Crowdsourced peer- versus expert-written smoking-cessation messages
Heather L Coley1, Rajani S Sadasivam, Jessica H Williams
1Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
American Journal of Preventive Medicine
|October 22, 2013
Summary
Smoker-to-smoker (S2S) messages encouraged more return visits to a web-assisted tobacco intervention than expert messages. Peer-generated content enhanced engagement by focusing on real-life aspects of quitting smoking.
Area of Science:
- Digital Health
- Public Health
- Behavioral Science
Background:
- Web-assisted tobacco interventions offer scalable reach for smoking cessation.
- Crowdsourcing content from peers can increase the relevance of digital health interventions.
- Previous research highlights the potential of tailored digital interventions for smoking cessation.
Purpose of the Study:
- To determine if peer-generated messages can effectively encourage smokers to use a web-assisted tobacco intervention (Decide2Quit.org).
- To compare the impact of smoker-to-smoker (S2S) messages versus expert-written messages on user engagement.
- To identify themes within peer-generated messages that correlate with increased intervention use.
Main Methods:
- Phase 1: Smokers generated 2,886 messages in response to scenarios, which were then coded for themes.
- Phase 2: Newly registered smokers received either S2S or expert-written messages via email.
- Subsequent website visits were compared between groups using multivariable analysis.
Main Results:
- S2S messages were significantly more likely to generate a return visit to the intervention (OR=2.03).
- Message themes varied by user readiness to quit, with S2S messages focusing on quality of life and behavioral strategies.
- Stratified analyses revealed that "social" and "real-life" aspects in S2S messages drove increased engagement.
Conclusions:
- Smoker-to-smoker (S2S) peer messages successfully increased longitudinal engagement in a web-assisted tobacco intervention.
- S2S messages expanded beyond a purely biomedical model, incorporating relatable, real-world experiences to enhance intervention relevance.
- This study demonstrates the efficacy of crowdsourced peer content in digital health interventions for smoking cessation.
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