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.
IMPORTANCE Smoking is a leading cause of premature death globally. Smartphone applications for smoking cessation are ubiquitous and address barriers to accessing traditional treatments, yet there is limited evidence for their efficacy.OBJECTIVE To determine the efficacy of a smartphone application for smoking cessation based on acceptance and commitment therapy (ACT) vs a National Cancer Institute smoking cessation application based on US clinical practice guidelines (USCPG). DESIGN, SETTING, AND PARTICIPANTSA 2-group, stratified, double-blind, individually randomized clinical trial was conducted from May 27, 2017, to September 28, 2018, among 2415 adult cigarette smokers (n = 1214 for the ACT-based smoking cessation application group and n = 1201 for the USCPG-based smoking cessation application group) with 3-, 6-, and 12-month postrandomization follow-up. The study was prespecified in the trial protocol. Follow-up data collection started on August 26, 2017, and ended at the last randomized participant's 12-month follow-up survey on December 23, 2019. Data were analyzed from February 25 to April 3, 2020. The primary analysis was performed on a complete-case basis, with intent-to-treat missing as smoking and multiple imputation sensitivity analyses.INTERVENTIONS iCanQuit, an ACT-based smoking cessation application, which taught acceptance of smoking triggers, and the National Cancer Institute QuitGuide, a USCPG-based smoking cessation application, which taught avoidance of smoking triggers. MAIN OUTCOMES AND MEASURESThe primary outcome was self-reported 30-day point prevalence abstinence (PPA) at 12 months after randomization. Secondary outcomes were 7-day PPA at 12 months after randomization, prolonged abstinence, 30-day and 7-day PPA at 3 and 6 months after randomization, missing data imputed with multiple imputation or coded as smoking, and cessation of all tobacco products (including e-cigarettes) at 12 months after randomization.RESULTS Participants were 2415 adult cigarette smokers (1700 women [70.4%]; 1666 White individuals [69.0%] and 868 racial/ethnic minorities [35.9%]; mean [SD] age at enrollment, 38.2 [10.9] years) from all 50 US states. The 3-month follow-up data retention rate was 86.7% ( 2093), the 6-month retention rate was 88.4% (2136), and the 12-month retention rate was 87.2% (2107). For the primary outcome of 30-day PPA at the 12-month follow-up, iCanQuit participants had 1.49 times higher odds of quitting smoking compared with QuitGuide participants (28.2% [293 of 1040] vs 21.1% [225 of 1067]; odds ratio [OR], 1.49; 95% CI, 1.22-1.83; P < .001). Effect sizes were very similar and statistically significant for 7-day PPA at the 12-month follow-up (OR, 1.35; 95% CI, 1.12-1.63; P = .002), prolonged abstinence at the 12-month follow-up (OR, 2.00; 95% CI, 1.45-2.76; P < .001), abstinence from all tobacco products (including e-cigarettes) at the 12-month follow-up (OR, 1.60; 95% CI, 1.28-1.99; P < .001), 30-day PPA at 3-month follow-up (OR, 2.20; 95% CI, 1.68-2.89; P < .001), 30-day PPA at 6-month f...
BackgroundDespite having many advantages, online eHealth trials are not without challenges—notably, participant recruitment, and outcome data retention. Moreover, publications from these trials rarely provide detailed information on the methods used for recruitment and retention or discuss implications of the methods for future studies.ObjectiveTo address this need for empirical guidance regarding recruitment and outcome data retention planning, we aim to describe the methods and lessons learned from the recruitment and retention procedures used in a large randomized trial of 2 Web-based smoking cessation interventions.MethodsTo ensure a demographically and geographically diverse participant sample, we used the recruitment strategies (1) traditional, (2) Web-based, and (3) online survey panel methods and adaptively modified each in response to recruitment success. At baseline, participants indicated how they heard about the study and answered demographic questions. To maximize trial retention at each of the 3-, 6-, and 12-month assessment points, 4 survey modalities (first Web, followed by phone, mail, and postcard) were sequentially timed over a 30-day period. Participants received US $25 for submitting their responses, regardless of modality, and received an additional US $10 bonus for completing the Web survey within 24h of electronic notification.ResultsWe randomized 2637 smokers in 16 months and achieved 88% retention at 12-months. Participants (79.26% female, 72.60% Caucasian) were recruited from all 50 states. The majority of participants were recruited through Facebook (49.43%), followed by the survey panel (20.85%), free internet sources (14.54%), traditional media (11.34%), and Google ads (3.84%). Descriptively, participant demographics varied by recruitment source. Of the completed follow-up surveys, most were completed by Web (92%). Retention rates did not vary by recruitment source.ConclusionsContinuous monitoring and refinement of multiple recruitment methods, particularly of online advertising campaigns, allowed us to maximize the effectiveness of recruitment strategies in recruiting a large, diverse sample of smokers. Likewise, offering multiple follow-up survey modalities in sequential order along with time-dependent bonus incentives enabled us to obtain outcome data from a very high level of enrolled participants for the duration of the trial protocol. These strategies may be similarly useful in other trials.Trial RegistrationClinicalTrials.gov NCT01812278; https://clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/71gy5GLvO)
Background The first randomized trial of a smartphone application (app) for adult smoking cessation (SmartQuit 1.0) revealed key features that predict cessation. These findings guided the revision of this Acceptance & Commitment Therapy (ACT)-based application (SmartQuit 2.0), which was primarily tested to examine participant receptivity, short-term cessation and reduction, and the relationship between program completion, smoking cessation and reduction. Secondarily, outcomes were descriptively compared with the SmartQuit1.0 trial. Method Adult participants (78% female, 25% with high school or less education, 30% unemployed) were recruited into the single-arm pilot trial (N = 99) of SmartQuit 2.0 with a two-month follow-up (85% retention). Results Regarding receptivity, 84% of participants were satisfied with SmartQuit 2.0 (vs. 59% for SmartQuit1.0), 73% would recommend it to a friend (vs. 48% for SmartQuit1.0), 81% found the ACT exercises useful for quitting (vs. 44% for SmartQuit1.0). At the 2-month follow-up, the quit rates were 21% for 7-day point prevalence (vs. 23% for SmartQuit1.0), 11% for 30-day point prevalence (vs. 13% for SmartQuit1.0), and 75% of participants reduced their smoking frequency (vs. 57% for SmartQuit1.0). Among program completers (24% of total sample), the quit rates were 33% for 7-day point prevalence, 28% for 30-day point prevalence, and 88% of participants reduced their smoking frequency. Conclusions The revised app had high user receptivity, modest quit rates, and high smoking reduction rates. Program completion may be key to boosting the app’s effectiveness.
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.
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