Web-based peer-driven chain referrals for smoking cessation

UMMS Affiliation

Department of Quantitative Health Sciences

Publication Date


Document Type



Behavior and Behavior Mechanisms | Health Information Technology | Health Services Administration | Health Services Research | Therapeutics | Translational Medical Research


BACKGROUND: We are testing web-based respondent-driven sampling (RDS) chain referrals to recruit smokers to the Decide2Quit.org (D2Q) web-assisted tobacco intervention.

METHODS: Using an online survey of smokers, we assessed the potential of recruiting 1200 smokers in 9 months using RDS chain referrals. RDS is a complex sample design, and many factors can influence its success. We conducted simulations to determine the design of optimal RDS chains.

RESULTS: Smokers (n=48) were mostly female (72%) and between ages 30-60 (82%). Estimation of smokers in their network: 1-5 (40%), 6-10 (24%), and 10-20 (22%), with mean number of intimate family (2.2, SD=2.1) and close friend smokers (3.7, SD=3.8). Most smokers (82%) were willing to refer to D2Q and thought their friends (mean=5.0, SD=4.4, range=0-20) would be open to referral. Simulations suggested that with a quota of 3 and 10 seeds, 99.9% of the sample would be achieved in 107 days if the acceptance probability was 0.5. Acceptance probability of 25% would necessitate an increased quota.

CONCLUSIONS: Our study suggests that it is possible to recruit smokers using RDS.


Internet interventions, web-assisted tobacco interventions, Internet recruitment, peer-driven chain referral, respondent-driven sampling, UMCCTS funding

DOI of Published Version



Stud Health Technol Inform. 2013;192:357-61.

Journal/Book/Conference Title

Studies in health technology and informatics

Related Resources

Link to Article in PubMed

PubMed ID