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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Web-based peer-driven chain referrals for smoking cessation.

Rajani S Sadasivam1, Sarah L Cutrona, Erik Volz

  • 1VA eHealth Quality Enhancement Research Initiative, Bedford VAMC, Bedford, Massachusetts, USA.

Studies in Health Technology and Informatics
|August 8, 2013
PubMed
Summary
This summary is machine-generated.

Web-based respondent-driven sampling (RDS) effectively recruits smokers for tobacco interventions. Simulations show RDS can achieve large sample sizes quickly, demonstrating its feasibility for public health research.

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Area of Science:

  • Public Health
  • Behavioral Science
  • Digital Health

Background:

  • Testing web-based respondent-driven sampling (RDS) chain referrals for recruiting smokers.
  • Focus on the Decide2Quit.org (D2Q) web-assisted tobacco intervention.

Purpose of the Study:

  • Assess the potential of recruiting 1200 smokers in 9 months using RDS chain referrals.
  • Determine the optimal design for RDS chains through simulations.

Main Methods:

  • Online survey of smokers to evaluate recruitment potential.
  • Conducted simulations to model RDS chain success factors.
  • Assessed network size and willingness to participate/refer.

Main Results:

  • Simulations indicate 99.9% sample achievement in 107 days with a quota of 3 and 10 seeds, assuming 0.5 acceptance probability.
  • Smokers surveyed showed high willingness (82%) to refer peers.
  • Network size estimations varied, with a mean of 2.2 intimate family and 3.7 close friend smokers.

Conclusions:

  • Web-based respondent-driven sampling (RDS) is a viable method for recruiting smokers.
  • RDS chain referral strategies show promise for tobacco intervention recruitment.