Web-based peer-driven chain referrals for smoking cessation
Department of Quantitative Health Sciences
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.
Studies in health technology and informatics
Sadasivam RS, Cutrona SL, Volz E, Rao SR, Houston TK. (2013). Web-based peer-driven chain referrals for smoking cessation. UMass Center for Clinical and Translational Science Supported Publications. https://doi.org/10.3233/978-1-61499-289-9-357. Retrieved from https://escholarship.umassmed.edu/umccts_pubs/197