Changes over time in reasons for quitting vaping among treatment-seeking young people from 2019 to 2022.

Objectives: The landscape of availability, policies, and norms around e-cigarette use and cessation has changed rapidly in the last few years. There is also high interest in quitting vaping among teens and young adults. Understanding the motivation of those who want to quit vaping is important for effective intervention development. This analysis compares user-submitted reasons for quitting (RFQ) vaping from 2022 to a previous analysis from 2019 to determine whether motivations have shifted among young people. Methods: We reviewed 2000 RFQ submissions from users who enrolled in a vaping cessation text message program in 2022. Each response was coded by ≥ 2 researchers and categorized into one of 16 themes. Findings were compared to the 2019 analysis using item-wise comparisons. Results: The most frequent RFQ in 2022 were health (56.1%), social influence (15.8%), and other (11.7%). In comparison to 2019, health remained the top reason, but the rank order of all other reasons shifted. Theme prevalence changed significantly, with cost decreasing and health increasing. Among health-related sub-categories, current and mental health increased compared to 2019 submissions. Discussion: RFQ among young people shifted between 2019 and 2022. We observed greater concern about current and mental health, possibly from experiencing negative health impacts from vaping or from increased awareness of these impacts. The lower prevalence of cost may reflect the widespread availability of cheaper e-cigarettes. RFQ likely change rapidly with the fluctuating e-cigarette landscape and should be considered in cessation interventions, promotional campaigns, and policy.

Treatment-seeking young people enrolled in a United States vaping cessation intervention trial report high frequency of use and nicotine dependence.

Objective: This study examines characteristics of participants enrolled in a vaping cessation intervention trial and study generalizability of the treatment-seeking sample to the broader population of young people interested in quitting vaping to evaluate dissemination of an evidence-based treatment program. Methods: Data was obtained from 697 treatment-seeking participants (aged 13-24 years) from a vaping cessation intervention trial conducted between February and March 2023 with This is Quitting and 665 participants who expressed intent to quit vaping in the Truth Longitudinal Cohort, a nationally representative longitudinal study of United States youth and young adults (aged 15-24 years), collected October 2022 to February 2023. Comparisons were made using two-sample Pearson Chi-square tests and t-tests. Results: Treatment-seeking young people were younger, less racially diverse, more diverse in sexual orientation, and reported higher psychological distress, frequency of e-cigarette use, and nicotine dependence, relative to the nationally representative sample of young people expressing intentions to quit vaping. Conclusions: Participants enrolled in treatment reported higher levels of dependence and use frequency than the broader population, suggesting that many young e-cigarette users with lower dependence who want to quit might not be reached by current treatment dissemination efforts. The implication of these findings is that communications for vaping cessation programs may need to be adjusted to have broader appeal among young people.

Effect of Messaging Content on Engagement With a Short Messaging Service for Perioperative Smoking Cessation.

INTRODUCTION: We determined whether a tobacco cessation intervention targeting brief perioperative abstinence ("quit for a bit") increased engagement of surgical patients with treatment compared with an intervention targeting long-term postoperative abstinence ("quit for good"). AIMS AND METHODS: Surgical patients who smoke were stratified according to intended duration of postoperative abstinence, and then randomized within strata to receive either a "quit for a bit" or a "quit for good" intervention. Both employed initial brief counseling and short message service (SMS) to deliver treatment up to 30 days after surgery. The primary outcome of treatment engagement was defined as the rate at which subjects actively responded to system requests delivered via SMS. RESULTS: The engagement index did not differ between intervention groups (median [25th, 75th] of 23.7% [8.8, 46.0] for "quit for a bit" group (n = 48) and 22.2% [4.8, 46.0] for "quit for good" group (n = 50), p = .74), nor did the proportion of patients continuing SMS use after study completion (33% and 28%, respectively). Exploratory abstinence outcomes on the morning of surgery and 7 and 30 days after surgery did not differ between groups. Program satisfaction was high in both groups and did not differ. There was no significant interaction between intended abstinence duration and any outcome, ie, alignment of intent with intervention did not affect engagement. CONCLUSIONS: Tobacco cessation treatment delivered via SMS was well accepted by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. IMPLICATIONS: Treatment of surgical patients for tobacco use is efficacious and reduces postoperative complications. However, implementation in clinical practice has proved challenging, and new methods of engaging these patients in cessation treatment are needed. We found that tobacco use treatment delivered via SMS was feasible and well utilized by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. CLINICAL TRIAL NUMBER: NCT03839043. Registry URL: https://clinicaltrials.gov/ct2/show/NCT03839043.

Tailored text message and web intervention for smoking cessation in U.S. socioeconomically-disadvantaged young adults: A randomized controlled trial.

The prevalence of cigarette smoking in young adults is higher among those with socioeconomic disadvantage than those without. Low treatment-seeking among young adult smokers is compounded by few efficacious smoking cessation interventions for this group, particularly socioeconomically-disadvantaged young adults (SDYA) who smoke cigarettes. The goal of this study was to test a tailored smoking-cessation intervention for SDYA. 343 SDYA aged 18-30 living in the U.S. (85% female) who smoke cigarettes with access to a smartphone and interest in quitting smoking in the next six months were recruited online in Spring 2020 and randomized to referral to online quit resources (usual care control; n = 171) or a 12-week tailored text message smoking-cessation program with a companion web-based intervention (n = 172). Intent to treat analyses examined associations between study condition, self-reported 30-day point prevalence abstinence (PPA), and confidence to quit smoking at 12 weeks, controlling for potential confounders. Intervention group participants had greater self-reported 30-day PPA at 12-weeks than controls (adjusted relative risk 3.93, 95% CI 2.14-7.24). Among those who continued smoking, the intervention increased confidence to quit (0.81 points, 95% confidence interval 0.08-1.53). Weekly engagement in the intervention predicted greater cessation. A tailored text message intervention for SDYA increased smoking abstinence and confidence to quit at the end-of-treatment. Findings may have been influenced by recruitment at the start of the COVID pandemic but suggest that text messaging is an acceptable and efficacious cessation strategy for SDYA smokers. Future studies should examine the impact on longer-term smoking-cessation and importance of intervention tailoring for SDYA.

E-cigarette and combusted tobacco abstinence among young adults: Secondary analyses from a U.S.-based randomized controlled trial of vaping cessation.

OBJECTIVE: To examine patterns of abstinence from e-cigarettes, combusted tobacco products (CTPs), both, or neither among young adults enrolled in a U.S.-based randomized trial of a text message vaping cessation intervention. METHODS: At baseline, 1829 young adult e-cigarette users were categorized as Exclusive E-cigarette Users (no past 30-day CTP use; n = 1036, 56.6%) or Dual Users (past 30-day CTP use; n = 793, 43.4%). Four groups were defined at 7-months: 1) Dual Abstinent, 2) Exclusive Vaping, 3) Exclusive CTP Use, and 4) Dual Users. The proportion of participants who were Dual Abstinent was the outcome of interest. RESULTS: At follow-up, 22.1% (95% CI: 20.3, 24.1) of participants were Dual Abstinent, 44.8% (95% CI: 42.5, 47.1) reported Exclusive Vaping, 6.3% (95% CI: 5.2, 7.5) reported Exclusive CTP Use, and 26.8% (95% CI: 24.8, 28.9) were Dual Users. A higher proportion of participants randomized to Intervention were Dual Abstinent (25.9%, 95% CI 23.1, 28.9) compared to Control (18.5%, 95% CI 16.0, 21.1; p = .0002). Analyses of treatment effects on dual abstinence by baseline tobacco product use favored Intervention over Control among both Exclusive E-cigarette Users (p = .019) and Dual Users (p = .0014). CONCLUSION: A text message vaping cessation intervention was effective in promoting dual abstinence from e-cigarettes and CTPs among young adults. The advantage of treatment over control was equivalent for Exclusive E-cigarette Users and Dual Users. Rates of dual abstinence were higher among exclusive vapers than dual users, signaling the need for more research to optimize cessation programs for poly-tobacco users.

Effectiveness of an optimized text message and Internet intervention for smoking cessation: A randomized controlled trial.

AIMS: To evaluate the effectiveness of a combined internet and text message intervention for smoking cessation compared with an internet intervention alone. The text message intervention was optimized for engagement in an earlier multiphase optimization (MOST) screening phase. DESIGN: A parallel, two-group, individually randomized clinical trial (RCT) was conducted in a MOST confirming phase. Recruitment spanned December 2018 to March 2019. Follow-up was conducted at 3 and 9 months, beginning March 2019 and ending January 2020. SETTING: United States: a digital study conducted among new registrants on a free tobacco cessation website. PARTICIPANTS: Eligible individuals were 618 adult current smokers in the United States, age 18 years or older who signed up for text messages during website registration (67.2% female, 70.4% white). INTERVENTIONS: The treatment arm (WEB+TXT; n = 311) received access to the website and text messaging. The control arm (WEB; n = 307) received access to the website alone. MEASUREMENTS: The primary outcome was self-reported 30-day point prevalence abstinence (ppa) at 9 months post-randomization analyzed under intent to treat (ITT), counting non-responders as smoking. Secondary outcomes included 3-month measures of 30-day ppa, intervention engagement and intervention satisfaction. FINDINGS: Abstinence rates at 9 months were 23.1% among WEB+TXT and 23.2% among WEB (OR = 1.00, 95% CI = 0.69-1.45; P = 0.99). WEB+TXT increased engagement with 5 of 6 interactive features (standardized mean difference (SMD) = 0.26-0.47, all P < 0.001) and repeat website visits (48.7% vs 38.9%, SMD = 0.14, P = 0.02). Satisfaction metrics favored WEB+TXT (satisfied: 96.3% vs 90.5%, SMD = 0.17, P = 0.008; recommend to friend: 95.9% vs 90.1%, SMD = 0.16, P = 0.028). CONCLUSIONS: A randomized controlled trial found no evidence that a combined internet and text message intervention for smoking cessation compared with an internet intervention alone increased 9-month abstinence rates among adult current smokers in the United States, despite evidence of higher levels of intervention engagement and satisfaction at 3 months.

Delivery of smoking cessation treatment via live chat: An analysis of client-centered coaching skills and behavior change techniques.

OBJECTIVE: This qualitative study explored whether evidence-based tobacco cessation treatment components can be deployed via web-based live chat coaching. METHODS: N = 100 randomly selected chats were coded. Researchers used a structured coding guide to note the presence of 3 Motivational Interviewing (MI) skills and 61 behavior change techniques (BCTs). RESULTS: MI skills were observed in 86% of chats: 31 chats incorporated one skill, 31 incorporated two, and 24 incorporated all three. Open-ended questions were most common (76%), followed by affirmations (47%) and reflective listening statements (38%). BCTs were observed in 100% of chats: 21% involved one-five BCTs, 69% involved six-10 BCTs, and 10% involved 11 or more BCTs. Mean number of BCTs per chat was 7.25 (SD=2.5; range 2-17). The most common BCTs were Social Support (99%), Reward/Threat (95%), Natural Consequences (82%), Regulation (82%), Goals/Planning (64%), and Self Belief (42%). CONCLUSIONS: Tobacco cessation coaching using MI skills and evidence-based BCTs can be delivered via live chat. This synchronous modality allows the delivery of an intervention tailored to the user's motivations and goals. PRACTICE IMPLICATIONS: Web-based live chat can broaden the reach of tobacco treatment specialists to deploy evidence-based counseling skills and behavior change techniques in personalized, accessible coaching.

Effectiveness of a Vaping Cessation Text Message Program Among Young Adult e-Cigarette Users: A Randomized Clinical Trial.

Importance: e-Cigarettes are the most commonly used tobacco product among young adults (YAs). Despite the harms of nicotine exposure among YAs, there are few, if any, empirically tested vaping cessation interventions available. Objective: To determine the effectiveness of a text message program for vaping cessation among YAs vs assessment-only control. Design, Setting, and Participants: A parallel, 2-group, double-blind, individually randomized clinical trial was conducted from December 2019 to November 2020 among YA e-cigarette users. Eligible individuals were US residents aged 18 to 24 years who owned a mobile phone with an active text message plan, reported past 30-day e-cigarette use, and were interested in quitting in the next 30 days. Participants were recruited via social media ads, the intervention was delivered via text message, and assessments were completed via website or mobile phone. Follow-up was conducted at 1 and 7 months postrandomization; follow-up data collection began January 2020 and ended in November 2020. The study was prespecified in the trial protocol. Interventions: All participants received monthly assessments via text message about e-cigarette use. The assessment-only control arm (n = 1284) received no additional intervention. The active intervention arm (n = 1304) also received This is Quitting, a fully automated text message program for vaping cessation that delivers social support and cognitive and behavioral coping skills training. Main Outcomes and Measures: The primary outcome was self-reported 30-day point prevalence abstinence (ppa) at 7 months analyzed under intention-to-treat analysis, which counted nonresponders as vaping. Secondary outcomes were 7-day ppa under intention-to-treat analysis and retention weighted complete case analysis of 30-day and 7-day ppa. Results: Of the 2588 YA e-cigarette users included in the trial, the mean (SD) age was 20.4 (1.7) years, 1253 (48.4%) were male, 2159 (83.4%) were White, 275 (10.6%) were Hispanic, and 493 (19.0%) were a sexual minority. Most participants (n = 2129; 82.3%) vaped within 30 minutes of waking. The 7-month follow-up rate was 76.0% (n = 1967), with no differential attrition. Abstinence rates were 24.1% (95% CI, 21.8%-26.5%) among intervention participants and 18.6% (95% CI, 16.7%-20.8%) among control participants (odds ratio, 1.39; 95% CI, 1.15-1.68; P < .001). No baseline variables moderated the treatment-outcome relationship, including nicotine dependence. Conclusions and Relevance: Results of this randomized clinical trial demonstrated that a tailored and interactive text message intervention was effective in promoting vaping cessation among YAs. These results establish a benchmark of intervention effectiveness. Trial Registration: ClinicalTrials.gov Identifier: NCT04251273.

"It's really addictive and I'm trapped:" A qualitative analysis of the reasons for quitting vaping among treatment-seeking young people.

BACKGROUND: Debate continues over how e-cigarettes have impacted the health of young people, and what regulatory policies should be enacted. The debate has appropriately been informed by quantitative studies, often focused on initiation, prevalence, and product transition among the general population and demographic segments. Factors driving cessation and subjective experiences that motivate young users to quit have been largely absent from the debate. This qualitative study highlights the range of motivating experiences among a population of treatment-seeking young e-cigarette users. METHODS: Three researchers coded reasons for quitting provided by a sample of n = 1000 youth (13-17) and n = 1000 young adults (18-24) enrolled in a text message cessation program. Data spanned January 18 - February 22, 2019. Codes were adapted from previous literature. RESULTS: The most common reasons were health (50.9%; "I want my lungs back"), financial cost (21.7%; "I don't have enough money to feed my addiction"), freedom from addiction (16.0%; "i hate juuling. it's taking over my life"), and social influence (10.1%; "it's affecting my friendships"). Selected quotes highlight a broad range of additional ways in which e-cigarette use negatively impacted young people, including decreased academic performance and mental health. CONCLUSIONS: Young people trying to quit e-cigarettes are motivated by a diversity of reasons including health, financial, social, and academic. The range of impacts should be considered in discussions of policies intended to protect young people, and incorporated into cessation programs designed to serve them.

Correction: Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment.

[This corrects the article DOI: 10.2196/17734.].

Effectiveness of a Quit Vaping Text Message Program in Promoting Abstinence Among Young Adult E-Cigarette Users: Protocol for a Randomized Controlled Trial.

BACKGROUND: Millions of young adults currently vape electronic cigarettes (e-cigarettes), yet little research on vaping cessation interventions exists. Text messaging is a promising, scalable intervention strategy for delivering vaping cessation treatment. OBJECTIVE: This study evaluates the effectiveness of a text message quit vaping program (This is Quitting) in promoting abstinence from e-cigarettes among young adults; examines changes in self-efficacy, perceived social norms, and social support for quitting as hypothesized mediators of effectiveness; and examines if treatment effectiveness is moderated by gender, race, ethnicity, or sexual minority status. METHODS: Overall, 2600 young adult (aged 18-24 years) e-cigarette users in the United States will be recruited via web advertisements to participate in the study. Participants will be randomized to This is Quitting or an assessment-only control condition. The primary outcome measure is 30-day vaping abstinence at 7 months post enrollment. RESULTS: Study recruitment began on December 18, 2019, and is projected to be completed by spring 2020. The final 7-month follow-up is anticipated to be completed by fall/winter 2020. Because this is the first-ever evaluation of a quit vaping program, we were unable to draw on existing literature to determine the appropriate sample size. Therefore, we examined abstinence rates among an initial pilot sample of 269 participants (This is Quitting: n=148 and control: n=121) who completed the 1-month follow-up to determine the final sample size. The 1-month response rate was 79.2% (213/269), with no difference between arms. Using intention-to-treat analyses that counted nonresponders as still vaping, 30-day abstinence rates were 16.2% (24/148) among those randomized to This is Quitting and 8.3% (10/121) among those randomized to control. A treatment difference of 16% vs 8% is detectable with 80% power at 2-sided alpha=.05 with 260/group (520 total). To detect treatment differences of this magnitude in a 20% subsample (eg, Hispanic or sexual minority young adult e-cigarette users), we will enroll 1300/group (2600 total). CONCLUSIONS: The scientific, clinical, and public health communities are desperate for cessation resources to address vaping among young people. This study is the first-ever comparative effectiveness trial of an intervention to help young people quit vaping. It focuses on evaluating the effectiveness of a theory-grounded, empirically informed text message intervention among young adults. The study is fully powered to examine potentially important subgroup differences among young people who are more vulnerable to e-cigarette use. Although potentially more challenging from a research ethics and pragmatic standpoint, evaluating quit vaping intervention approaches in teens is an important area for future research. Data from this trial will establish a benchmark of effectiveness for other vaping cessation programs and begin to create a body of evidence focused on how best to help young people break free from e-cigarettes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04251273; https://clinicaltrials.gov/ct2/show/NCT04251273. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18327.

Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment.

BACKGROUND: Smoking remains a leading cause of preventable death and illness. Internet interventions for smoking cessation have the potential to significantly impact public health, given their broad reach and proven effectiveness. Given the dose-response association between engagement and behavior change, identifying strategies to promote engagement is a priority across digital health interventions. Text messaging is a proven smoking cessation treatment modality and a powerful strategy to increase intervention engagement in other areas of health, but it has not been tested as an engagement strategy for a digital cessation intervention. OBJECTIVE: This study examined the impact of 4 experimental text message design factors on adult smokers' engagement with an internet smoking cessation program. METHODS: We conducted a 2×2×2×2 full factorial screening experiment wherein 864 participants were randomized to 1 of 16 experimental conditions after registering with a free internet smoking cessation program and enrolling in its automated text message program. Experimental factors were personalization (on/off), integration between the web and text message platforms (on/off), dynamic tailoring of intervention content based on user engagement (on/off), and message intensity (tapered vs abrupt drop-off). Primary outcomes were 3-month measures of engagement (ie, page views, time on site, and return visits to the website) as well as use of 6 interactive features of the internet program. All metrics were automatically tracked; there were no missing data. RESULTS: Main effects were detected for integration and dynamic tailoring. Integration significantly increased interactive feature use by participants, whereas dynamic tailoring increased the number of features used and page views. No main effects were found for message intensity or personalization alone, although several synergistic interactions with other experimental features were observed. Synergistic effects, when all experimental factors were active, resulted in the highest rates of interactive feature use and the greatest proportion of participants at high levels of engagement. Measured in terms of standardized mean differences (SMDs), effects on interactive feature use were highest for Build Support System (SMD 0.56; 95% CI 0.27 to 0.81), Choose Quit Smoking Aid (SMD 0.38; 95% CI 0.10 to 0.66), and Track Smoking Triggers (SMD 0.33; 95% CI 0.05 to 0.61). Among the engagement metrics, the largest effects were on overall feature utilization (SMD 0.33; 95% CI 0.06 to 0.59) and time on site (SMD 0.29; 95% CI 0.01 to 0.57). As no SMD >0.30 was observed for main effects on any outcome, results suggest that for some outcomes, the combined intervention was stronger than individual factors alone. CONCLUSIONS: This factorial experiment demonstrates the effectiveness of text messaging as a strategy to increase engagement with an internet smoking cessation intervention, resulting in greater overall intervention dose and greater exposure to the core components of tobacco dependence treatment that can promote abstinence. TRIAL REGISTRATION: ClinicalTrials.gov NCT02585206; https://clinicaltrials.gov/ct2/show/NCT02585206. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2015-010687.

Menthol cigarette smoking is associated with greater subjective reward, satisfaction, and "throat hit", but not greater behavioral economic demand.

AIMS: The cooling and minty flavor of menthol in cigarettes has been hypothesized to mask the harshness of inhaled cigarette smoke, contributing to menthol's appeal and subjective reinforcement and linking menthol use to smoking initiation, progression, nicotine dependence, and difficulty quitting. This study examined differences between menthol and non-menthol smokers on behavioral economic indices of reinforcing efficacy (i.e., demand) and subjective response to smoking (i.e., satisfaction, reward, "throat hit," aversion) and the association between measurements of reinforcement and subjective response. DESIGN: 600 current adult smokers were recruited from an online smoking cessation program. Following website enrollment, individuals completed a self-report measurement of subjective response to smoking (reward, satisfaction, aversion, "throat hit"), and a modified cigarette purchase task (CPT) to assess behavioral economic cigarette demand. FINDINGS: In bivariate and adjusted ANOVA models, menthol smokers reported greater subjective reward, satisfaction, and positive sensations in the throat ("throat hit") from smoking compared to non-menthol smokers; and those outcomes were also correlated with greater nicotine dependence and lower likelihood of a past-year quit attempt. Although cigarette demand was associated with smoking level, subjective smoking reward, and nicotine dependence, there were no differences in smoking demand between menthol vs. non-menthol smokers. CONCLUSIONS: The pleasurable aspects of menthol vs non-menthol smoking may be a mechanism linking it to greater nicotine dependence and difficulty quitting. A menthol ban could decrease population-level cigarette consumption by restricting smokers' access to a highly rewarding cigarette flavoring.

Mining User-Generated Content in an Online Smoking Cessation Community to Identify Smoking Status: A Machine Learning Approach.

Online smoking cessation communities help hundreds of thousands of smokers quit smoking and stay abstinent each year. Content shared by users of such communities may contain important information that could enable more effective and personally tailored cessation treatment recommendations. This study demonstrates a novel approach to determine individuals' smoking status by applying machine learning techniques to classify user-generated content in an online cessation community. Study data were from BecomeAnEX.org, a large, online smoking cessation community. We extracted three types of novel features from a post: domain-specific features, author-based features, and thread-based features. These features helped to improve the smoking status identification (quit vs. not) performance by 9.7% compared to using only text features of a post's content. In other words, knowledge from domain experts, data regarding the post author's patterns of online engagement, and other community member reactions to the post can help to determine the focal post author's smoking status, over and above the actual content of a focal post. We demonstrated that machine learning methods can be applied to user-generated data from online cessation communities to validly and reliably discern important user characteristics, which could aid decision support on intervention tailoring.

Treatment engagement mediates the links between symptoms of anxiety, depression, and alcohol use disorder with abstinence among smokers registered on an Internet cessation program.

Mental health problems like anxiety, depression, and substance use problems commonly co-occur with cigarette smoking and are linked to poor cessation outcomes. Although millions of smokers seek online quitting assistance each year, few studies have examined links between website utilization and cessation outcomes among smokers with mental health problems. This study recruited 600 smokers with anxiety, depression, and alcohol use disorders (AUDs) who were new users of a publicly available Internet cessation treatment. Among participants with 3-month outcome data (n = 247, 42%), structural equation models (SEM) examined the association of symptoms of anxiety/depression (combined) and AUD diagnosis on website engagement and 3-month quit rates, controlling for covariates. The 3-month 30-day abstinence rate among those who completed follow-up was 28%, but only 14% among smokers with an AUD and 24.7% among smokers with symptoms of anxiety/depression. SEM results showed that treatment engagement significantly mediated the effect of mental health problems on 3-month abstinence: those with symptoms of anxiety/depression or an AUD had lower quit rates overall, however engagement with the website had a buffering effect on 3-month cessation outcomes. Engagement with an evidence-based Internet cessation program may be particularly useful for smokers with mental health comorbidities in increasing the chances of cessation. Future work should examine what level of treatment engagement meaningfully impacts behavior change for smokers with mental health problems who access Internet cessation programs.

Inferring Smoking Status from User Generated Content in an Online Cessation Community.

Introduction: User generated content (UGC) is a valuable but underutilized source of information about individuals who participate in online cessation interventions. This study represents a first effort to passively detect smoking status among members of an online cessation program using UGC. Methods: Secondary data analysis was performed on data from 826 participants in a web-based smoking cessation randomized trial that included an online community. Domain experts from the online community reviewed each post and comment written by participants and attempted to infer the author's smoking status at the time it was written. Inferences from UGC were validated by comparison with self-reported 30-day point prevalence abstinence (PPA). Following validation, the impact of this method was evaluated across all individuals and time points in the study period. Results: Of the 826 participants in the analytic sample, 719 had written at least one post from which content inference was possible. Among participants for whom unambiguous smoking status was inferred during the 30 days preceding their 3-month follow-up survey, concordance with self-report was almost perfect (kappa = 0.94). Posts indicating abstinence tended to be written shortly after enrollment (median = 14 days). Conclusions: Passive inference of smoking status from UGC in online cessation communities is possible and highly reliable for smokers who actively produce content. These results lay the groundwork for further development of observational research tools and intervention innovations. Implications: A proof-of-concept methodology for inferring smoking status from user generated content in online cessation communities is presented and validated. Content inference of smoking status makes a key cessation variable available for use in observational designs. This method provides a powerful tool for researchers interested in online cessation interventions and establishes a foundation for larger scale application via machine learning.

Discussions of Alcohol Use in an Online Social Network for Smoking Cessation: Analysis of Topics, Sentiment, and Social Network Centrality.

BACKGROUND: Few Internet smoking cessation programs specifically address the impact of alcohol use during a quit attempt, despite its common role in relapse. This study used topic modeling to describe the most prevalent topics about alcohol in an online smoking cessation community, the prevalence of negative sentiment expressed about alcohol use in the context of a quit attempt (i.e., alcohol should be limited or avoided during a quit attempt) within topics, and the degree to which topics differed by user social connectivity within the network. METHODS: Data were analyzed from posts from the online community of a larger Internet cessation program, spanning January 1, 2012 to May 31, 2015 and included records of 814,258 online posts. Posts containing alcohol-related content (n = 7,199) were coded via supervised machine learning text classification to determine whether the post expressed negative sentiment about drinking in the context of a quit attempt. Correlated topic modeling (CTM) was used to identify a set of 10 topics of at least 1% prevalence based on the frequency of word occurrences among alcohol-related posts; the distribution of negative sentiment and user social network connectivity was examined across the most salient topics. RESULTS: Three salient topics (with prevalence ≥10%) emerged from the CTM, with distinct themes of (i) cravings and temptations; (ii) parallel between nicotine addiction and alcoholism; and (iii) celebratory discussions of quit milestones including "virtual" alcohol use and toasts. Most topics skewed toward nonnegative sentiment about alcohol. The prevalence of each topic differed by users' social connectivity in the network. CONCLUSIONS: Future work should examine whether outcomes in Internet interventions are improved by tailoring social network content to match user characteristics, topics, and network behavior.

Exposure to positive peer sentiment about nicotine replacement therapy in an online smoking cessation community is associated with NRT use.

BACKGROUND: Little is known about the influence of online peer interactions on health behavior change. This study examined the relationship between exposure to peer sentiment about nicotine replacement therapy (NRT) in an online social network for smoking cessation and NRT use. METHODS: Participants were 3297 current smokers who enrolled in an Internet smoking cessation program, participated in a randomized trial, and completed a 3-month follow-up. Half received free NRT as part of the trial. Automated text classification identified 27,038 posts about NRT that one or more participants were exposed to in the social network. Sentiment towards NRT was rated on Amazon Mechanical Turk. Participants' exposure to peer sentiment about NRT was determined by analysis of clickstream data. Modified Poisson regression examined self-reported use of NRT at 3-months as a function of exposure to NRT sentiment, controlling for study arm and post exposure. RESULTS: One in five participants (19.3%, n = 639) were exposed to any NRT-related posts (mean exposure = 6.5 ±â€¯14.7, mean sentiment = 5.4 ±â€¯0.8). The association between sentiment exposure and NRT use varied by receipt of free NRT. Greater exposure to positive NRT sentiment was associated with an increased likelihood of NRT use among participants who did not receive free NRT (adjusted rate ratio 1.22, 95% CI 1.01, 1.47; p = .043), whereas no such relationship was observed among participants who did receive free NRT (p = .48). CONCLUSIONS: Exposure to positive sentiment about NRT was associated with increased NRT use when smokers obtained it on their own. Highlighting user-generated content containing positive NRT sentiment may increase NRT use among treatment-seeking smokers.

Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial.

Background: Partial adherence in Internet smoking cessation interventions presents treatment and evaluation challenges. Increasing adherence may improve outcomes. Purpose: To present smoking outcomes from an Internet randomized trial of two strategies to encourage adherence to tobacco dependence treatment components: (i) a social network (SN) strategy to integrate smokers into an online community and (ii) free nicotine replacement therapy (NRT). In addition to intent-to-treat analyses, we used novel statistical methods to distinguish the impact of treatment assignment from treatment utilization. Methods: A total of 5,290 current smokers on a cessation website (WEB) were randomized to WEB, WEB + SN, WEB + NRT, or WEB + SN + NRT. The main outcome was 30-day point prevalence abstinence at 3 and 9 months post-randomization. Adherence measures included self-reported medication use (meds), and website metrics of skills training (sk) and community use (comm). Inverse Probability of Retention Weighting and Inverse Probability of Treatment Weighting jointly addressed dropout and treatment selection. Propensity weights were used to calculate Average Treatment effects on the Treated. Results: Treatment assignment analyses showed no effects on abstinence for either adherence strategy. Abstinence rates were 25.7%-32.2% among participants that used all three treatment components (sk+comm +meds).Treatment utilization analyses revealed that among such participants, sk+comm+meds yielded large percentage point increases in 3-month abstinence rates over sk alone across arms: WEB = 20.6 (95% CI = 10.8, 30.4), WEB + SN = 19.2 (95% CI = 11.1, 27.3), WEB + NRT = 13.1 (95% CI = 4.1, 22.0), and WEB + SN + NRT = 20.0 (95% CI = 12.2, 27.7). Conclusions: Novel propensity weighting approaches can serve as a model for establishing efficacy of Internet interventions and yield important insights about mechanisms. Clinical Trials.gov: NCT01544153.

An integrated digital/clinical approach to smoking cessation in lung cancer screening: study protocol for a randomized controlled trial.

BACKGROUND: Delivering effective tobacco dependence treatment that is feasible within lung cancer screening (LCS) programs is crucial for realizing the health benefits and cost savings of screening. Large-scale trials and systematic reviews have demonstrated that digital cessation interventions (i.e. web-based and text message) are effective, sustainable over the long-term, scalable, and cost-efficient. Use of digital technologies is commonplace among older adults, making this a feasible approach within LCS programs. Use of cessation treatment has been improved with models that proactively connect smokers to treatment rather than passive referrals. Proactive referral to cessation treatment has been advanced through healthcare systems changes such as modifying the electronic health record to automatically link smokers to treatment. METHODS: This study evaluates the impact of a proactive enrollment strategy that links LCS-eligible smokers with an evidence-based intervention comprised of a web-based (WEB) program and integrated text messaging (TXT) in a three-arm randomized trial with repeated measures at one, three, six, and 12 months post randomization. The primary outcome is biochemically confirmed abstinence at 12 months post randomization. We will randomize 1650 smokers who present for a clinical LCS to: (1) a usual care control condition (UC) which consists of Ask-Advise-Refer; (2) a digital (WEB + TXT) cessation intervention; or (3) a digital cessation intervention combined with tobacco treatment specialist (TTS) counseling (WEB + TXT + TTS). DISCUSSION: The scalability and sustainability of a digital intervention may represent the most cost-effective and feasible approach for LCS programs to proactively engage large numbers of smokers in effective cessation treatment. We will also evaluate the impact and cost-effectiveness of adding proven clinical intervention provided by a TTS. We expect that a combined digital/clinical intervention will yield higher quit rates than digital alone, but that it may not be as cost-effective or feasible for LCS programs to implement. This study is innovative in its use of interoperable, digital technologies to deliver a sustainable, scalable, high-impact cessation intervention and to facilitate its integration within clinical practice. It will add to the growing knowledge base about the overall effectiveness of digital interventions and their role in the healthcare delivery system. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03084835 . Registered on 9 March 2017.