Get with the program: Adherence to a smartphone app for smoking cessation.

Publication Type:

Journal Article


Addictive behaviors, Volume 63, p.120-124 (2016)


INTRODUCTION: Although engagement is generally predictive of positive outcomes in technology-based behavioral change interventions, engagement measures remain largely atheoretical and lack treatment-specificity. This study examines the extent to which adherence measures based on the underlying behavioral change theory of an Acceptance and Commitment Therapy (ACT) app for smoking cessation predict smoking outcomes, and user characteristics associated with adherence.

METHODS: Study sample was adult daily smokers in a single arm pilot study (n=84). Using the app's log file data, we examined measures of adherence to four key components of the ACT behavior change model as predictors of smoking cessation and reduction. We also examined baseline user characteristics associated with adherence measures that predict smoking cessation.

RESULTS: Fully adherent users (24%) were over four times more likely to quit smoking (OR=4.45; 95% CI=1.13, 17.45; p=0.032). Both an increase in tracking the number of urges passed (OR=1.02; 95% CI=1.00, 1.03; p=0.043) and ACT modules completed (OR=1.27; 95% CI=1.01, 1.60; p=0.042) predicted cessation. Lower baseline acceptance of cravings was associated with over four times higher odds of full adherence (OR=4.59; 95% CI=1.35, 15.54; p=0.014).

CONCLUSIONS: Full adherence and use of specific ACT theory-based components of the app predicted quitting. Consistent with ACT theory, users with low acceptance were most likely to adhere to the app. Further research is needed on ways to promote app engagement.