DESCRIPTION (provided by applicant): Large scale reduction in smoking prevalence is a public health imperative. Evidenced based interventions recommended by the PHS Clinical Practice Guideline for Treatment exist but are massively underutilized. Even brief interventions that can be cost efficiently disseminated do not reach the vast majority of 44 million current smokers - such as those based on the 5A model (Ask, Advise, Assess, Assist, Arrange) delivered over multiple modalities including the Internet. Studies and meta-analysis show evidence based online interventions are effective with a relative risk of abstinence of 1.44 and quit rates of 7-26%. Our previous work suggests that successful Internet cessation is mediated by the degree of a user's integration into the site's social network: integration almost triples (OR=2.71) the chances of quitting 3 months later, while active use of interactive tools more than doubled rates of cessation (21.9% vs. 8.3%) at 6 months. In theory, wide availability of these programs should provide for a marked impact on smoking rates (impact = reach x efficacy): the majority (74%) of US adults are Internet users, including Hispanics (64%), Blacks (70%), and those with incomes less than $30,000/year (60%) while reports show 6-9% of all Internet users (more than 10 million adults) search for quitting smoking annually. Despite this, our work and that of others, indicates that only a third of searchers reach evidence based interventions and of those less than a quarter of users take advantage the social support recommended by the 2008 Guideline. To meet the promise of online interventions and make a significant public health impact, a major paradigm shift in intervention development is needed - interventions must be actively distributed to smokers online. The proposed study is a randomized trial of the contributors to diffusion of an evidence-based software application for smoking cessation embedded within the Facebook social network. It aims to extend existing theory and practice by testing a novel diffusion strategy for an evidence-based intervention through a large-scale existing online social network. This study combines chain recruitment techniques ("viral spread") for dissemination with previously validated Internet cessation approaches. Intervention design and evaluation will use a multi-phase methodology, seeding multiple, hypothesis-driven variants of a smoking cessation application into Facebook, and powered to detect interaction effects between the components of different variants under a factorial model. The goal is to determine the intervention characteristics, and thus modifiable variables, that directly impact diffusion (the reproductive rate) and ultimately add to our knowledge base about constructing interventions capable of self-propagation and distribution. This study will add to our knowledge base and theory to help define a new paradigm for broad scale dissemination of behavioral interventions and public health impact. These findings will enable a near-term, future generation of effective health interventions to be disseminated to large populations in a low-cost, efficient manner.
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