Predictors of Utilization of a Novel Smoking Cessation Smartphone App.

Journal Article (Journal Article)

BACKGROUND: Understanding the characteristics of high and low utilizers of smartphone applications (apps) for smoking cessation would inform development of more engaging and effective apps, yet no studies to date have addressed this critical question. Informed by prior research on predictors of cessation Web site utilization, this study examines the degree to which baseline demographic factors (gender, age, and education), smoking-related factors (smoking level and friends' smoking), and psychological factors (depression and anxiety) are predictive of utilization of a smartphone app for smoking cessation called SmartQuit. MATERIALS AND METHODS: Data came from 98 participants randomized to SmartQuit as part of a pilot trial from March to May 2013. We used negative binomial count regressions to examine the relationship between user characteristics and utilization of the app over an 8-week treatment period. RESULTS: Lower education (risk ratio [RR]=0.492; p=0.021), heavier smoking (RR=0.613; p=0.033), and depression (RR=0.958; p=0.017) prospectively predicted lower app utilization. Women (RR=0.320; p=0.022), those with lower education (RR=0.491; p=0.013), and heavier smokers (RR=0.418; p=0.039) had lower utilization of app features known to predict smoking cessation. CONCLUSIONS: Many of the predictors of utilization of smoking cessation apps are the same as those of cessation Web sites. App-delivered smoking cessation treatment effectiveness could be enhanced by focusing on increasing engagement of women, those with lower education, heavy smokers, and those with current depressive symptoms.

Full Text

Duke Authors

Cited Authors

  • Zeng, EY; Vilardaga, R; Heffner, JL; Mull, KE; Bricker, JB

Published Date

  • December 2015

Published In

Volume / Issue

  • 21 / 12

Start / End Page

  • 998 - 1004

PubMed ID

  • 26171733

Pubmed Central ID

  • PMC4776539

Electronic International Standard Serial Number (EISSN)

  • 1556-3669

Digital Object Identifier (DOI)

  • 10.1089/tmj.2014.0232


  • eng

Conference Location

  • United States