Abstract
BackgroundSmoking continues to be the leading preventable cause of death. Digital Interventions for Smoking Cessation (DISCs) are health communication programs accessible via the internet and smartphones and allow for greater reach and effectiveness of tobacco cessation programs. DISCs have led to increased 6-month cessation rates while also reaching vulnerable populations. Despite this, the impact of DISCs has been limited and new ways to increase access and effectiveness are needed.ObjectiveWe are conducting a hybrid effectiveness-dissemination study. We aim to evaluate the effectiveness of a machine learning–based approach (recommender system) for computer-tailored health communication (CTHC) over a standard CTHC system based on quit rates and risk reduction. In addition, this study will assess the dissemination of providing access to a peer recruitment toolset on recruitment rate and variability of the sample.MethodsThe Smoker-to-Smoker (S2S) study is a 6-month hybrid effectiveness dissemination trial conducted nationally among English-speaking, current smokers aged ≥18 years. All eligible participants will register for the DISC (Decide2quit) and be randomized to the recommender system CTHC or the standard CTHC, followed by allocation to a peer recruitment toolset group or control group. Primary outcomes will be 7-day point prevalence and risk reduction at the 6-month follow-up. Secondary outcomes include recruitment rate, website engagement, and patient-reported outcomes collected via the 6-month follow-up questionnaire. All primary analyses will be conducted on an intent-to-treat basis.ResultsThe project is funded from 2017 to 2020 by the Patient Centered Outcomes Research Institute. Enrollment was completed in early 2019, and 6-month follow-ups will be completed by late 2019. Preliminary data analysis is currently underway.ConclusionsConducting a hybrid study with both effectiveness and dissemination hypotheses raises some unique challenges in the study design and analysis. Our study addresses these challenges to test new innovations and increase the effectiveness and reach of DISCs.International Registered Report Identifier (IRRID)DERR1-10.2196/14814
Highlights
Smoking continues to be a public health concern and is the leading cause of preventable death in the United States [1]
All eligible participants will register for the Digital Interventions for Smoking Cessation (DISCs) (Decide2quit) and be randomized to the recommender system computer-tailored health communication (CTHC) or the standard CTHC, followed by allocation to a peer recruitment toolset group or control group
Conducting a hybrid study with both effectiveness and dissemination hypotheses raises some unique challenges in the study design and analysis
Summary
We are conducting a hybrid effectiveness-dissemination study. We aim to evaluate the effectiveness of a machine learning–based approach (recommender system) for computer-tailored health communication (CTHC) over a standard CTHC system based on quit rates and risk reduction. This study will assess the dissemination of providing access to a peer recruitment toolset on recruitment rate and variability of the sample
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