Caroline O Cobb1, Amanda L Graham2. 1. Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington, DC; 2. Schroeder Institute for Tobacco Research and Policy Studies, Legacy, Washington, DC; Department of Oncology, Georgetown University Medical Center/Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Washington, DC agraham@legacyforhealth.org.
Abstract
INTRODUCTION: A recent meta-analysis of Internet interventions for smoking cessation found mixed evidence regarding effectiveness. One explanation may be differential use of non-assigned cessation treatments-including other Internet programs-that either amplify or mask study intervention effects. We examined the impact of non-assigned treatment use on cessation outcomes in The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation. METHODS: Participants were randomized to a basic Internet (BI) comparison condition (N = 675), enhanced Internet (EI: N = 651), or EI plus telephone counseling (EI+P: N = 679). The primary outcome was 30-day point prevalence abstinence (ppa) at 3 and 6 months. Assigned intervention use was assessed with automated tracking data. Assessment of non-assigned treatments included pharmacotherapy, behavioral, alternative, and non-study Internet treatments. Univariate and multivariate logistic regression models examined whether non-assigned treatment use was associated with 30-day ppa. RESULTS: About 70% of participants used at least one non-assigned treatment. A higher rate of non-study Internet treatment among BI participants was the only treatment group difference at both 3 and 6 months. Multivariate models controlling for condition and baseline predictors of non-assigned treatment use showed that high-intensity non-study Internet treatment was positively associated with 30-day ppa at 3 and 6 months, and pharmacotherapy and behavioral treatment use was negatively associated with 30-day ppa at 6 months. CONCLUSIONS: Non-assigned treatment use is an important factor to consider when evaluating Internet cessation interventions. Results highlight methodological issues in selecting a comparison condition. Researchers should report non-assigned treatment use alongside main trial outcomes.
RCT Entities:
INTRODUCTION: A recent meta-analysis of Internet interventions for smoking cessation found mixed evidence regarding effectiveness. One explanation may be differential use of non-assigned cessation treatments-including other Internet programs-that either amplify or mask study intervention effects. We examined the impact of non-assigned treatment use on cessation outcomes in The iQUITT Study, a randomized trial of Internet and telephone treatment for smoking cessation. METHODS:Participants were randomized to a basic Internet (BI) comparison condition (N = 675), enhanced Internet (EI: N = 651), or EI plus telephone counseling (EI+P: N = 679). The primary outcome was 30-day point prevalence abstinence (ppa) at 3 and 6 months. Assigned intervention use was assessed with automated tracking data. Assessment of non-assigned treatments included pharmacotherapy, behavioral, alternative, and non-study Internet treatments. Univariate and multivariate logistic regression models examined whether non-assigned treatment use was associated with 30-day ppa. RESULTS: About 70% of participants used at least one non-assigned treatment. A higher rate of non-study Internet treatment among BI participants was the only treatment group difference at both 3 and 6 months. Multivariate models controlling for condition and baseline predictors of non-assigned treatment use showed that high-intensity non-study Internet treatment was positively associated with 30-day ppa at 3 and 6 months, and pharmacotherapy and behavioral treatment use was negatively associated with 30-day ppa at 6 months. CONCLUSIONS: Non-assigned treatment use is an important factor to consider when evaluating Internet cessation interventions. Results highlight methodological issues in selecting a comparison condition. Researchers should report non-assigned treatment use alongside main trial outcomes.
Authors: Amanda L Graham; Nathan K Cobb; George D Papandonatos; Jose L Moreno; Hakmook Kang; David G Tinkelman; Beth C Bock; Raymond S Niaura; David B Abrams Journal: Arch Intern Med Date: 2011-01-10
Authors: Jennifer B McClure; Susan M Shortreed; Andy Bogart; Holly Derry; Karin Riggs; Jackie St John; Vijay Nair; Larry An Journal: J Med Internet Res Date: 2013-03-25 Impact factor: 5.428
Authors: Jessie E Saul; Barbara A Schillo; Sharrilyn Evered; Michael G Luxenberg; Annette Kavanaugh; Nathan Cobb; Lawrence C An Journal: J Med Internet Res Date: 2007-09-30 Impact factor: 5.428
Authors: Jennifer L Pearson; Cassandra A Stanton; Sarah Cha; Raymond S Niaura; George Luta; Amanda L Graham Journal: Nicotine Tob Res Date: 2014-12-26 Impact factor: 4.244
Authors: John T Denny; Angela M Denny; James T Tse; Vincent J Deangelis; Darrick Chyu; Enrique J Pantin; Sloane S Yeh; Shaul Cohen; Christine H Fratzola; Alann Solina Journal: Exp Ther Med Date: 2016-07-01 Impact factor: 2.447
Authors: Brian G Danaher; Herbert H Severson; Shu-Hong Zhu; Judy A Andrews; Sharon E Cummins; Edward Lichtenstein; Gary J Tedeschi; Coleen Hudkins; Chris Widdop; Ryann Crowley; John R Seeley Journal: Internet Interv Date: 2015-05-01
Authors: Amanda L Graham; George D Papandonatos; Sarah Cha; Bahar Erar; Michael S Amato; Nathan K Cobb; Raymond S Niaura; David B Abrams Journal: Nicotine Tob Res Date: 2017-03-01 Impact factor: 4.244