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NAQC Newsroom: Research

Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial

Friday, April 13, 2018  
Posted by: Natalia Gromov
Amanda L Graham, George D Papandonatos, Sarah Cha, Bahar Erar, Michael S Amato.
Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial.
Annals of Behavioral Medicine, Volume 52, Issue 4, 15 March 2018, Pages 331–341, https://doi.org/10.1093/abm/kax023
 
Partial adherence in Internet smoking cessation interventions presents treatment and evaluation challenges. Increasing adherence may improve outcomes. To present smoking outcomes from an Internet randomized trial of two strategies to encourage adherence to tobacco dependence treatment components: (i) a social network (SN) strategy to integrate smokers into an online community and (ii) free nicotine replacement therapy (NRT). In addition to intent-to-treat analyses, we used novel statistical methods to distinguish the impact of treatment assignment from treatment utilization. A total of 5,290 current smokers on a cessation website (WEB) were randomized to WEB, WEB + SN, WEB + NRT, or WEB + SN + NRT. The main outcome was 30-day point prevalence abstinence at 3 and 9 months post-randomization. Adherence measures included self-reported medication use (meds), and website metrics of skills training (sk) and community use (comm). Inverse Probability of Retention Weighting and Inverse Probability of Treatment Weighting jointly addressed dropout and treatment selection. Propensity weights were used to calculate Average Treatment effects on the Treated. Treatment assignment analyses showed no effects on abstinence for either adherence strategy. Abstinence rates were 25.7%-32.2% among participants that used all three treatment components (sk+comm +meds).Treatment utilization analyses revealed that among such participants, sk+comm+meds yielded large percentage point increases in 3-month abstinence rates over sk alone across arms: WEB = 20.6 (95% CI = 10.8, 30.4), WEB + SN = 19.2 (95% CI = 11.1, 27.3), WEB + NRT = 13.1 (95% CI = 4.1, 22.0), and WEB + SN + NRT = 20.0 (95% CI = 12.2, 27.7). Novel propensity weighting approaches can serve as a model for establishing efficacy of Internet interventions and yield important insights about mechanisms.


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