An Avatar-Led Web-Based and SMS Text Message Smoking Cessation Program for Socioeconomically Disadvantaged Veterans: Pilot Randomized Controlled Trial.

BACKGROUND: Despite the declining prevalence of cigarette smoking in the United States, socioeconomically disadvantaged veterans receiving care from the Veterans Health Administration have a high prevalence of smoking. Currently, available treatment options for these veterans focus on tobacco users who are ready to quit and have limited reach. Consequently, there is a great need for accessible, effective smoking cessation interventions for veterans at all levels of readiness to quit smoking. OBJECTIVE: To address these needs, we developed Vet Flexiquit, a web-based Acceptance and Commitment Therapy program for veterans, and evaluated its acceptability (primary aim), efficacy, and impact on theory-based change processes relative to the National Cancer Institute's SmokefreeVET program in a pilot randomized controlled trial. METHODS: Participants (N=49) were randomized 1:1 to receive either the Vet Flexiquit (n=25) or SmokefreeVET (n=24) web program. Both groups received SMS text messages as part of the intervention for 6 weeks. Both interventions are fully automated and self-guided. Primary outcome data were collected at 3 months after the randomization. Self-reported smoking abstinence was biochemically verified using saliva cotinine. Multivariable logistic regression, negative binomial regression, and linear regression models were used to evaluate the association between the treatment arm and outcomes of interest. RESULTS: Acceptability, as measured by overall treatment satisfaction, was high and similar across treatment arms: 100% (17/17) for Vet Flexiquit and 95% (18/19) for SmokefreeVET. Acceptability, as measured by utilization, was more modest (log-ins: M=3.7 for Vet Flexiquit and M=3.2 for SmokefreeVET). There were no statistically significant differences between treatment arms for any acceptability measures. Similarly, there were no statistically significant differences between treatment arms in the secondary outcomes of smoking cessation or change in Acceptance and Commitment Therapy's theory-based processes. In open-ended survey responses, some veterans in both treatment arms expressed interest in having support from a professional or peer to enhance their experience, as well as an expanded SMS text messaging program. CONCLUSIONS: Both programs had high ratings of acceptability, limited utilization, and a similar impact on cessation and cessation processes. Taken together with the qualitative data suggesting that additional support may enhance participants' experience of both programs, these preliminary findings suggest that the programs may have similar outcomes among veterans who are looking for a digital cessation treatment option and that integrating provider or peer support and enhancing the SMS text messaging program holds promise as a means of boosting engagement and outcomes for both programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04502524; https://clinicaltrials.gov/ct2/show/NCT04502524.

An Avatar-Led Digital Smoking Cessation Program for Sexual and Gender Minority Young Adults: Intervention Development and Results of a Single-Arm Pilot Trial.

BACKGROUND: Sexual and gender minority young adults have a high prevalence of smoking and unique barriers to accessing tobacco treatment. OBJECTIVE: To address these challenges as well as their preferences for sexual and gender minority-targeted interventions and digital programs, we developed and evaluated the acceptability, preliminary efficacy, and impact on theory-based change processes of an acceptance and commitment therapy-based digital program called Empowered, Queer, Quitting, and Living (EQQUAL). METHODS: Participants (n=22) of a single-arm trial conducted to evaluate the program were young adults, age 18 to 30 years, who self-identified as sexual and gender minority individuals and smoked at least one cigarette per day. All participants received access to the EQQUAL program. Participants completed web-based surveys at baseline and at a follow-up 2 months after enrollment. We verified self-reported smoking abstinence with biochemical testing; missing data were counted as smoking or using tobacco. RESULTS: For young adults who logged in at least once (n=18), the mean number of log-ins was 5.5 (SD 3.6), mean number of sessions completed was 3.1 (SD 2.6), and 39% (7/18) completed all 6 sessions. Overall, 93% of participants (14/15) were satisfied with the EQQUAL program, 100% (15/15) found it easy to use, and 100% (15/15) said it helped them be clearer about how to quit. Abstinence from smoking or using tobacco was confirmed with biochemical testing for 23% of participants (5/22). Both quantitative and qualitative results suggested a positive overall response to the avatar guide, with areas for future improvement largely centered on the avatar's appearance and movements. CONCLUSIONS: Treatment acceptability of EQQUAL was very promising. The rate of abstinence, which was biochemically confirmed, was 3 times higher than that of the only other digital program to date that has targeted sexual and gender minority young adults and 6 to 13 times higher than those of nontargeted digital smoking interventions among sexual and gender minority young adults. Planned improvements for the next iteration of the program include making the avatar's movements more natural; offering multiple avatar guides with different on characteristics such as race, ethnicity, and gender identity from which to choose; and providing a support forum for users to connect anonymously with peers.

Identifying Content-Based Engagement Patterns in a Smoking Cessation Website and Associations With User Characteristics and Cessation Outcomes: A Sequence and Cluster Analysis.

INTRODUCTION: Using WebQuit as a case study, a smoking cessation website grounded in Acceptance and Commitment Therapy, we aimed to identify sequence clusters of content usage and examine their associations with baseline characteristics, change to a key mechanism of action, and smoking cessation. METHODS: Participants were adult smokers allocated to the WebQuit arm in a randomized controlled trial (n = 1,313). WebQuit contains theory-informed content including goal setting, self-monitoring and feedback, and values- and acceptance-based exercises. Sequence analysis was used to temporally order 30-s website usage segments for each participant. Similarities between sequences were assessed with the optimal matching distance algorithm and used as input in an agglomerative hierarchical clustering analysis. Associations between sequence clusters and baseline characteristics, acceptance of cravings at 3 months and self-reported 30-day point prevalence abstinence at 12 months were examined with linear and logistic regression. RESULTS: Three qualitatively different sequence clusters were identified. "Disengagers" (576/1,313) almost exclusively used the goal-setting feature. "Tryers" (375/1,313) used goal setting and two of the values- and acceptance-based components ("Be Aware," "Be Willing"). "Committers" (362/1,313) primarily used two of the values- and acceptance-based components ("Be Willing," "Be Inspired"), goal setting, and self-monitoring and feedback. Compared with Disengagers, Committers demonstrated greater increases in acceptance of cravings (p = .01) and 64% greater odds of quit success (ORadj = 1.64, 95% CI = 1.18, 2.29, p = .003). DISCUSSION: WebQuit users were categorized into Disengagers, Tryers, and Committers based on their qualitatively different content usage patterns. Committers saw increases in a key mechanism of action and greater odds of quit success. IMPLICATIONS: This case study demonstrates how employing sequence and cluster analysis of usage data can help researchers and practitioners gain a better understanding of how users engage with a given eHealth intervention over time and use findings to test theory and/or to improve future iterations to the intervention. Future WebQuit users may benefit from being directed to the values- and acceptance-based and the self-monitoring and feedback components via reminders over the course of the program.

The association between frequency of e-cigarette use and long-term smoking cessation outcomes among treatment-seeking smokers receiving a behavioral intervention.

INTRODUCTION: A growing body of literature suggests daily, but not non-daily, e-cigarette use is associated with greater odds of quitting combustible cigarettes in the general adult population. However, it is unknown if these findings generalize to treatment-seeking smokers who are receiving a behavioral intervention. Our primary aim was to examine whether frequency of e-cigarette use was associated with subsequent cessation among treatment-seeking smokers who are receiving a behavioral smoking cessation intervention. METHODS: Participants (N = 2637) enrolled in a RCT of web-based smoking treatments reported their use of e-cigarettes at baseline, 3-, and 6-months. Three groups were created based on e-cigarette use: (1) non-users, (2) intermittent users, and (3) daily users. The primary outcome was complete-case, self-reported 30-day point prevalence abstinence at 12 months. RESULTS: Compared to non-users, daily e-cigarette users were significantly less likely to be abstinent (21.39 % vs. 29.68 %; p = .006). Quit rates for intermittent users (24.56 %) were not significantly different from non-users (p = .092). Nicotine dependence moderated the results such that among smokers with low nicotine dependence, those who used e-cigarettes (intermittently or daily) were less likely to quit than non-users; these differences were not significant among those with high nicotine dependence. Post hoc analyses indicated that initiating daily e-cigarette use after baseline, but not daily e-cigarette use at baseline, was associated with lower odds of cessation. CONCLUSIONS: Daily e-cig use may be associated with lower odds of quitting smoking among treatment-seeking smokers, particularly among those with lower nicotine dependence and who initiate daily use after beginning an intervention.

Efficacy of Smartphone Applications for Smoking Cessation: A Randomized Clinical Trial.

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 Participants: A 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 Measures: The 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 follow-up (OR, 2.03; 95% CI, 1.63-2.54; P < .001), 7-day PPA at 3-month follow-up (OR, 2.04; 95% CI, 1.64-2.54; P < .001), and 7-day PPA at 6-month follow-up (OR, 1.73; 95% CI, 1.42-2.10; P < .001). Conclusions and Relevance: This trial provides evidence that, compared with a USCPG-based smartphone application, an ACT-based smartphone application was more efficacious for quitting cigarette smoking and thus can be an impactful treatment option. Trial Registration: ClinicalTrials.gov Identifier: NCT02724462.

Which Method of Assessing Depression and Anxiety Best Predicts Smoking Cessation: Screening Instruments or Self-Reported Conditions?

INTRODUCTION: Affective disorders and symptoms (ADS) are predictive of lower odds of quitting smoking. However, it is unknown which approach to assessing ADS best predicts cessation. This study compared a battery of ADS screening instruments with a single, self-report question on predicting cessation. Among those who self-reported ADS, we also examined if an additional question regarding whether participants believed the condition(s) might interfere with their ability to quit added predictive utility to the single-item question. METHODS: Participants (N = 2637) enrolled in a randomized controlled trial of web-based smoking treatments completed a battery of five ADS screening instruments and answered a single-item question about having ADS. Those with a positive self-report on the single-item question were also asked about their interference beliefs. The primary outcome was complete-case, self-reported 30-day point prevalence abstinence at 12 months. RESULTS: Both assessment approaches significantly predicted cessation. Screening positive for ≥ one ADS in the battery was associated with 23% lower odds of quitting than not screening positive for any (p = .023); those with a positive self-report on the single-item had 39% lower odds of quitting than self-reporting no mental health conditions (p < .001). Area under the receiver operating characteristic curve values for the two assessment approaches were similar (p = .136). Adding the interference belief question to the single-item assessment significantly increased the area under the receiver operating characteristic curve value (p = .042). CONCLUSIONS: The single-item question assessing ADS had as much predictive validity, and possibly more, than the battery of screening instruments for identifying participants at risk for failing to quit smoking. Adding a question about interference beliefs significantly increased the predictive utility of the single-item question. IMPLICATIONS: This is the first study to demonstrate that a single-item question assessing ADS has at least as much predictive validity, and possibly more, than a battery of validated screening instruments for identifying smokers at highest risk for cessation failure. This study also demonstrates adding a question about interference beliefs significantly adds to the predictive utility of a single, self-report question about mental health conditions. Findings from this study can be used to inform decisions regarding how to assess ADS in the context of tobacco treatment settings.

A Smartphone App Designed to Help Cancer Patients Stop Smoking: Results From a Pilot Randomized Trial on Feasibility, Acceptability, and Effectiveness.

BACKGROUND: Persistent smoking after a cancer diagnosis predicts worse treatment outcomes and mortality, but access to effective smoking cessation interventions is limited. Smartphone apps can address this problem by providing a highly accessible, low-cost smoking cessation intervention designed for patients with a recent cancer diagnosis. OBJECTIVE: This study aimed to summarize our development process and report the trial design, feasibility, participant acceptability, preliminary effectiveness, and impact on processes of change (eg, cancer stigma) of the first-known smoking cessation smartphone app targeted for cancer patients. METHODS: We used an agile, user-centered design framework to develop a fully automated smartphone app called Quit2Heal that provided skills training and stories from cancer survivors focusing on coping with internalized shame, cancer stigma, depression, and anxiety as core triggers of smoking. Quit2Heal was compared with the National Cancer Institute's QuitGuide, a widely used stop smoking app for the general population, in a pilot double-blinded randomized trial with a 2-month follow-up period. Participants were 59 adult smokers diagnosed with cancer within the past 12 months and recruited through 2 cancer center care networks and social media over a 12-month period. The most common types of cancer diagnosed were lung (21/59, 36%) and breast (10/59, 17%) cancers. The 2-month follow-up survey retention rate was 92% (54/59) and did not differ by study arm (P=.15). RESULTS: Compared with QuitGuide participants, Quit2Heal participants were more satisfied with their assigned app (90% [19/21] for Quit2Heal vs 65% [17/26] for QuitGuide; P=.047) and were more likely to report that the app assigned to them was made for someone like them (86% [18/21] for Quit2Heal vs 62% [16/26] for QuitGuide; P=.04). Quit2Heal participants opened their app a greater number of times during the 2-month trial period, although this difference was not statistically significant (mean 10.0, SD 14.40 for Quit2Heal vs mean 6.1, SD 5.3 for QuitGuide; P=.33). Self-reported 30-day point prevalence quit rates at the 2-month follow-up were 20% (5/25) for Quit2Heal versus 7% (2/29) for QuitGuide (odds ratio 5.16, 95% CI 0.71-37.29; P=.10). Quit2Heal participants also showed greater improvement in internalized shame, cancer stigma, depression, and anxiety, although these were not statistically significant (all P>.05). CONCLUSIONS: In a pilot randomized trial with a high short-term retention rate, Quit2Heal showed promising acceptability and effectiveness for helping cancer patients stop smoking. Testing in a full-scale randomized controlled trial with a longer follow-up period and a larger sample size is required to test the effectiveness, mediators, and moderators of this promising digital cessation intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03600038; https://clinicaltrials.gov/ct2/show/NCT03600038.

Long-Term Smoking Cessation Outcomes for Sexual Minority Versus Nonminority Smokers in a Large Randomized Controlled Trial of Two Web-Based Interventions.

INTRODUCTION: Despite greater smoking prevalence among sexual minority (SM) individuals relative to non-SM individuals, minimal research has examined whether SM smokers have differential success at quitting, and no prior treatment studies have examined differences within SM subgroups. There is also limited knowledge of the psychosocial characteristics of treatment-seeking SM smokers, which could inform targeted treatments. To address these gaps, we compared treatment outcomes and baseline characteristics for SM and non-SM smokers and for bisexual versus lesbian or gay smokers in a large randomized controlled trial of two web-based cessation treatments. METHODS: Trial participants completed a survey to assess baseline characteristics, including self-identification as either SM (n = 253; lesbian or gay, n = 122; bisexual, n = 131) or non-SM (n = 2384). The primary cessation outcome was complete-case, self-reported 30-day abstinence at 12 months after randomization. RESULTS: Cessation outcomes did not differ significantly for SM versus non-SM smokers (24% vs. 25%, adjusted OR = 0.91, 95% CI = 0.65 to 1.28) or across SM subgroups (24% for bisexual vs. 23% for lesbian or gay, adjusted OR = 1.01, 95% CI = 0.51 to 2.00), and there were no interactions with treatment group assignment. At baseline, SM smokers differed from non-SM smokers on most demographics, were more likely to screen positive for all mental health conditions assessed, and had greater exposure to other smokers in the home. CONCLUSIONS: Substantial differences in baseline characteristics of SM versus non-SM smokers and bisexual versus lesbian or gay smokers did not translate into differential treatment outcomes. Nonetheless, SM smokers' willingness or ability to quit smoking could be enhanced by taking their unique psychosocial profile into account when designing targeted interventions. IMPLICATIONS: The findings of this study, which included the largest sample of SM smokers in a prospective intervention trial to date, support those of a small extant body of literature showing no differences in treatment-assisted cessation outcomes between SM and non-SM smokers. Regardless of their quit rates relative to non-SM smokers, SM smokers' willingness or ability to quit smoking could potentially be enhanced by taking their unique psychosocial profile into account in intervention design, including their younger age, lower socioeconomic status, greater likelihood of being racial or ethnic minorities, and greater prevalence of mental health symptoms.

Pilot Randomized Controlled Trial of Web-Delivered Acceptance and Commitment Therapy Versus Smokefree.gov for Smokers With Bipolar Disorder.

INTRODUCTION: Smokers with bipolar disorder (BD) are less successful at quitting than the general population. In this study, we evaluated in a pilot randomized controlled trial a novel, targeted, web-based intervention for smokers with BD based on acceptance and commitment therapy (ACT) and designed for reach and disseminability. AIMS AND METHODS: Daily smokers (n = 51) with bipolar I or II disorder were recruited from four US sites and randomly assigned to one of two web-based smoking cessation interventions-ACT-based WebQuit Plus (n = 25) or Smokefree.gov (n = 26) over a 10-week treatment period. All participants received nicotine patch for 8 weeks. Key outcomes were trial design feasibility, intervention acceptability, and cessation at end of treatment and 1-month follow-up. RESULTS: We screened 119 to enroll 51 participants (target sample size = 60) over 24 months. The most common reason for ineligibility was the inability to attend study appointments. Retention was 73% at end of treatment and 80% at follow-up, with no differences by arm. The mean number of logins was twice as high for WebQuit Plus (10.3 vs. 5.3). The usefulness of program skills was rated higher for WebQuit Plus (75% vs. 29%). Biochemically confirmed, 7-day abstinence at end of treatment was 12% in WebQuit Plus versus 8% in Smokefree.gov (odds ratio = 1.46, 95% confidence interval = 0.21 to 9.97). At follow-up, abstinence rates were 8% in both arms. CONCLUSIONS: Trial design produced favorable retention rates, although alternative recruitment methods will be needed for a larger trial. At end of treatment, acceptability and estimated effect size of WebQuit Plus relative to Smokefree.gov were promising and support continued program refinement and evaluation. IMPLICATIONS: In this first randomized controlled trial of a targeted intervention for smokers with BD, we found that the ACT-based WebQuit Plus intervention, delivered in combination with the nicotine patch, had promising acceptability and cessation outcomes relative to Smokefree.gov. The observed signals for acceptability and cessation suggest that the WebQuit Plus program should be refined based on participant feedback and evaluated in a larger trial. Feasibility findings from this study also provide direction for refining trial procedures to enhance the recruitment of smokers with BD.

A Behavioral Activation Mobile Health App for Smokers With Depression: Development and Pilot Evaluation in a Single-Arm Trial.

BACKGROUND: The integration of Behavioral Activation Treatment for Depression (BAT-D) into smoking cessation interventions is a promising approach to address depression as a barrier to quitting. However, this approach has only been tested as a face-to-face intervention, which has low reach. OBJECTIVE: The aims of the study were to develop a BAT-D mobile health app with high potential reach and determine its feasibility, acceptability, and preliminary effects on theory-based behavioral processes of behavioral activation, reduced depressive symptoms, and smoking cessation. METHODS: Following a user-centered design process consisting of competitive analysis, focus groups, and prototype testing, we conducted a single-arm pilot trial of Actify!, a BAT-D app for depressed smokers. Participants used SmokefreeTXT along with Actify! to provide cessation content that had not yet been built into the app for this initial phase of pilot testing. Participants in the trial were current, daily smokers with mild to moderate depressive symptoms. We examined use outcomes for all enrolled participants and process and cessation outcomes at 6 weeks postenrollment for study completers (16/17, 94% retention). RESULTS: Regarding acceptability, average number of log-ins per participant was 16.6 (SD 13.7), and 63% (10/16) reported being satisfied overall with the app. Posttreatment interviews identified some usability challenges (eg, high perceived burden of planning and scheduling values-based activities). There was a significant decrease in depressive symptoms from baseline to follow-up (mean change in Patient Health Questionnaire-9 scores was -4.5, 95% CI -7.7 to -1.3; P=.01). Additionally, carbon monoxide (CO)-confirmed, 7-day point prevalence abstinence (PPA) at 6-week follow-up was 31% (5/16), and the 30-day PPA was 19% (3/16). CONCLUSIONS: Results demonstrate promising engagement with Actify! and potential for impact on theory-based change processes and cessation outcomes. Preliminary quit rates compare favorably to previous trials of smoking cessation apps for the general population (ie, short-term, self-reported 30-day quit rates in the 8% to 18% range) and a previous trial of face-to-face BAT-D for depressed smokers (ie, CO-confirmed, 7-day PPA rate of 17% at end of treatment).

Comparing Treatment Acceptability and 12-Month Cessation Rates in Response to Web-Based Smoking Interventions Among Smokers Who Do and Do Not Screen Positive for Affective Disorders: Secondary Analysis.

BACKGROUND: Web-based cessation programs are now common for intervening with smokers. However, it remains unclear how acceptable or effective these interventions are among people with affective disorders and symptoms (ADS; eg, depression and anxiety). Research examining this is extremely limited, with mixed results on cessation rates. Additional large studies are needed to more fully understand whether Web-based interventions are similarly used and equally effective among people with and without affective disorder symptomology. If not, more targeted Web-based interventions may be required. OBJECTIVE: The goal of the research was to compare Web-based treatment acceptability (defined by satisfaction and use) and 12-month cessation outcomes between smokers with and without ADS. METHODS: Participants (N=2512) were adult smokers enrolled in a randomized, comparative effectiveness trial of two Web-based smoking interventions designed for the general population of smokers. At baseline, participants reported demographic and smoking characteristics and completed measures assessing ADS. Participants were then classified into subgroups based on their self-reported ADS-either into a no ADS group or into six nonmutually exclusive subgroups: depression, posttraumatic stress disorder (PTSD), panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), and more than one ADS. Surveys at 12 months postrandomization included subjective ratings of treatment acceptability and self-reported smoking cessation. Treatment use (ie, number of log-ins and total duration of exposure) was assessed via automated records. RESULTS: Relative to the no ADS group, all six ADS subgroups reported significantly greater satisfaction with their assigned Web treatment program, but they spent less time logged in than those with no ADS. For number of log-ins, a treatment arm by ADS group interaction was observed across all ADS subgroups except GAD, suggesting that relative to the no ADS group, they logged in less to one website but not the other. At the 12-month follow-up, abstinence rates in the no ADS group (153/520, 29.42%) were significantly higher than for participants who screened positive for depression (306/1267, 24.15%; P=.03), PTSD (294/1215, 24.19%; P=.03), PD (229/1003, 23.83%; P=.009), and two or more ADS (323/1332, 24.25%; P=.03). Post hoc analyses suggest the lower quit rates may be associated with differences in baseline nicotine dependence and levels of commitment to resist smoking in difficult situations. Website use did not explain the differential abstinence rates. CONCLUSIONS: Despite reporting higher levels of treatment satisfaction, most smokers with ADS used their assigned intervention less often and had lower quit rates than smokers with no ADS at treatment onset. The results support the need for developing more targeted interventions for smokers with ADS. TRIAL REGISTRATION: Clinical Trials.gov NCT01812278; https://clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/78L9cNdG4).

Smokers with bipolar disorder, other affective disorders, and no mental health conditions: Comparison of baseline characteristics and success at quitting in a large 12-month behavioral intervention randomized trial.

BACKGROUND: The extent to which smokers with bipolar disorder (BD) differ from other smokers on cessation-related characteristics and outcomes is unknown and could improve knowledge of treatment needs for this group. These analyses compared smokers with BD versus smokers with other affective disorders (ADs; anxiety and unipolar depression) and smokers with no mental health conditions (MHCs). METHOD: Participants (n = 2570) were a subsample of those enrolled in a smoking cessation trial comparing two web-delivered intervention approaches: acceptance and commitment therapy (ACT) and cognitive behavioral therapy. Those included in this analysis self-reported having BD (n = 221), other ADs (n = 783) or no major MHCs (n = 1566). Surveys assessed baseline characteristics and self-reported abstinence at 3, 6, and 12-months post-randomization. Treatment utilization was tracked via page views. RESULTS: Smokers with BD were distinct from both AD and no MHC smokers on the majority of baseline characteristics. At 12-months, quit rates were lower for smokers with BD (20%) than no MHCs (29%; p = 0.01), but no different than other ADs (20%; p = .467). Interactions between treatment assignment and diagnostic group were non-significant for cessation outcome. The number of logins was higher for smokers with BD than AD in the ACT arm only (p = .001), but this finding was not replicated across other utilization indicators. CONCLUSIONS: Smokers with BD and other ADs had similar long-term quit rates despite numerous differences in baseline characteristics. Despite being lower than for smokers without MHCs, long-term quit rates from web-based treatment are promising for smokers with BD as well as other ADs.

Participant Recruitment and Retention in Remote eHealth Intervention Trials: Methods and Lessons Learned From a Large Randomized Controlled Trial of Two Web-Based Smoking Interventions.

BACKGROUND: Despite 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. OBJECTIVE: To 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. METHODS: To 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. RESULTS: We 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. CONCLUSIONS: Continuous 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 REGISTRATION: ClinicalTrials.gov NCT01812278; https://clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/71gy5GLvO).

Trajectories of 12-Month Usage Patterns for Two Smoking Cessation Websites: Exploring How Users Engage Over Time.

BACKGROUND: Little is known about how individuals engage with electronic health (eHealth) interventions over time and whether this engagement predicts health outcomes. OBJECTIVE: The objectives of this study, by using the example of a specific type of eHealth intervention (ie, websites for smoking cessation), were to determine (1) distinct groups of log-in trajectories over a 12-month period, (2) their association with smoking cessation, and (3) baseline user characteristics that predict trajectory group membership. METHODS: We conducted a functional clustering analysis of 365 consecutive days of log-in data from both arms of a large (N=2637) randomized trial of 2 website interventions for smoking cessation (WebQuit and Smokefree), with a primary outcome of 30-day point prevalence smoking abstinence at 12 months. We conducted analyses for each website separately. RESULTS: A total of 3 distinct trajectory groups emerged for each website. For WebQuit, participants were clustered into 3 groups: 1-week users (682/1240, 55.00% of the sample), 5-week users (399/1240, 32.18%), and 52-week users (159/1240, 12.82%). Compared with the 1-week users, the 5- and 52-week users had 57% higher odds (odds ratio [OR] 1.57, 95% CI 1.13-2.17; P=.007) and 124% higher odds (OR 2.24, 95% CI 1.45-3.43; P<.001), respectively, of being abstinent at 12 months. Smokefree users were clustered into 3 groups: 1-week users (645/1309, 49.27% of the sample), 4-week users (395/1309, 30.18%), and 5-week users (269/1309, 20.55%). Compared with the 1-week users, 5-week users (but not 4-week users; P=.99) had 48% higher odds (OR 1.48, 95% CI 1.05-2.07; P=.02) of being abstinent at 12 months. In general, the WebQuit intervention had a greater number of weekly log-ins within each of the 3 trajectory groups as compared with those of the Smokefree intervention. Baseline characteristics associated with trajectory group membership varied between websites. CONCLUSIONS: Patterns of 1-, 4-, and 5-week usage of websites may be common for how people engage in eHealth interventions. The 5-week usage of either website, and 52-week usage only of WebQuit, predicted a higher odds of quitting smoking. Strategies to increase eHealth intervention engagement for 4 more weeks (ie, from 1 week to 5 weeks) could be highly cost effective. TRIAL REGISTRATION: ClinicalTrials.gov NCT01812278; https://www.clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/6yPO2OIKR).

Cigarette craving and stressful social interactions: The roles of state and trait social anxiety and smoking to cope.

BACKGROUND: Previous research indicates that social anxiety (SA) is a risk factor for the maintenance and relapse of smoking behaviors. However, little is known about the mechanisms underlying this relationship. The current study tested the effects of state and trait levels of SA as well as smoking to cope with symptoms of SA on craving during a social stressor task in abstinent conditions. METHODS: Participants (n = 60) were daily smokers, aged 18-30. Participants attended two sessions: a baseline session and a second session, wherein they engaged in a social stressor task while deprived from nicotine for 24 h. Subjective ratings of cigarette craving and state levels of SA were assessed six times throughout the task. Data were analyzed via multilevel modeling. RESULTS: Both trait SA and some forms of smoking to cope with symptoms of SA were more likely to predict increased craving during times of high, relative to low, social stress. Further, individuals with higher state SA, greater smoking to cope behaviors, and those who experience greater relief of social distress by smoking experienced greater craving throughout the task. These effects remained after controlling for nicotine dependence, withdrawal symptoms, depression, and other symptoms of anxiety and stress. Smoking to cope with symptoms of SA did not moderate the relationship between state SA and craving. CONCLUSIONS: Smokers high in SA (state and trait) and smoking to cope with symptoms of SA may be at risk for continued smoking and relapse because of the intensity of cravings they experience during stressful social situations.

"I Smoke Like This to Suppress These Issues That Are Flaws of My Character": Challenges and Facilitators of Cessation Among Smokers With Bipolar Disorder.

OBJECTIVE: Smokers with bipolar disorder (BD) have low rates of successful quitting, yet no prior studies have evaluated the process of quitting among these smokers in the context of a current quit attempt. To facilitate development of more effective interventions, we conducted a qualitative exploration of challenges and facilitators of quitting in an intervention study for smokers with BD. METHODS: Participants were adult daily smokers with BD (n = 10) who completed a 10-week smoking cessation intervention consisting of Acceptance and Commitment Therapy (ACT) and nicotine patch. We administered semistructured interviews focused on the quitting process at the end of treatment and used inductive content analysis to extract themes. RESULTS: Emergent themes representing challenges of quitting included social impediments, lack of awareness, avoidance, maladaptive beliefs, ambivalence, benefits of smoking, and difficulties with nicotine replacement. Themes representing change facilitators included positive treatment effects (ACT-specific, nonspecific, and nicotine patch-related), coping behaviors, reasons to quit, changes in self-perception, and social benefits. CONCLUSIONS: Results suggest a need for assistance with obtaining social support and handling social impediments, interrupting the automaticity of smoking, expanding the behavioral repertoire to handle aversive internal states that tend to be avoided by smoking, preventing maladaptive beliefs from interfering with quitting, taking meaningful action toward change while experiencing ambivalence, either replacing the benefits of smoking or accepting their loss, and troubleshooting difficulties with nicotine replacement. Findings regarding facilitators of quitting supported previous quantitative findings that the ACT intervention impacted theory-based targets and highlighted the importance of the counseling relationship.

Improving quit rates of web-delivered interventions for smoking cessation: full-scale randomized trial of WebQuit.org versus Smokefree.gov.

BACKGROUND AND AIMS: Millions of people world-wide use websites to help them quit smoking, but effectiveness trials have an average 34% follow-up data retention rate and an average 9% quit rate. We compared the quit rates of a website using a new behavioral approach called Acceptance and Commitment Therapy (ACT; WebQuit.org) with the current standard of the National Cancer Institute's (NCI) Smokefree.gov website. DESIGN: A two-arm stratified double-blind individually randomized trial (n = 1319 for WebQuit; n = 1318 for Smokefree.gov) with 12-month follow-up. SETTING: United States. PARTICIPANTS: Adults (n = 2637) who currently smoked at least five cigarettes per day were recruited from March 2014 to August 2015. At baseline, participants were mean [standard deviation (SD)] age 46.2 years (13.4), 79% women and 73% white. INTERVENTIONS: WebQuit.org website (experimental) provided ACT for smoking cessation; Smokefree.gov website (comparison) followed US Clinical Practice Guidelines for smoking cessation. MEASUREMENTS: The primary outcome was self-reported 30-day point prevalence abstinence at 12 months. FINDINGS: The 12-month follow-up data retention rate was 88% (2309 of 2637). The 30-day point prevalence abstinence rates at the 12-month follow-up were 24% (278 of 1141) for WebQuit.org and 26% (305 of 1168) for Smokefree.gov [odds ratio (OR) = 0.91; 95% confidence interval (CI) = 0.76, 1.10; P = 0.334] in the a priori complete case analysis. Abstinence rates were 21% (278 of 1319) for WebQuit.org and 23% (305 of 1318) for Smokefree.gov (OR = 0.89 (0.74, 1.07; P = 0.200) when missing cases were imputed as smokers. The Bayes factor comparing the primary abstinence outcome was 0.17, indicating 'substantial' evidence of no difference between groups. CONCLUSIONS: WebQuit.org and Smokefree.gov had similar 30-day point prevalence abstinence rates at 12 months that were descriptively higher than those of prior published website-delivered interventions and telephone counselor-delivered interventions.

Differential prevalence of established risk factors for poor cessation outcomes among smokers by level of social anxiety.

BACKGROUND AND OBJECTIVES: Despite clear associations between social anxiety (SA), high prevalence of smoking, and cessation failure, little is known about factors contributing to these relationships. Moreover, the extent to which smokers with moderate SA represent an at-risk group of smokers is also unknown. This study examined the extent to which established risk factors for poor cessation (eg, sociodemographic, smoking history, mental health comorbidity) are prevalent among smokers with low, moderate, and high levels of SA. METHODS: Participants (N = 2,637) were adult smokers from a web-based smoking cessation trial. Nineteen characteristics considered risk factors for poor cessation outcomes were assessed at baseline. Those associated with social anxiety were subsequently compared by SA level. RESULTS: Regression models indicated that 10/19 risk factors were associated with SA. Compared to smokers with low SA, those with moderate and high SA endorsed 4/10 and 10/10 risk factors as more prevalent or severe, respectively. Compared to smokers with low SA, High SA was associated with greater sociodemographic risk factors, while both moderate and high SA was associated with more severe mental health symptoms. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Smokers with moderate and high levels of SA endorse more risk factors for poor cessation outcomes than those with low levels of SA, particularly mental health symptoms. These factors may help explain the differential smoking outcomes of socially anxious smokers. Results suggest that smokers with both moderate and high levels of SA would likely benefit from cessation interventions that address and consider these risk factors. (Am J Addict 2017;26:176-182).

Relationships Between Social Anxiety and Smoking-Specific Experiential Avoidance.

OBJECTIVES: Although social anxiety is associated with higher prevalence of smoking and lower cessation rates, little is known about the underlying mechanisms of these relationships. Research suggests that socially anxious smokers have higher levels of smoking-specific experiential avoidance and are inclined to smoke to avoid internal smoking cues. However, it is unknown which types of internal smoking cues they avoid. Thus, this study aimed to address this gap in the literature. METHODS: Participants (N = 450) were adult smokers from a group-based trial for smoking cessation. Bivariate correlations and hierarchical linear regression models examined relationships between baseline levels of social anxiety and acceptance of internal smoking cues-physical sensations, emotions, and cognitions. RESULTS: Social anxiety was associated with lower levels of acceptance of thoughts, sensations, and emotions that cue smoking. After controlling for levels of nicotine dependence, depression, generalized anxiety, and posttraumatic stress disorder, social anxiety still explained unique variability in overall acceptance of internal smoking cues and in acceptance of physical sensations and emotions that serve as smoking cues. Social anxiety no longer explained unique variability in acceptance of thoughts that trigger smoking. CONCLUSIONS: Smokers with high levels of social anxiety are less accepting of internal smoking cues. For physical and emotional cues, this effect was independent of level of dependence and mental health comorbidity. Results help explain why smokers with social anxiety are less likely to quit and can inform the development of targeted cessation treatments for smokers with social anxiety.