Quit Date Research Articles

Efficacy of a conversational chatbot for cigarette smoking cessation: Protocol of the QuitBot full-scale randomized controlled trial

Globally, cigarette smoking results in over 8 million premature annual deaths. Addressing this issue requires high-impact, cost-effective population-level interventions for smoking cessation. Conversational chatbots offer a potential solution given the recent advancements in machine learning and large language models. Chatbots can deliver supportive, empathetic behaviors, personalized responses, and timely advice tailored to users' needs that is engaging through therapeutic conversations aimed at creating lasting social-emotional connections. Despite their promise, little is known about the efficacy and underlying mechanisms of chatbots for cigarette smoking cessation. We developed QuitBot, a quit smoking program of two to three-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing cessation medications, coping with triggers, maintaining abstinence, and recovering from relapse. QuitBot employs conversational interactions, powered by an expert-curated large language model, allowing users to ask questions and receive personalized guidance on quitting smoking. Here, we report the design and execution of a randomized clinical trial comparing QuitBot (n = 760) against Smokefree TXT (SFT) text messaging program (n = 760), with a 12-month follow-up period. Both interventions include 42-days of content on motivations to quit, skills to cope with triggers, and relapse prevention. The key distinction between QuitBot and SFT is the communication and engagement feature of QuitBot. This study aims to determine: whether QuitBot yields higher quit rates than SFT; and whether therapeutic alliance processes and engagement are mechanisms underlying cessation outcomes. Additionally, we will explore whether baseline factors including trust, social support, and demographics, moderate the efficacy of QuitBot.Trial Registration numberClinicalTrials.govNCT04308759

Factors influencing tobacco quitting: findings from National Tobacco-Quitline Services, Mumbai, India.

The Government of India established National Tobacco Quitline Services (NTQLS) to provide free and effective telephonic counselling to help people quit tobacco. The objective of the paper is to present the data of tobacco quitters who quit tobacco through NTQLS, Mumbai, in the years 2021-2022 and the factors that influenced tobacco quitting. This is a prospective study where individuals willing to quit tobacco utilised NTQLS. Effective counselling was provided and was followed up. Multiple logistic regression analysis was conducted. Tobacco quitting is the dependent variable while sociodemographic characteristics, tobacco consumption habits, previous quit attempts, alcohol consumption, other substance use and co-morbidity were independent variables. In the years 2021-2022, a total of 448,893 calls hit the system. Of these, 127,163 (28.3%) calls were attended. Of the attended calls, a quit date was set for 21,504 calls (16.9%); of these, 8,276 (38.5%) callers quit tobacco. Individuals with no previous quit attempts [OR: 1.48, 95% confidence interval (CI): 1.25-1.75], never consumed alcohol (OR: 1.37, 95%CI: 1.2-1.56), consumed tobacco within 6-30 minutes (OR: 1.29, 95% CI: 1.12-1.49) and 30-60 minutes after waking up (OR: 1.26, 95% CI: 1.05-1.51) had higher quitting rates. While, female callers (OR: 0.59, 95% CI: 0.35-0.99), private sector workers (OR: 0.70, 95% CI: 0.61-0.81), individuals consuming more than ten tobacco units/packets (OR: 0.70, 95% CI: 0.61-0.79), tobacco use more than 10 years (OR: 0.85, 95% CI: 0.73-0.97), expenditure of more than 5,000 rupees on tobacco (OR: 0.58, 95% CI: 0.44-0.77) and those with no known co-morbid conditions (OR: 0.8, 95% CI: 0.71-0.91) were less likely to quit tobacco. Reduced tobacco consumption will inadvertently reduce the non-communicable disease (NCD) burden and help in achieving the sustainable development goals related to tobacco control and NCD. Quitline plays an important role in tobacco control.

Sex differences in cigarette smoking following a mindfulness-based cessation randomized controlled trial

Some interventions for smoking cessation such as quit smoking aids show sex-specific effects on outcomes, but behavioral interventions such as mindfulness-based interventions (MBIs) for smoking cessation lack formal reporting of sex-intervention tests of interaction to date. To address this gap, we conducted a secondary analysis of a RCT dataset (N = 213), recruiting participants from California, to statistically test a sex-intervention interaction effect on complete 7-day point prevalence abstinence (PPA), proportion of days abstinent, and daily cigarettes smoked. Smoking was assessed using the timeline follow back method spanning the four weeks following a daily 14-day app-based intervention and a planned smoking quit date immediately following the intervention phase. All models adjusted for baseline nicotine dependence. The study groups had comparable sex proportions (MBI: 56 % female; control: 55 % female) and the ratio of outcome assessment completion by group was not dependent on sex. Adjusted analyses revealed a significant sex-intervention interaction effect for daily cigarettes smoked ([female coded 1]: two-way interaction effect IRR = 0.59, 95 % CI: 0.46–0.77, p < 0.0001; effect for female: IRR = 0.68, 95 % CI: 0.57–0.81, effect for male: IRR = 1.14, 95 % CI: 0.95–1.37), but not for complete 7-day PPA ([female coded 1] two-way interaction effect OR = 1.24, 95 % CI: 0.31–4.89, p = 0.76) or proportion of total days abstinent ([female coded 1] two-way interaction effect OR = 1.97, 95 % CI: 0.53–7.37, p = 0.31). Females, but not males, allocated to a daily app-based MBI with a quit plan and quit aid workbook smoked fewer cigarettes per day compared to females in the control group. Males, but not females, showed significantly less use of the MBI app compared to the control app.

Boosting Smoking Cessation Intervention Utilization in Chinese Healthcare Providers: A Randomized Controlled Trial of the 'WeChat WeQuit' Medical Education Program.

In China, standard smoking cessation practices are rarely used by healthcare service providers (HSPs). WeChat, a popular social media app, has been widely used in China. In this single-blind, randomized trial, undertaken in China with 8-week interventions and follow-up to 34 weeks, 1887 HSPs were randomly selected to the intervention (n=942) or control group (n=945) from Oct 2020 to Oct 2021. The intervention group received regular smoking cessation training program messages from the professional team for 8 weeks and followed for 34 weeks. The control group received thanks messages for 8 weeks, and follow-up to 34 weeks. Both groups received a hard copy of the manual after randomization. The primary outcome measure was the utilization rate of behavioral and pharmacotherapy interventions for smoking patients from 9 to 34 weeks. This trial is registered at ClinicalTrials.gov (number NCT03556774). HSPs in the intervention group demonstrated a better overall utilization rate of smoking cessation at 20-week follow-up compared to the control group (35.54% vs 31.41%, p=0.036). Additionally, both groups showed a significant increase in the adoption of various components of the 5A's model - including "Assess", "Assist: set a quit date", "Assist: recommend cessation program", "Assist: provide information", "Assist: recommend medication", and "Arrange" - at the 9-week follow-up relative to baseline. Notably, at the 20-week follow-up, the intervention group reported significantly enhanced utilization rates for all these components, except "Assist: set a quit date". The "Wechat Wequit" training program effectively enhanced smoking cessation intervention adoption among Chinese HSPs. 'WeChat WeQuit' training program was effective in increasing the provision of effective tobacco cessation interventions by Chinese-speaking HSPs to patients with cigarette smoking, which could provide valuable insights into bridging the gap between need and services for smoking cessation in China.

Associations between compliance with very low nicotine content (VLNC) cigarettes, abstinence self-efficacy, and quit outcomes in a pilot smoking cessation trial

BackgroundSwitching to Very Low Nicotine Content (VLNC) cigarettes reduces toxicant exposure and nicotine dependence, and may improve smoking cessation. However, non-compliance with VLNCs is often high, which may reduce their effectiveness. Here, we conducted secondary analyses of a pilot smoking cessation trial utilizing VLNCs to examine associations between pre-cessation VLNC compliance and changes in smoking rate, dependence, and abstinence self-efficacy, as well as quit outcomes. MethodsPeople who smoke daily (n=35) engaged in a 4-week pre-cessation intervention including VLNCs, transdermal nicotine patch, and behavioral counseling. After quit date, participants received 8 weeks of nicotine replacement therapy and 4 additional behavioral sessions, and were followed for 10 weeks to assess abstinence. Compliance with VLNCs was assessed biweekly during pre-cessation using timeline follow-back. Statistical analyses examined associations between VLNC compliance and a) changes in smoking rate, dependence and abstinence self-efficacy over the course of study cigarette use; and b) time to relapse, controlling for other smoking variables. ResultsGreater compliance during the second half of study cigarette use was associated with subsequent improvement in self-efficacy (p<.05). Increased self-efficacy and VLNC compliance both predicted lower likelihood of relapse. Nicotine dependence and cigarettes per day both decreased following study cigarette use, but were unrelated to compliance or relapse. ConclusionsCompliance with VLNCs prior to quitting increased abstinence self-efficacy and predicted better quit outcomes above and beyond baseline smoking characteristics. Although preliminary, these findings suggest that identifying strategies to promote exclusive use of VLNCs during a brief pre-cessation window may be beneficial.

Financial Incentives for Smoking Cessation Among Socioeconomically Disadvantaged Adults

Socioeconomically disadvantaged individuals (ie, those with low socioeconomic status [SES]) have difficulty quitting smoking and may benefit from incentive-based cessation interventions. To evaluate the impact of incentivizing smoking abstinence on smoking cessation among adults with low SES. This study used a 2-group randomized clinical trial design. Data collection occurred between January 30, 2017, and February 7, 2022. Participants included adults with low SES who were willing to undergo smoking cessation treatment. Data were analyzed from April 18, 2023, to April 19, 2024. Participants were randomized to usual care (UC) for smoking cessation (counseling plus pharmacotherapy) or UC plus abstinence-contingent financial incentives (UC plus FI). The primary outcome was biochemically verified 7-day point prevalence smoking abstinence (PPA) at 26 weeks after the quit date. Secondary outcomes included biochemically verified 7-day PPA at earlier follow-ups, 30-day PPA at 12 and 26 weeks, repeated 7-day PPA, and continuous abstinence. Multiple approaches were employed to handle missing outcomes at follow-up, including categorizing missing data as smoking (primary), complete case analysis, and multiple imputation. The 320 participants had a mean (SD) age of 48.9 (11.6) and were predominantly female (202 [63.1%]); 82 (25.6%) were Black, 15 (4.7%) were Hispanic, and 200 (62.5%) were White; and 146 (45.6%) participated during the COVID-19 pandemic. Overall, 161 were randomized to UC and 159 were randomized to UC plus FI. After covariate adjustment with missing data treated as smoking, assignment to UC plus FI was associated with a greater likelihood of 7-day PPA at the 4-week (adjusted odds ratio [AOR], 3.11 [95% CI, 1.81-5.34]), 8-week (AOR, 2.93 [95% CI, 1.62-5.31]), and 12-week (AOR, 3.18 [95% CI, 1.70-5.95]) follow-ups, but not at the 26-week follow-up (22 [13.8%] vs 14 [8.7%] abstinent; AOR, 1.79 [95% CI, 0.85-3.80]). However, the association of group assignment with smoking cessation reached statistical significance at all follow-ups, including 26 weeks, with multiple imputation (37.37 [23.5%] in the UC plus FI group vs 19.48 [12.1%] in the UC group were abstinent; AOR, 2.29 [95% CI, 1.14-4.63]). Repeated-measures analyses indicated that participants in the UC plus FI group were significantly more likely to achieve PPA across assessments through 26 weeks with all missing data estimation methods. Other secondary cessation outcomes also showed comparable patterns across estimation methods. Participants earned a mean (SD) of $72 ($90) (of $250 possible) in abstinence-contingent incentives. Participation during the COVID-19 pandemic reduced the likelihood of cessation across assessments. In this randomized clinical trial, incentivizing smoking cessation did not increase cessation at 26 weeks when missing data were treated as smoking; however, the UC plus FI group had greater odds of quitting at follow-ups through 12 weeks. Cessation rates were higher for the UC plus FI group at all follow-ups through 26 weeks when multiple imputation was used to estimate missing outcomes. ClinicalTrials.gov Identifier: NCT02737566.

Smoking data quality of primary care practices in comparison with smoking data from the New Zealand Māori and Pacific abdominal aortic aneurysm screening programme: an observational study

BackgroundQuality smoking data is crucial for assessing smoking-related health risk and eligibility for interventions related to that risk. Smoking information collected in primary care practices (PCPs) is a major data source; however, little is known about the PCP smoking data quality. This project compared PCP smoking data to that collected in the Māori and Pacific Abdominal Aortic Aneurysm (AAA) screening programme.MethodsA two stage review was conducted. In Stage 1, data quality was assessed by comparing the PCP smoking data recorded close to AAA screening episodes with the data collected from participants at the AAA screening session. Inter-rater reliability was analysed using Cohen’s kappa scores. In Stage 2, an audit of longitudinal smoking status was conducted, of a subset of participants potentially misclassified in Stage 1. Data were compared in three groups: current smoker (smoke at least monthly), ex-smoker (stopped > 1 month ago) and never smoker (smoked < 100 cigarettes in lifetime).ResultsOf the 1841 people who underwent AAA screening, 1716 (93%) had PCP smoking information. Stage 1 PCP smoking data showed 82% concordance with the AAA data (adjusted kappa 0.76). Fewer current or ex-smokers were recorded in PCP data. In the Stage 2 analysis of discordant and missing data (N = 313), 212 were enrolled in the 29 participating PCPs, and of these 13% were deceased and 41% had changed PCP. Of the 93 participants still enrolled in the participating PCPs, smoking status had been updated for 43%. Data on quantity, duration, or quit date of smoking were largely missing in PCP records. The AAA data of ex-smokers who were classified as never smokers in the Stage 2 PCP data (N = 27) showed a median smoking cessation duration of 32 years (range 0–50 years), with 85% (N = 23) having quit more than 15 years ago.ConclusionsPCP smoking data quality compared with the AAA data is consistent with international findings. PCP data captured fewer current and ex-smokers, suggesting ongoing improvement is important. Intervention programmes based on smoking status should consider complementary mechanisms to ensure eligible individuals are not missed from programme invitation.

Moderation of the real-world effectiveness of smoking cessation aids by mental health conditions: A population study

Objective To examine whether the real-world effectiveness of popular smoking cessation aids differs between users with and without a history of mental health conditions. Design Nationally-representative cross-sectional survey conducted monthly between 2016–17 and 2020–23. Setting England. Participants 5,593 adults (2,524 with a history of ≥1 mental health conditions and 3,069 without) who had smoked regularly within the past year and had attempted to quit at least once in the past year. Main outcome measures The outcome was self-reported abstinence from quit date up to the survey. Independent variables were use of the following cessation aids during the most recent quit attempt: prescription nicotine replacement therapy (NRT), NRT over-the-counter, varenicline, bupropion, vaping products, face-to-face behavioural support, telephone support, written self-help materials, websites, hypnotherapy, Allen Carr’s Easyway, heated tobacco products, and nicotine pouches. The moderator was history of diagnosed mental health conditions (yes/no). Covariates included sociodemographic characteristics, level of cigarette addiction, and characteristics of the quit attempt. Results Relative to those without, participants with a history of mental health conditions were significantly more likely to report using vaping products (38.8% [95%CI 36.7–40.8] vs. 30.7% [28.9–32.5]), prescription NRT (4.8% [3.9–5.7] vs. 2.7% [2.1–3.3]), and websites (4.0% [3.2–4.8] vs. 2.2% [1.6–2.7]). Groups did not differ significantly in their use of other aids. After adjusting for covariates and use of other cessation aids, those who used vaping products (OR = 1.92, 95%CI 1.61–2.30), varenicline (OR = 1.88, 95%CI 1.19–2.98), or heated tobacco products (OR = 2.33, 95%CI 1.01–5.35) had significantly higher odds of quitting successfully than those who did not report using these aids. There was little evidence that using other cessation aids increased the odds of successful cessation, or that the user’s history of mental health conditions moderated the effectiveness of any aid. Conclusions Use of vaping products, varenicline, or heated tobacco products in a quit attempt was associated with significantly greater odds of successful cessation, after adjustment for use of other cessation aids and potential confounders. There was no evidence to suggest the effectiveness of any popular cessation aid differed according to the user’s history of mental health conditions.

Implementing a Staff-Led Smoking Cessation Intervention in a Diverse Safety-Net Rheumatology Clinic: A Pre-Post Scalability Study in a Low-Resource Setting.

Quit Connect (QC), our specialty clinic smoking cessation intervention, supports clinic staff to check, advise, and connect willing patients to a state quit line or class. QC improved tobacco screening and quit line referrals 26-fold in a predominantly White academic health care system population. Implementing QC includes education, electronic health record (EHR) reminders, and periodic audit feedback. This study tested QC's feasibility and impact in a safety-net rheumatology clinic with a predominantly Black population. In this pre-post study, adult rheumatology visits were analyzed 12 months before through 18 months after QC intervention (November 2019 through November 2021, omitting COVID-19 peak April through November 2020). EHR data compared process and clinical outcomes, including offers, referrals to resources, completed referrals, and documented cessation. Clinic staff engaged in pre-post focus groups and questionnaires regarding intervention feasibility and acceptability. Cost-effectiveness was also assessed. Visit-level patients who smoked were 89.8% Black and 69.5% women (n = 550). Before intervention, clinic staff rarely asked patients about readiness to cut back smoking (<10% assessment). After QC intervention, staff assessed quit readiness in 31.8% of visits with patients who smoked (vs 8.1% before); 58.9% of these patients endorsed readiness to cut back or quit. Of 102 accepting cessation services, 37% (n = 17) of those reached set a quit date. Staff found the intervention feasible and acceptable. Each quit attempt cost approximately $4 to $10. In a safety-net rheumatology clinic with a predominantly Black population, QC improved tobacco screening, readiness-to-quit assessment, and referrals and was also feasible and cost-effective.

Project phoenix: Pilot randomized controlled trial of a smartphone-delivered intervention for people who are not ready to quit smoking

BackgroundMost people who smoke cigarettes report they want to quit in the future, but only 20 % are ready to quit within the next 30 days. This 3-arm pilot randomized controlled trial examined the feasibility and initial efficacy of a novel smartphone-based intervention that aimed to induce smoking cessation attempts among adults not initially ready to quit. MethodsParticipants randomized into the two intervention groups (Group 1: Phoenix App Only; Group 2: Phoenix App + Nicotine Replacement Therapy) received daily smoking cessation messages via smartphone application that were tailored to their current readiness to quit, while the attention control group (i.e., Factoid) received messages not related to smoking cessation. All participants completed a weekly survey for 26 weeks and used the app to set quit dates when/if desired. ResultsParticipants (N=152) were female (67.8 %), White (75.7 %), 50.0 years old (SD=12.5), and smoked 20.4 cigarettes per day (SD=10.5). Results indicated that the Phoenix interventions were feasible (e.g., participants viewed ~185 messages over 26 weeks; 74.8 % of weekly surveys were completed; 85.5 % completed the 26-week follow-up assessment). Phoenix participants set more quit dates, set quit dates sooner, were abstinent for more days, and used smoking cessation medications on more days than those assigned to the Factoid group. ConclusionsThis low-burden, smartphone-based smoking cessation induction intervention may increase smoking cessation attempts, and may reduce barriers that are encountered with traditional in-person or call-based interventions.Trial Registration: Clinicaltrials.gov number: NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129

Effect of Adding Personalized Instant Messaging Apps to a Brief Smoking Cessation Model in Community Smokers in Hong Kong: Pragmatic Randomized Clinical Trial.

While text messaging has proven effective for smoking cessation (SC), engagement in the intervention remains suboptimal. This study aims to evaluate whether using more interactive and adaptive instant messaging (IM) apps on smartphones, which enable personalization and chatting with SC advisors, can enhance SC outcomes beyond the provision of brief SC advice and active referral (AR) to SC services. From December 2018 to November 2019, we proactively recruited 700 adult Chinese daily cigarette users in Hong Kong. Participants were randomized in a 1:1 ratio. At baseline, all participants received face-to-face brief advice on SC. Additionally, they were introduced to local SC services and assisted in selecting one. The intervention group received an additional 26 personalized regular messages and access to interactive chatting through IM apps for 3 months. The regular messages aimed to enhance self-efficacy, social support, and behavioral capacity for quitting, as well as to clarify outcome expectations related to cessation. We developed 3 sets of messages tailored to the planned quit date (within 30 days, 60 days, and undecided). Participants in the intervention group could initiate chatting with SC advisors on IM themselves or through prompts from regular messages or proactive inquiries from SC advisors. The control group received 26 SMS text messages focusing on general health. The primary outcomes were smoking abstinence validated by carbon monoxide levels of <4 parts per million at 6 and 12 months after the start of the intervention. Of the participants, 505/700 (72.1%) were male, and 450/648 (69.4%) were aged 40 or above. Planning to quit within 30 days was reported by 500/648 (77.2%) participants, with fewer intervention group members (124/332, 37.3%) reporting previous quit attempts compared with the control group (152/335, 45.4%; P=.04). At the 6- and 12-month follow-ups (with retention rates of 456/700, 65.1%, and 446/700, 63.7%, respectively), validated abstinence rates were comparable between the intervention (14/350, 4.0%, and 19/350, 5.4%) and control (11/350, 3.1% and 21/350, 6.0%) groups. Compared with the control group, the intervention group reported greater utilization of SC services at 12 months (RR 1.26, 95% CI 1.01-1.56). Within the intervention group, engaging in chat sessions with SC advisors predicted better validated abstinence at 6 months (RR 3.29, 95% CI 1.13-9.63) and any use of SC services (RR 1.66, 95% CI 1.14-2.43 at 6 months; RR 1.67, 95% CI 1.26-2.23 at 12 months). An IM-based intervention, providing support and assistance alongside brief SC advice and AR, did not yield further increases in quitting rates but did encourage the utilization of SC services. Future research could explore whether enhanced SC service utilization leads to improved long-term SC outcomes. ClinicalTrials.gov NCT03800719; https://clinicaltrials.gov/ct2/show/NCT03800719.

Behavioral Activation Mobile App to Motivate Smokers to Quit: Feasibility and Pilot Randomized Controlled Trial.

Behavioral activation (BA) is an evidence-based treatment for depression that fosters engagement in values-based activities to increase access to positive reinforcement. Depressed mood has been shown to hinder smoking cessation. This study determined the feasibility and preliminary efficacy of a mobile app to motivate smokers to quit by using BA and integrating motivational messages to quit smoking. Adult smokers (N=56; mean age 34.5, SD 9.52 years) who were not ready to quit smoking within 30 days were recruited from advertisements and randomized to either 8 weeks of the BA app (set 2 values-based activities per week+motivational messages+feedback on changes in smoking, mood, and values-based activities) or the control group (no app; received resources for quitting smoking). All participants completed the baseline and end-of-treatment web-based questionnaires. Controls also completed weekly web-based assessments, and BA app participants completed assessments through the app. There were no dropouts and only 2 participants in each condition did not complete the end-of-treatment questionnaire. The results demonstrated that it is feasible to recruit smokers who are unmotivated to quit into a smoking cessation induction trial: 86% (57/66) of eligible participants were randomized (BA app: n=27; control: n=29). Participants reported high levels of satisfaction: 80% (20/25) of participants said they would recommend the BA app, there were moderate-to-high scores on the Mobile App Rating Scale, and 88% (22/25) of participants rated the app 3 stars or higher (out of 5). There were high levels of BA app engagement: 96% (26/27) of participants planned activities, and 67% (18/27) of participants planned 7 or more activities. High engagement was found even among those who were at the highest risk for continued smoking (low motivation to quit, low confidence to quit, and high negative affect). The results provided support for the hypothesized relationships between BA constructs: greater pleasant activity completion was associated with greater positive affect (b=0.37, SE 0.21; 95% CI -0.05 to 0.79; P=.08), and greater positive affect tended to predict fewer cigarettes smoked the next day (b=-0.19, SE 0.10; 95% CI -0.39 to 0.01; P=.06). Additionally, a greater number of activities planned was associated with lower negative affect (b=-0.26, SE 0.15; 95% CI -0.55 to 0.04; P=.09). Overall, 16% (4/25) of BA app participants set a quit date versus 4% (1/27) among controls, and there were promising (but not significant) trends for motivation and confidence to quit. The findings suggest that a mobile app intervention can be made appealing to smokers who are unmotivated to quit by focusing on aspects most important to them, such as mood management. This theory-based intervention has shown some initial support for the underlying theoretical constructs, and further efficacy testing is warranted in a fully powered trial.

A smoking cessation smartphone app that delivers real-time 'context aware' behavioural support: the Quit Sense feasibility RCT.

During a quit attempt, cues from a smoker's environment are a major cause of brief smoking lapses, which increase the risk of relapse. Quit Sense is a theory-guided Just-In-Time Adaptive Intervention smartphone app, providing smokers with the means to learn about their environmental smoking cues and provides 'in the moment' support to help them manage these during a quit attempt. To undertake a feasibility randomised controlled trial to estimate key parameters to inform a definitive randomised controlled trial of Quit Sense. A parallel, two-arm randomised controlled trial with a qualitative process evaluation and a 'Study Within A Trial' evaluating incentives on attrition. The research team were blind to allocation except for the study statistician, database developers and lead researcher. Participants were not blind to allocation. Online with recruitment, enrolment, randomisation and data collection (excluding manual telephone follow-up) automated through the study website. Smokers (323 screened, 297 eligible, 209 enrolled) recruited via online adverts on Google search, Facebook and Instagram. Participants were allocated to 'usual care' arm (n = 105; text message referral to the National Health Service SmokeFree website) or 'usual care' plus Quit Sense (n = 104), via a text message invitation to install the Quit Sense app. Follow-up at 6 weeks and 6 months post enrolment was undertaken by automated text messages with an online questionnaire link and, for non-responders, by telephone. Definitive trial progression criteria were met if a priori thresholds were included in or lower than the 95% confidence interval of the estimate. Measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), biochemically verified 6-month abstinence and hypothesised mechanisms of action and participant views of the app (qualitative). Self-reported smoking outcome completion rates were 77% (95% confidence interval 71% to 82%) and health economic data (resource use and quality of life) 70% (95% CI 64% to 77%) at 6 months. Return rate of viable saliva samples for abstinence verification was 39% (95% CI 24% to 54%). The per-participant recruitment cost was £19.20, which included advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%; 78/104) installed the app and, of these, 100% set a quit date within the app and 51% engaged with it for more than 1 week. The rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CIs 1.23 to 16.94). There was no evidence of between-arm differences in hypothesised mechanisms of action. Three out of four progression criteria were met. The Study Within A Trial analysis found a £20 versus £10 incentive did not significantly increase follow-up rates though reduced the need for manual follow-up and increased response speed. The process evaluation identified several potential pathways to abstinence for Quit Sense, factors which led to disengagement with the app, and app improvement suggestions. Biochemical validation rates were lower than anticipated and imbalanced between arms. COVID-19-related restrictions likely limited opportunities for Quit Sense to provide location tailored support. The trial design and procedures demonstrated feasibility and evidence was generated supporting the efficacy potential of Quit Sense. Progression to a definitive trial is warranted providing improved biochemical validation rates. This trial is registered as ISRCTN12326962. This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Preliminary Efficacy of a Cognitive Behavioral Therapy-Based Smartphone App for Smoking Cessation in China: Randomized Controlled Pilot Trial.

The overall prevalence of cigarette smokers in China is very high, and China's total cigarette consumption makes up more than 40% of the world's consumption. In view of the lack of smoking cessation services and social support in China and the effectiveness of mobile phone apps for quitting smoking in other countries, we carried out a smartphone app-based smoking cessation trial in China. This study aimed to evaluate the efficacy of a cognitive behavioral therapy (CBT)-based smoking cessation smartphone app among smokers seeking treatment in China. We conducted a randomized controlled, web-based pilot clinical trial in China between February 23 and June 27, 2021. Eligible participants were randomly assigned to the smoking cessation app intervention group or the control group in a ratio of 1:1. The intervention group received the CBT smoking cessation intervention using a smartphone app, and the control group received a "thank you" message. The intervention was 4 weeks long, and the patients were followed up for 4 weeks. The primary outcome was self-reported continuous smoking abstinence at week 4 after the quit date. The secondary outcomes included self-reported 7-day point prevalence of smoking abstinence; reduction of the number of cigarettes smoked per day at weeks 1, 2, 3, and 4; and program acceptability. A total of 973 people were recruited to quit smoking, of whom 262 completed basic information, 56 were excluded, and 206 were randomized and included in the final analysis. There were 189 (91.7%) men and 17 (8.3%) women, with an average age of 34.46 (SD 7.53) years and an average daily smoking rate of 15.93 (SD 7.10) cigarettes/day. We found 30 (29.7%) of the 101 participants in the intervention group and 7 (6.7%) of the 105 participants in the control group reported continuous smoking cessation after the quit date at week 4 (odds ratio 5.92, 95% CI 3.78-9.26; P<.001). The 7-day point prevalence abstinence rate of the intervention group varied from 42.6% (43/101) to 46.5% (47/101) after 1, 2, 3, and 4 weeks, while the control group varied from 18.1% (19/105) to 26.7% (28/105). Compared to the control group, continued smokers consumed 1.5-3.0 fewer cigarettes per day in the intervention group. The overall program got positive user feedback with a high satisfaction rate (66/87, 76%) and an average Mobile Application Rating Scale user version score of 3.46. Our pilot study provided preliminary evidence that the CBT-based smoking cessation smartphone app led to improved smoking quit rates versus control in Chinese smokers. The study demonstrated the CBT-based smartphone app may be an effective and feasible digital treatment model to help smokers quit, which may improve smoking cessation service quality and accessibility in China. ClinicalTrials.gov NCT04421170; https://clinicaltrials.gov/study/NCT04421170. RR2-10.1136/bmjopen-2020-041985.

Electronic Nicotine-Delivery Systems for Smoking Cessation

BackgroundElectronic nicotine-delivery systems — also called e-cigarettes — are used by some tobacco smokers to assist with quitting. Evidence regarding the efficacy and safety of these systems is needed.MethodsIn this open-label, controlled trial, we randomly assigned adults who were smoking at least five tobacco cigarettes per day and who wanted to set a quit date to an intervention group, which received free e-cigarettes and e-liquids, standard-of-care smoking-cessation counseling, and optional (not free) nicotine-replacement therapy, or to a control group, which received standard counseling and a voucher, which they could use for any purpose, including nicotine-replacement therapy. The primary outcome was biochemically validated, continuous abstinence from smoking at 6 months. Secondary outcomes included participant-reported abstinence from tobacco and from any nicotine (including smoking, e-cigarettes, and nicotine-replacement therapy) at 6 months, respiratory symptoms, and serious adverse events.ResultsA total of 1246 participants underwent randomization; 622 participants were assigned to the intervention group, and 624 to the control group. The percentage of participants with validated continuous abstinence from tobacco smoking was 28.9% in the intervention group and 16.3% in the control group (relative risk, 1.77; 95% confidence interval, 1.43 to 2.20). The percentage of participants who abstained from smoking in the 7 days before the 6-month visit was 59.6% in the intervention group and 38.5% in the control group, but the percentage who abstained from any nicotine use was 20.1% in the intervention group and 33.7% in the control group. Serious adverse events occurred in 25 participants (4.0%) in the intervention group and in 31 (5.0%) in the control group; adverse events occurred in 272 participants (43.7%) and 229 participants (36.7%), respectively.ConclusionsThe addition of e-cigarettes to standard smoking-cessation counseling resulted in greater abstinence from tobacco use among smokers than smoking-cessation counseling alone. (Funded by the Swiss National Science Foundation and others; ESTxENDS ClinicalTrials.gov number, NCT03589989.)

Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development Process and Randomized Controlled Trial.

Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot. We aim to report results of the user-centered design development process and randomized controlled trial for a novel and comprehensive quit smoking conversational chatbot called QuitBot. The 4 years of formative research for developing QuitBot followed an 11-step process: (1) specifying a conceptual model; (2) conducting content analysis of existing interventions (63 hours of intervention transcripts); (3) assessing user needs; (4) developing the chat's persona ("personality"); (5) prototyping content and persona; (6) developing full functionality; (7) programming the QuitBot; (8) conducting a diary study; (9) conducting a pilot randomized controlled trial (RCT); (10) reviewing results of the RCT; and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot RCT results. The process of adding a QnA function itself involved a three-step process: (1) generating QnA pairs, (2) fine-tuning large language models (LLMs) on QnA pairs, and (3) evaluating the LLM outputs. We developed a quit smoking program spanning 42 days of 2- to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing Food and Drug Administration-approved cessation medications, coping with triggers, and recovering from lapses and relapses. In a pilot RCT with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT text messaging program, particularly among those who viewed all 42 days of program content: 30-day, complete-case, point prevalence abstinence rates at 3-month follow-up were 63% (39/62) for QuitBot versus 38.5% (45/117) for SmokefreeTXT (odds ratio 2.58, 95% CI 1.34-4.99; P=.005). However, Facebook Messenger intermittently blocked participants' access to QuitBot, so we transitioned from Facebook Messenger to a stand-alone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions led to us develop a core conversational feature, enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT-3.5 (OpenAI) responds to questions that are not within our library of QnA pairs. The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions. ClinicalTrials.gov NCT03585231; https://clinicaltrials.gov/study/NCT03585231.

Evaluating the impact of an incentive scheme to encourage pregnant people to set a quit-smoking date

PurposeThis study aims to demonstrate the evaluation of an incentive scheme to encourage pregnant people to set a quit-smoking date.Design/methodology/approachThe paper outlines a collaborative approach, working with pregnant people, clinicians, tobacco dependency practitioners and academics to gain insights into their perspectives and experiences. Quantitative and qualitative data were analysed.FindingsThe incentive scheme and appropriate support from clinicians have been shown to encourage pregnant people to set a quit date. The tobacco dependency practitioners helped remove barriers, such as the perception of the stigmatisation of smoking when pregnant. The practitioners also helped pregnant people make informed decisions to support successful behaviour change. The impact of the scheme resulted in improved infant health indicators. The scheme’s evaluation also supported establishing stakeholder knowledge exchange and learning processes.Research limitations/implicationsThis is a single-site study among a relatively small group of people designed to achieve a specific evaluation objective. Caution in generalising to wider settings should be exercised.Practical implicationsThis study highlights the efficacy of an incentive scheme, complemented with support from clinicians, and the significance of knowledge exchange and collaboration between stakeholders in health care with significance in similar settings.Originality/valueThe paper details the incentive scheme input, actions, output, outcomes and impact involving a wider range of stakeholders, including the emotional consequences for participants, clinicians and academics.

Clinical study protocol on electronic cigarettes and nicotine pouches for smoking cessation in Pakistan: a randomized controlled trial

BackgroundPakistan is one of most vulnerable low- and middle-income countries with 29 million adult active tobacco users. Smoking cessation services are lacking as the tobacco control initiatives have largely failed to address the smoking endemic. Over the last 5 years, Pakistan has witnessed the use of innovative tobacco harm reduction (THR) products such as e-cigarettes and nicotine pouches. However, their use remains limited. THR products are imported legally as consumer goods and are taxable. The lack of sufficient data for THR and its application is a challenge in gauging their effectiveness in assisting smokers quit combustible smoking. Evidence-based studies can help in measuring the effectiveness of e-cigarettes and nicotine pouches as smoking cessation aids.MethodKeeping in view the study objectives, a sample size of 600 participants will be sufficient to assess the effectiveness of e-cigarettes and nicotine pouches for smoking cessation in Pakistan. Of these, 200 participants each will receive e-cigarettes and nicotine pouches along with basic care counselling, while the remaining 200 participants will only receive basic care counselling for 48 weeks. The association of participants’ characteristics with smoking and health status will be based on the bivariate and multivariate analysis. The simple t-test and variance analysis will assess the differences in intervention indicators between the control and treatment groups. For the inferential analysis, the average treatment impact will be based on the quasi-experimental techniques such as difference in difference (DID) or propensity score matching (PMS).DiscussionThe study will evaluate the participants at the baseline as they decide the quit date. After every 12 weeks, a follow-up survey with the participants will be conducted. Results are anticipated to inform the public, decision-makers, and researchers about the effects of using e-cigarettes and nicotine pouches in the short- and medium-term periods. Critically, the potential of e-cigarettes and other alternative nicotine delivery systems as smoking cessation aid will be assessed.Trial registration ClinicalTrials.govNCT05715164. Registered on February 6, 2023. Protocol version. Protocol version 1.0, 14-12-2022Trial in progress and not yet recruiting participants. Estimated primary data collection date—April 2024

Effect of a mindfulness training app on a cigarette quit attempt: an investigator-blinded, 58-county randomized controlled trial.

Cigarette smoking is the leading cause of preventable cancers. A majority of the 34 million people who currently smoke report wanting to quit. Mindfulness training apps offer a guided telehealth intervention to foster individuals' behavioral meditation practice. We present the main outcomes of a parallel-group randomized controlled trial that tested app-based mindfulness training vs attention control on smoking behavior. We enrolled adult residents from across California who smoked daily and were willing to make a quit attempt (N = 213). Participants completed daily sessions in 10-minute segments for 14 consecutive days. Participants then started a quit attempt and reported daily smoking for 28 days following the quit date using the timeline follow-back measure. Seven-day point-prevalence abstinence for each week during the 4-week quit period ranged from 21.8% to 27.7% for app-based mindfulness training and 17.9% to 19.6% for controls. The intention-to-treat sample revealed that app-based mindfulness training outperformed controls on the proportion of abstinence days during the quit period (odds ratio = 2.00, 95% confidence interval = 1.03 to 3.87, P = .041). Although the 7-day point prevalence abstinence for week 4 favored app-based mindfulness training, significance was not reached (odds ratio = 1.65, 95% confidence interval = 0.84 to 3.23, P = .148). The mean number of cigarettes smoked per day among smokers was 4.95 for app-based mindfulness training vs 5.69 for controls (odds ratio = 0.81, 95% confidence interval = 0.71 to 0.92, P = .002), suggesting harm reduction in continued smokers. A mindfulness training app prescribed for 2 weeks leading up to a quit date showed an advantage over controls for total abstinence days and fewer cigarettes smoked in a diverse sample consisting of urban and rural residents. These findings yield implications for the use of apps to reduce exposure to the carcinogenic properties of cigarette smoke.

Varenicline Combined With Oral Nicotine Replacement Therapy and Smartphone-Based Medication Reminders for Smoking Cessation: Feasibility Randomized Controlled Trial.

Varenicline and oral nicotine replacement therapy (NRT) have each been shown to increase the likelihood of smoking cessation, but their combination has not been studied. In addition, smoking cessation medication adherence is often poor, thus, challenging the ability to evaluate medication efficacy. This study examined the effects of combined varenicline and oral NRT and smartphone medication reminders on pharmacotherapy adherence and smoking abstinence among adults enrolled in smoking cessation treatment. A 2×2 factorial design was used. Participants (N=34) were randomized to (1) varenicline + oral NRT (VAR+NRT) or varenicline alone (VAR) and (2) smartphone medication reminder messages (REM) or no reminder messages (NREM) over 13 weeks. Participants assigned to VAR+REM received varenicline reminder prompts, and those assigned to VAR+NRT+REM also received reminders to use oral NRT. The other 2 groups (VAR+NREM and VAR+NRT+NREM) did not receive medication reminders. Participants were not blinded to intervention groups. All participants received tobacco cessation counseling. Smartphone assessments of smoking as well as varenicline and NRT use (if applicable) were prompted daily through the first 12 weeks after a scheduled quit date. Descriptive statistics were generated to characterize the relations between medication and reminder group assignments with daily smoking, daily varenicline adherence, and daily quantity of oral NRT used. Participants completed follow-up assessments for 26 weeks after the quit date. Participants were predominantly White (71%), and half were female (50%). On average, participants were 54.2 (SD 9.4) years of age, they smoked an average of 19.0 (SD 9.0) cigarettes per day and had smoked for 34.6 (SD 12.7) years. Descriptively, participants assigned to VAR+NRT reported more days of smoking abstinence compared to VAR (29.3 vs 26.3 days). Participants assigned to REM reported more days of smoking abstinence than those assigned to NREM (40.5 vs 21.8 days). Participants assigned to REM were adherent to varenicline on more days compared to those assigned to NREM (58.6 vs 40.5 days), and participants assigned to VAR were adherent to varenicline on more days than those assigned to VAR + NRT (50.7 vs 43.3 days). In the subsample of participants assigned to VAR+NRT, participants assigned to REM reported more days where ≥5 pieces of NRT were used than NREM (14.0 vs 7.4 days). Average overall medication adherence (assessed via the Medication Adherence Questionnaire) showed the same pattern as the daily smartphone-based adherence assessments. Preliminary findings indicated that smoking cessation interventions may benefit from incorporating medication reminders and combining varenicline with oral NRT, though combining medications may be associated with poorer adherence. Further study is warranted. ClinicalTrials.gov NCT03722966; https://classic.clinicaltrials.gov/ct2/show/NCT03722966.