Efficacy of smartphone applications for smoking cessation in heavy-drinking adults: Secondary analysis of the iCanQuit randomized trial
Introduction
Cigarette smoking and heavy drinking are leading causes of preventable death and disease in the United States (US) (Collaborators, 2017, GBD Tobacco Collaborators 2017 GBD Risk Factor Collaborators 2018). People who smoke cigarettes are twice as likely to drink heavily compared to their non-smoking counterparts (Weinberger et al., 2019, Xu et al., 2007). In addition, the rate of current cigarette smoking is over two times higher among heavy-drinking adults compared to non-drinkers (49% vs. 19%) (Weinberger, Gbedemah, & Goodwin, 2017). Moreover, heavy drinkers are less likely to quit smoking than non-drinkers (52% vs. 65%) (Babb et al., 2017, U.S. Department of Health and Human Services, 2020). Smoking and heavy drinking have a synergetic detrimental health effect beyond use of either substance alone (e.g., greater cancer risk), making this population a high priority for smoking cessation interventions (Hagger-Johnson et al., 2013, Pelucchi et al., 2006).
Although quitting cigarette smoking is often difficult, quitting can be even more challenging for people who drink heavily and may experience alcohol-induced craving to smoke (Leventhal et al., 2019, McKee et al., 2007, Piper et al., 2019, Roberts et al., 2020, Thrul et al., 2021, West et al., 2020). Cue-induced cravings can be a driving mechanism for the negative effect of alcohol use on successfully quitting smoking in this group (Erblich and Montgomery, 2012, Roberts et al., 2017). A potentially promising treatment is an evidence-based behavioral approach that teaches individuals to accept their cravings to smoke rather than avoid them, such as Acceptance and Commitment Therapy (ACT) (Hayes, Levin, Plumb-Vilardaga, Villatte, & Pistorello, 2013). ACT-based interventions have shown promise for smoking cessation by teaching participants to observe, acknowledge, and accept their cravings (Bricker et al., 2014, McClure et al., 2020). Importantly, instruction and practice of acceptance of cravings is conceptually distinct from existing US Clinical Practice Guidelines (USCPG)-based standard approaches that teach avoidance of cravings (Fiore, 2000). Avoidance of cravings may be impractical for heavy-drinking individuals who are more likely to crave smoking when drinking and more likely to smoke or drink when in social settings (Rodriguez-Cano, Garey, Bakhshaie, Shepherd, & Zvolensky, 2020). ACT-theory based interventions for smoking cessation could help heavy-drinking individuals quit smoking because they focus on increasing one’s ability to recognize and be open to experiencing discomfort associated with cravings (Byrne et al., 2019, Cohn et al., 2017, Roberts et al., 2020, Rodriguez-Cano et al., 2020).
Remotely delivered digital smoking cessation interventions can help reduce barriers of access to treatments that further contribute to high rates of smoking and poor cessation outcomes among adults who smoke, including those who drink heavily (Rapp et al., 2006, Tucker et al., 2004). To date, only a few feasibility trials have tested digital interventions for smoking cessation among heavy drinkers. One pilot study tested the effects of a web-based digital smoking cessation program that specifically addresses heavy drinking versus a similar smoking cessation-only program among 119 heavy-drinking adults (Kahler et al., 2020). Although user satisfaction was high, 6-month quit rates did not differ significantly between treatment conditions (19% vs. 15%). Another pilot study tested a Facebook-delivered USCPG-based smoking cessation intervention addressing both tobacco and alcohol use against an equivalent tobacco-only intervention among 179 heavy-drinking young adults (Meacham, Ramo, & Prochaska, 2021). Although user engagement and satisfaction were high, 12-month quit rates did not differ significantly from one another (29% vs. 26%). Other studies have tested the use of in-person or telephone USCPG-based counseling alone or in combination with pharmacotherapy, but these approaches have been ineffective or have had small effect sizes (Kahler et al., 2008, Toll et al., 2015).
The emergence of accessible and affordable digital interventions for smoking cessation, especially smartphone applications, has strong potential for helping heavy-drinking adults. Bricker et al. developed iCanQuit (Bricker, Watson, Mull, Sullivan, & Heffner, 2020), an ACT theory-based smartphone application for smoking cessation. In a two-arm RCT, the efficacy of an ACT-based smartphone application (iCanQuit) was tested against a USCPG-based smartphone application (QuitGuide) among 2,415 adults (Bricker et al., 2020). Compared to QuitGuide, the odds of smoking cessation at 12-months were 1.49 times higher with iCanQuit (28% iCanQuit vs. 21% QuitGuide, OR = 1.49; 95% CI: 1.22–1.83).
The present study utilized data from the iCanQuit parent trial to test the efficacy of an ACT-based smartphone application relative to an USCPG-based smartphone application for smoking cessation among heavy-drinking adults enrolled in the trial. We hypothesized that, compared to those in the QuitGuide arm, heavy-drinking adults in the iCanQuit arm would have higher rates of smoking cessation and greater increases in ACT-based acceptance of cravings to smoke. We further hypothesized that increases in acceptance of cravings to smoke would mediate the effect of the intervention on smoking cessation. To test these hypotheses, we first determined the efficacy of iCanQuit relative to QuitGuide for smoking cessation at 12-months among participants classified as heavy drinkers. Second, we compared the two treatment arms on changes in ACT-based processes. Third, we evaluated the extent to which the effect of the treatment on cessation was mediated by changes in ACT-based processes. Exploratory analyses were also conducted to better understand the effect of the intervention on cessation of both smoking and heavy drinking, and alcohol use at 12-months.
Section snippets
Overview
Data are from the two-arm randomized iCanQuit parent trial which had the eligibility criteria of adults ( 18 years) who smoked 5 cigarettes or more per day, had access to their own iPhone or Android smartphone, and wanted to quit smoking (Bricker et al., 2020). Exclusion criteria included being unable to read English, receiving smoking cessation treatment, having used QuitGuide in the past, or having a household member already enrolled in the study. All participants were screened for
Discussion
Using data from a full-scale randomized trial with long-term follow-up, the present study found that, among heavy-drinking adults, the ACT-based iCanQuit application was more efficacious for smoking cessation than the USCPG-based QuitGuide application. For the primary outcome of self-reported complete-case 30-day PPA at 12-months, iCanQuit relative to QuitGuide participants were almost twice as likely to quit smoking (24% abstinent vs. 15% abstinent). Findings were similar for the multiple
Conclusions
The current study demonstrates that an ACT-based application (iCanQuit) may be more efficacious than a USCPG-based application (QuitGuide) for helping heavy-drinking adults quit smoking. Future testing of an iCanQuit application tailored to the unique barriers to cessation for heavy-drinking adults is a promising next step in this line of research.
Funding
This study was funded by grant R01CA192849, awarded to Dr. Bricker, from the National Cancer Institute and registered in ClinicalTrials.gov (NCT02724462).
CRediT authorship contribution statement
Margarita Santiago-Torres: Conceptualization, Methodology, Writing – original draft, Visualization, Writing – review & editing. Kristin E. Mull: Conceptualization, Methodology, Data curation, Formal analysis, Visualization, Writing – review & editing. Brianna M. Sullivan: Project administration, Writing – review & editing. Michael J. Zvolensky: Conceptualization, Writing – review & editing. Christopher W. Kahler: Conceptualization, Writing – review & editing. Jonathan B. Bricker:
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We appreciate the tireless contributions of the entire study staff, most notably, Eric Meier, Eric Strand, Carolyn Ehret, Alanna Boynton, the design services of Ayogo, Inc., and the development services of Moby, Inc. We are very appreciative of the study participants.
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