quit: Web-based Peer-driven Referrals for Smoking CessationR21CA158968 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SADASIVAM, RAJANI · 2012 to 2013
$381k
Medical Research Council MR/K010174/1NCATS NIH HHS UL1 TR000161NCI NIH HHS K07 CA172677NCI NIH HHS R21 CA158968
6 · The paper itself

Abstract

backgroundSmoking is the number one preventable cause of death in the United States. Effective Web-assisted tobacco interventions are often underutilized and require new and innovative engagement approaches. Web-based peer-driven chain referrals successfully used outside health care have the potential for increasing the reach of Internet interventions.

objectiveThe objective of our study was to describe the protocol for the development and testing of proactive Web-based chain-referral tools for increasing the access to Decide2Quit.org, a Web-assisted tobacco intervention system.

methodsWe will build and refine proactive chain-referral tools, including email and Facebook referrals. In addition, we will implement respondent-driven sampling (RDS), a controlled chain-referral sampling technique designed to remove inherent biases in chain referrals and obtain a representative sample. We will begin our chain referrals with an initial recruitment of former and current smokers as seeds (initial participants) who will be trained to refer current smokers from their social network using the developed tools. In turn, these newly referred smokers will also be provided the tools to refer other smokers from their social networks. We will model predictors of referral success using sample weights from the RDS to estimate the success of the system in the targeted population.

resultsThis protocol describes the evaluation of proactive Web-based chain-referral tools, which can be used in tobacco interventions to increase the access to hard-to-reach populations, for promoting smoking cessation.

conclusionsShare2Quit represents an innovative advancement by capitalizing on naturally occurring technology trends to recruit smokers to Web-assisted tobacco interventions.

Indexed as

peer-driven chain referralsrecruitmentrespondent-driven samplingWeb-assisted tobacco interventions

Identifiers

PMID24067329
PMCPMC3786127
OpenAlexW1976776154

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.