Diffusion of an Evidence-Based Smoking Cessation Intervention Through Facebook: A Randomized Controlled Trial
Nathan K Cobb1, Megan A Jacobs1, Paul Wileyto1
1Nathan K. Cobb is with the Department of Pulmonary and Critical Care, Georgetown University Medical Center, Washington, DC, and the Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Megan A. Jacobs is with the Schroeder Institute for Tobacco Research and Policy Studies, Truth Initiative, Washington, DC. Paul Wileyto is with the Department of Biostatistics & Epidemiology, University of Pennsylvania School of Medicine, Philadelphia. Thomas Valente is with the Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles. Amanda L. Graham is with the Schroeder Institute for Tobacco Research and Policy Studies, Truth Initiative, Washington, DC, and the Department of Oncology, Georgetown University Medical Center/Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Washington, DC.
This study found that combining active contagion and longer app use significantly increased smoking cessation app diffusion through social networks. These findings show online interventions can be designed for effective social spread.
Area of Science:
- Digital Health
- Public Health Interventions
- Social Network Analysis
Background:
- Smoking cessation remains a major public health challenge.
- Social networks offer a potential channel for disseminating health interventions.
- Evidence-based mobile applications can support smoking cessation efforts.
Purpose of the Study:
- To investigate the diffusion of a smoking cessation app within Facebook social networks.
- To identify specific intervention components that enhance the spread of the app.
Main Methods:
- Adult smokers were recruited via Facebook and randomized into 12 app variants.
- App variants were designed to test diffusion components: duration of use, contagiousness, and network size.
- The primary outcome measured was the reproductive ratio (R), indicating app spread per user.
Main Results:
- A total of 9042 smokers were randomized.
- The highest diffusion (R=0.087) was achieved by combining active contagion strategies with increased app duration.
- Involving non-smokers did not significantly impact app diffusion.
Conclusions:
- The observed diffusion rate, while modest, is sufficient for large-scale impact on smoking cessation.
- Online health interventions can be strategically designed for effective propagation through social networks.
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