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Diffusion of an Evidence-Based Smoking Cessation Intervention Through Facebook

A Randomized Controlled Trial

Bibliographic Data

ID11030259
AuthorsNathan K Cobb (Nathan 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...), Nathan Cobb (0000-0003-4210-226X, Johns Hopkins University), Megan A Jacobs (0000-0001-6526-964X, Nathan 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...), Paul Wileyto (Nathan 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...), T W Valente (0000-0002-8824-5816, Nathan 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...), Thomas Valente, Amanda L Graham (0000-0003-3036-9653, Nathan 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...)
Year2016
Volume106
Issue6
Pages1130-1135
Publication date2016-06-01
Open AccessNo
TypeARTICLE
VenueAmerican Journal of Public Health (JOURNAL)
Journal identifiersISSN: 0090-0036 • E-ISSN: 1541-0048
PublisherAmerican Public Health Association (PUBLISHER • US)
DOI10.2105/ajph.2016.303106
PMID27077358
OpenAlexW2339153508
LanguageEN
Citations received6
References cited18

Objectives. To examine the diffusion of an evidence-based smoking cessation application (“app”) through Facebook social networks and identify specific intervention components that accelerate diffusion. Methods. Between December 2012 and October 2013, we recruited adult US smokers (“seeds”) via Facebook advertising and randomized them to 1 of 12 app variants using a factorial design. App variants targeted components of diffusion: duration of use (t), “contagiousness” (β), and number of contacts (Z). The primary outcome was the reproductive ratio (R), defined as the number of individuals installing the app (“descendants”) divided by the number of a seed participant’s Facebook friends. Results. We randomized 9042 smokers. App utilization metrics demonstrated between-variant differences in expected directions. The highest level of diffusion (R = 0.087) occurred when we combined active contagion strategies with strategies to increase duration of use (incidence rate ratio = 9.99; 95% confidence interval = 5.58, 17.91; P Conclusions. The maximal R value (0.087) is sufficient to increase the numbers of individuals receiving treatment if applied on a large scale. Online interventions can be designed a priori to spread through social networks

Affect (linguistics) · Confidence interval · Intervention (counseling) · Psychiatry · Psychological intervention · Randomized controlled trial · Smoking cessation · Social media · World Wide Web · Computer Science · Demography · Internal Medicine · Medicine · Mobile Health and mHealth Applications · Psychology · Smoking Behavior and Cessation · Social Media in Health Education

  • The effectiveness of technology‐based interventions for smoking cessation

    Open Access•Amanual G Mersha, MICHELLE KENNEDY et al.•Drug and Alcohol Review•2021

  • Use of social network analysis in the development, dissemination, implementation, and sustainability of health behavior interventions for adults

    Open Access•Rachel C Shelton, Matthew Lee et al.•Social Science & Medicine•2019

  • A Public Health of Consequence

    Sandro Galea, Roger Vaughan•American Journal of Public Health•2016

  • Effectiveness of a brief social network intervention for depressive symptoms among Chinese adolescents under major chronic stress

    Open Access•Lin Fu, Yueyue Zhou et al.•Children and Youth Services Review•2024

  • The Efficacy of Smoking Cessation Interventions via Social Media

    Eddy Lopez•American Journal of Public Health•2017

  • Social Networks and Health

    Jingwen Zhang, Damon Centola•Annual Review of Sociology•2019

  • Social Networks and Health

    T W Valente•Social networks and health•2010

  • Network Interventions

    Open Access•T W Valente•Science•2012

  • Identifying Influential and Susceptible Members of Social Networks

    Open Access•Sinan Aral, D Walker•Science•2012

  • Exploring Network Structure, Dynamics, and Function using NetworkX

    Open Access•Aric A Hagberg, Aric Hagberg et al.•Proceedings of the Python in…•2008

  • The Collective Dynamics of Smoking in a Large Social Network

    Nicholas A Christakis, J H Fowler•New England Journal of Medicine•2008

  • A 61-million-person experiment in social influence and political mobilization

    Open Access•Robert M Bond, Christopher J Fari et al.•Nature•2012

  • Social Network Structure of a Large Online Community for Smoking Cessation

    Nathan K Cobb, Nathan Cobb et al.•American Journal of Public Health•2010

  • Influentials, Networks, and Public Opinion Formation

    Duncan J Watts, Peter Sheridan Dodds•Journal of Consumer Research•2007

Citations per year0.6
Citation span2016 - 2024 (9)
Highly citedNo

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