|Grant Number:||5R21CA158968-02 Interpret this number|
|Primary Investigator:||Sadasivam, Rajani|
|Organization:||Univ Of Massachusetts Med Sch Worcester|
|Project Title:||SHARE2QUIT: Web-Based Peer-Driven Referrals for Smoking Cessation|
DESCRIPTION (provided by applicant): While cessation efforts have achieved some success, the decline in smoking has slowed, especially among younger smokers. Easily disseminated interventions like Quitlines and smoking cessation websites can potentially reach much greater numbers of smokers. Unfortunately, these interventions are under-utilized. Peer-driven chain referrals are quickly becoming the method of choice for recruiting hard-to-reach persons and their social networks. However, use of web-based chain referrals to recruit patients to online health interventions has not been extensively studied. Thus, in Share2Quit we will test a suite of electronic chain referral approaches to increase access to smoking cessation self-management interventions online. Our overall goal is to increase access to smoking cessation resources. We will conduct our study using Decide2Quit.org (D2Q), an existing web-based intervention. D2Q is the core patient intervention of two current randomized trials that include over 240 dental and physician practices that have already recruited over 1,000 smokers. We have the following specific aims: 1) Formative Research: Conduct in-depth interviews with a purposive sample of 40 smokers to refine proactive chain referral tools. 2) Development and Testing: Using agile programming, think aloud interviews, and mini-pilot mimicking the actual intervention, develop and test the Share2Quit tools. 3) Intervention: Evaluate the chain referral process and the referral success of the Share2Quit tools. The intervention will start with an initial set of seeds and we estimate a sample of 800-1200 smokers. The best practices of respondent-driven-sampling (RDS), an advance chain referral technique, will be implemented, including innovative webRDS techniques. We will model predictors of referral success, using sample weights from RDS to estimate the success of the system in the targeted population. Our findings will contribute significantly to our understanding of the potential of online chain referrals to increase access to services, and the impact on outcomes.