Do medications increase the efficacy of digital interventions for smoking cessation? Secondary results from the iCanQuit randomized trial

BACKGROUND AND AIMS

iCanQuit is a smartphone application (app) proven efficacious for smoking cessation in a Phase III randomized controlled trial (RCT). This study aimed to measure whether medications approved by the US Food and Drug Administration (FDA) for smoking cessation would further enhance the efficacy of iCanQuit, relative to its parent trial comparator-the National Cancer Institute's (NCI's) QuitGuide app.

DESIGN

Secondary analysis of the entire parent trial sample of a two-group (iCanQuit and QuitGuide), stratified, doubled-blind RCT.

SETTING

United States.

PARTICIPANTS

Participants who reported using an FDA-approved cessation medication on their own (n = 619) and those who reported no use of cessation medications (n = 1469).

INTERVENTIONS

Participants were randomized to receive iCanQuit app or NCI's QuitGuide app.

MEASUREMENTS

Use of FDA-approved medications was measured at 3 months post-randomization. Smoking cessation outcomes were measured at 3, 6 and 12 months. The primary outcome was 12-month self-reported 30-day point prevalence abstinence (PPA).

FINDINGS

The data retention rate at the 12-month follow-up was 94.0%. Participants were aged 38.5 years, 71.0% female, 36.6% minority race/ethnicity, 40.6% high school or less education, residing in all 50 US States and smoking 19.2 cigarettes/day. The 29.6% of all participants who used medications were more likely to choose nicotine replacement therapy (NRT; 78.8%) than other cessation medications (i.e. varenicline or bupropion; 18.3 and 10.5%, respectively) and use did not differ by app treatment assignment (all P > 0.05). There was a significant (P = 0.049) interaction between medication use and app treatment assignment on PPA. Specifically, 12-month quit rates were 34% for iCanQuit versus 20% for QuitGuide [odds ratio (OR) = 2.36, 95% confidence interval (CI) = 1.59, 3.49] among participants reporting any medication use, whereas among participants reporting no medication use, quit rates were 28% for iCanQuit versus 22% for QuitGuide (OR = 1.41, 95% CI = 1.09, 1.82). Results were stronger for those using only NRT: 40% quit rates for iCanQuit versus 18% quit rates for QuitGuide (OR = 3.57, 95% CI = 2.20, 5.79).

CONCLUSIONS

The iCanQuit smartphone app for smoking cessation was more efficacious than the QuitGuide smartphone app, regardless of whether participants used medications to aid cessation. Smoking cessation medications, especially nicotine replacement therapy, might enhance the efficacy of the iCanQuit app.

Acceptance and Commitment Therapy-Based Smartphone Applications for Cessation of Tobacco Use among Adults with High Nicotine Dependence: Results from the iCanQuit Randomized Trial

Background: With 1 in 2 adult tobacco users being highly dependent on nicotine, population-based interventions specifically designed for this group are urgently needed. This study used data from a randomized trial to evaluate whether (1) Acceptance and Commitment Therapy (ACT) delivered via a smartphone application (iCanQuit) would be more efficacious for cessation of nicotine-containing tobacco products than the US Clinical Practice Guidelines (USCPG)-based application (QuitGuide) among highly nicotine-dependent adults, (2) the effect of treatment on cessation was mediated by increases in acceptance of cravings to smoke, and (3) treatment utilization and satisfaction differed by arm. Methods: A total of 1452 highly nicotine-dependent adults received the iCanQuit or QuitGuide application for 12-months. Cessation outcomes were self-reported complete-case 30-day abstinence of nicotine-containing tobacco products (e.g., combustible cigarettes, e-cigarettes, chewing tobacco, snus, hookahs, cigars, cigarillos, tobacco pipes, and kreteks) at 3, 6, and 12-month post-randomization timepoints, missing-as-smoking, and multiple imputation analyses. Acceptance of cues to smoke and satisfaction with the applications was also reported. Results: Participants who received iCanQuit were significantly more likely to report 30-day abstinence of nicotine-containing tobacco products than those who received QuitGuide at 12-months (24% vs. 17%; OR = 1.47 95% CI: 1.11, 1.95). iCanQuit participants utilized their application more frequently and reported greater satisfaction than those who received QuitGuide. Increases in participants' acceptance of cues to smoke mediated the intervention effect on cessation of nicotine-containing tobacco products. Conclusions: Among nicotine-dependent adults, an application-delivered ACT-based intervention was more engaging and efficacious than a USCPG-based intervention for cessation of nicotine-containing tobacco products.

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

BACKGROUND

A single generalizable metric that accurately predicts early dropout from digital health interventions has the potential to readily inform intervention targets and treatment augmentations that could boost retention and intervention outcomes. We recently identified a type of early dropout from digital health interventions for smoking cessation, specifically, users who logged in during the first week of the intervention and had little to no activity thereafter. These users also had a substantially lower smoking cessation rate with our iCanQuit smoking cessation app compared with users who used the app for longer periods.

OBJECTIVE

This study aimed to explore whether log-in count data, using standard statistical methods, can precisely predict whether an individual will become an iCanQuit early dropout while validating the approach using other statistical methods and randomized trial data from 3 other digital interventions for smoking cessation (combined randomized N=4529).

METHODS

Standard logistic regression models were used to predict early dropouts for individuals receiving the iCanQuit smoking cessation intervention app, the National Cancer Institute QuitGuide smoking cessation intervention app, the WebQuit.org smoking cessation intervention website, and the Smokefree.gov smoking cessation intervention website. The main predictors were the number of times a participant logged in per day during the first 7 days following randomization. The area under the curve (AUC) assessed the performance of the logistic regression models, which were compared with decision trees, support vector machine, and neural network models. We also examined whether 13 baseline variables that included a variety of demographics (eg, race and ethnicity, gender, and age) and smoking characteristics (eg, use of e-cigarettes and confidence in being smoke free) might improve this prediction.

RESULTS

The AUC for each logistic regression model using only the first 7 days of log-in count variables was 0.94 (95% CI 0.90-0.97) for iCanQuit, 0.88 (95% CI 0.83-0.93) for QuitGuide, 0.85 (95% CI 0.80-0.88) for WebQuit.org, and 0.60 (95% CI 0.54-0.66) for Smokefree.gov. Replacing logistic regression models with more complex decision trees, support vector machines, or neural network models did not significantly increase the AUC, nor did including additional baseline variables as predictors. The sensitivity and specificity were generally good, and they were excellent for iCanQuit (ie, 0.91 and 0.85, respectively, at the 0.5 classification threshold).

CONCLUSIONS

Logistic regression models using only the first 7 days of log-in count data were generally good at predicting early dropouts. These models performed well when using simple, automated, and readily available log-in count data, whereas including self-reported baseline variables did not improve the prediction. The results will inform the early identification of people at risk of early dropout from digital health interventions with the goal of intervening further by providing them with augmented treatments to increase their retention and, ultimately, their intervention outcomes.

Can a smartphone application help Hispanic/Latinx adults quit smoking? A randomized trial secondary analysis

Introduction

There are no known efficacious digital smoking cessation interventions for Hispanic/Latinx adults who smoke. This study is a secondary analysis using data from a randomized trial to evaluate whether Acceptance and Commitment Therapy (ACT) delivered via a smartphone app (iCanQuit) would be more efficacious for smoking cessation than the US Clinical Practice (USCPG)-based app (QuitGuide) in a sample of Hispanic/Latinx participants.

Methods

A total of 210 Hispanic/Latinx adults who smoke were randomized to receive the iCanQuit or QuitGuide app for 12-months. Participants self-reported on 30-day abstinence from cigarette smoking at the 3-month, 6-month, and 12-month follow-ups; 7-day abstinence at all follow-ups; abstinence from other nicotine/tobacco products at 12-months; and continuous prolonged abstinence from 3 to 12-months. Participants also reported on their willingness to accept cues to smoke without smoking and satisfaction with their apps.

Results

A total of 176 (84%) participants reported on study outcomes at the 12-month follow-up. Compared to QuitGuide participants, iCanQuit participants were significantly more likely to report 30-day abstinence from cigarette smoking at 12-months (34% iCanQuit, 20% QuitGuide; p=0.026). iCanQuit participants utilized their app more frequently and reported greater satisfaction with their assigned app than those who received the QuitGuide app. Increases in participants' willingness to accept cues to smoke mediated the intervention effect on abstinence from cigarette smoking at 12-months.

Conclusions

Acceptance and Commitment Therapy-delivered via a smartphone app may be efficacious for helping Hispanic/Latinx adults abstain from cigarette smoking. Replication in a fully powered randomized trial that focuses on an independent sample of Hispanic/Latinx adults is now needed.

Efficacy of smartphone applications for smoking cessation in heavy-drinking adults: Secondary analysis of the iCanQuit randomized trial

INTRODUCTION

Efficacious smoking cessation treatments are needed for heavy-drinking adults who often have difficulty quitting smoking. In a secondary analysis of a parent randomized controlled trial, we explored the efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) versus a US Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation among heavy-drinking participants (4 + drinks/day for women; 5 + drinks/day for men).

METHODS

Participants were randomized to receive iCanQuit (n = 188) or QuitGuide (n = 160) for 12-months. Smoking cessation outcomes were measured at 3, 6 and 12-months. The primary outcome was self-reported complete-case 30-day point prevalence abstinence (PPA) at 12-months. Secondary outcomes were 7-day PPA at all timepoints; prolonged abstinence; and cessation of all nicotine-containing products at 12-months. Multiple imputation and missing-as-smoking analyses were also conducted. Exploratory outcomes were cessation of both smoking and heavy drinking and change in alcohol use (drinks/day) at 12-months. Treatment engagement and satisfaction and change in ACT-based processes were compared between arms.

RESULTS

Retention rate was 85% at 12-months and did not differ by arm. At 12-months, iCanQuit participants had nearly double the odds of smoking cessation compared to QuitGuide (complete-case 30-day PPA = 24% vs. 15%; OR = 1.87 95% CI: 1.03, 3.42). Findings were similar for the multiple imputation and missing-as-smoking outcomes at 12-months. Combined cessation of smoking and heavy drinking, and alcohol use at 12-months did not differ by arm. iCanQuit was significantly more engaging and satisfying than QuitGuide. Increased acceptance of thoughts about smoking mediated the effect of treatment on cessation of heavy drinking at 12-months.

CONCLUSIONS

The iCanQuit smartphone application was more efficacious and engaging for smoking cessation among heavy-drinking adults than a USCPG-based smartphone application.

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

BACKGROUND

Little is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes.

OBJECTIVE

In the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership.

METHODS

Functional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app.

RESULTS

For iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app.

CONCLUSIONS

Patterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful.

Efficacy of an acceptance and commitment therapy-based smartphone application for helping rural populations quit smoking: Results from the iCanQuit randomized trial

Limited access to evidence-based smoking cessation interventions among rural populations contributes to high rates of cigarette smoking and poor cessation outcomes. Yet, accessible digital interventions for cessation focusing on rural populations are lacking. In a secondary analysis, we determined the acceptability and efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) relative to a U.S. Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation among rural participants enrolled in the two-arm randomized iCanQuit trial. Participants were enrolled between May 2017 and September 2018 and randomized to either receive iCanQuit or QuitGuide for 12-months. Rural residence was determined by sub-county level Rural-Urban Commuting Area codes. A total of 550 rural participants were recruited from 43 U.S. states. Self-reported complete-case 30-day point-prevalence abstinence was 15% (33/226) for iCanQuit vs. 9% (22/253) for QuitGuide at 3-months (OR = 1.83; 95% CI: 1.03, 3.25) and 29% (66/231) for iCanQuit vs. 25% (64/288) for QuitGuide at 12-months (OR = 1.19 95% CI: 0.80, 1.79). Retention rate was 89% at 12-months and did not differ by arm. iCanQuit vs. QuitGuide participants were significantly more engaged and satisfied with the iCanQuit application. Increased acceptance of internal cues to smoke mediated the effect of treatment on cessation. Findings suggest that iCanQuit had significantly higher short-term quit rates, descriptively higher long-term quit rates, and operated through its hypothesized mechanisms of action relative to QuitGuide. Future larger studies are needed to further evaluate the efficacy of and methods for disseminating the iCanQuit application for smoking cessation among U.S. rural adults nationwide. Trial registrationClinicalTrials.gov Identifier: NCT02724462.

Efficacy and utilization of an acceptance and commitment therapy-based smartphone application for smoking cessation among Black adults: secondary analysis of the iCanQuit randomized trial

BACKGROUND AND AIMS

Black adults who smoke are less likely to seek treatment and to succeed in quitting compared with other racial groups. The lack of efficacious and engaging trials for smoking cessation further contributes to this disparity. This study explored whether an acceptance and commitment therapy (ACT)-based smartphone application (iCanQuit) was more efficacious for smoking cessation than a United States Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) among Black adults.

DESIGN

Secondary analysis of a two-arm randomized trial with 12-month follow-up.

SETTING

United States (US).

PARTICIPANTS

A total of 554 Black adults who smoke daily were recruited from 34 US states and enrolled between May 2017 and September 2018.

INTERVENTIONS

Participants were randomized to receive iCanQuit (n = 274) or QuitGuide (n = 280) for 12 months.

MEASUREMENTS

Smoking cessation outcomes were measured at 3, 6, and 12 months. The primary outcome was self-reported complete-case 30-day point prevalence abstinence (PPA) at 12 months. Secondary outcomes were 7-day PPA, missing-as-smoking imputation, multiple imputation, prolonged abstinence, and cessation of all tobacco products at 12 months. Study retention, treatment engagement, and change in ACT-based processes were also compared between arms.

FINDINGS

Study retention was 89% at 12 months and did not differ by arm (P > 0.05). The complete-case 30-day PPA was 28% for iCanQuit versus 20% for QuitGuide at 12 months (odds ratio [OR] = 1.60; 95% confidence interval [CI] = 1.03, 2.46). Similar associations were observed for the missing-as-smoking imputation, although non-significant (25% iCanQuit vs 18% QuitGuide; OR = 1.50; 95% CI = 0.98, 2.30). iCanQuit vs QuitGuide participants were significantly more engaged with iCanQuit application as measured by the number of logins from baseline to 6 months (incidence rate ratio = 3.26; 95% CI = 2.58, 4.13). Increased acceptance of cues to smoke mediated the effect of treatment on cessation (indirect effect: OR = 0.20; 95% CI = 0.05, 0.29).

CONCLUSIONS

Among Black adults, an acceptance and commitment therapy-based smartphone application appeared to be more efficacious and engaging for smoking cessation than the United States Clinical Practice Guidelines-based QuitGuide application.