Randomized, controlled pilot trial of a smartphone app for smoking cessation using acceptance and commitment therapy

Abstract

Background There is a dual need for (1) innovative theory-based smartphone applications for smoking cessation and (2) controlled trials to evaluate their efficacy. Accordingly, this study tested the feasibility, acceptability, preliminary efficacy, and mechanism of behavioral change of an innovative smartphone-delivered Acceptance and Commitment Therapy (ACT) application for smoking cessation versus an application following US Clinical Practice Guidelines. Method Adult participants were recruited nationally into the double-blind randomized controlled pilot trial (N = 196) that compared smartphone-delivered ACT for smoking cessation application (SmartQuit) with the National Cancer Institute's application for smoking cessation (QuitGuide). Results We recruited 196 participants in two months. SmartQuit participants opened their application an average of 37.2 times, as compared to 15.2 times for QuitGuide participants (p <.0001). The overall quit rates were 13% in SmartQuit vs. 8% in QuitGuide (OR=2.7; 95% CI=0.8-10.3). Consistent with ACT's theory of change, among those scoring low (below the median) on acceptance of cravings at baseline (n = 88), the quit rates were 15% in SmartQuit vs. 8% in QuitGuide (OR=2.9; 95% CI=0.6-20.7). Conclusions ACT is feasible to deliver by smartphone application and shows higher engagement and promising quit rates compared to an application that follows US Clinical Practice Guidelines. As results were limited by the pilot design (e.g., small sample), a full-scale efficacy trial is now needed.

A systematic review of smartphone applications for smoking cessation

“…While some apps have shown promise in small randomized trials for promoting changes in smoking, including point prevalence abstinence, none have been tested with fully powered studies [21,22,25]. Apparent turnover of apps, inconsistent quality, varying results between search terms, and irrelevant app suggestions are significant barriers for consumers seeking scientifically supported health apps.…”

“…Heath apps offer functionality which allows users to receive reminders for health appointments and medication adherence for chronic conditions such as diabetes, while others offer accessible, real-time, monitoring and social support for behavioral health conditions such as tobacco addiction [19]. With the ubiquity of the mobile phone, and the potential for flexible treatment options to reach more people, research about health apps is on the rise, although, few studies have examined the quality of content or the effectiveness of apps promoting smoking cessation [21][22][23][24][25][26][27].…”

Realising the technological promise of smartphones in addiction research and treatment: An ethical review

“…There is great potential of mHealth technology, yet it is imperative that we first address these ethical considerations to ensure that we capitalise on the possible benefits of these technologies while minimising the potential risks to the users. BinDhim et al, 2014;Borland et al, 2013;Bricker et al, 2014;Buller et al, 2014;Haug et al, 2014;Hertzberg et al, 2013;Kirchner et al, 2013;Meredith et al, 2014;V. Patel, Nowostawski, Thomson, Wilson, & Medlin, 2013;Ploderer et al, 2014;Reitzel et al, 2014; Whittaker, 2011) Alcohol 12 (34.3%) (Bendtsen & Bendtsen, 2014;Dulin et al, 2014;Gajecki et al, 2014;Gamito et al, 2014;Haug et al, 2014;Kauer, Reid, Sanci, & Patton, 2009;Matsumura, Yamakoshi, & Ida, 2009;McTavish et al, 2012;Renner, 2012;Yu et al, 2012) Heroin 2 (5.7%) Epstein et al, 2009) Cocaine 1 (2.9%) (Freedman, Lester, McNamara, Milby, & Schumacher, 2006) General 3 (8.6%) (Campling, 2011;Ingersoll et al, 2014; Bendtsen & Bendtsen, 2014;BinDhim et al, 2014;Borland et al, 2013;Bricker et al, 2014;Buller et al, 2014;Dulin et al, 2014;Hasin et al, 2014;Haug et al, 2014;Ingersoll et al, 2014;Ploderer et al, 2014;…”

“…User anonymity 13 (38.2% a ) BinDhim et al, 2014;Borland et al, 2013;Freedman et al, 2006;Gajecki et al, 2014;Haug et al, 2014;Matsumura et al, 2009;Renner, 2012;) Data encryption 11 (32.3% b ) BinDhim et al, 2014;Boyer et al, 2012;Gajecki et al, 2014;Gamito et al, 2014;Haug et al, 2014;Meredith et al, 2014;Renner, 2012;) Password protection 7 (24.1% c ) Hasin et al, 2014;Haug et al, 2014;Hertzberg et al, 2013;Renner, 2012;) User control 20 (69.0% d ) (Bendtsen & Bendtsen, 2014;BinDhim et al, 2014;Bricker et al, 2014;Campling, 2011;Gajecki et al, 2014;Haug et al, 2014;Hertzberg et al, 2013;Ingersoll et al, 2014;Kauer et al, 2009;Ploderer et al, 2014;Reitzel et al, 2014;Renner, 2012;Whittaker, 2011;Yu et al, 2012 Dulin et al, 2014;Epstein et al, 2009;Freedman et al, 2006;Gamito et al, 2014;Hasin et al, 2014;Ingersoll et al, 2014;Johnson et al, 2009;Kauer et al, 2009;…”

“…One, for example, provided detailed personalised feedback in the form of graphs and summaries and, after 30 days, patients met with counsellors to ensure that they understood the feedback . Other apps fulfilled this ethical requirement by providing users with features mapping their selfreported progress in the form of monetary or health benefits trackers Bricker et al, 2014;. To be clinically meaningful, however, the findings must be scientifically robust and presented in a way that the patient understands.…”