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Impulsivity dimensions have been shown to be associated with smoking status and tobacco use disorder severity. However, it is important to determine the specific impulsivity traits associated with smoking relapse. This study aimed at investigating the associations between impulsivity traits and smoking cessation success among adult smokers at 12 months after a quit attempt. Participants were 68 adult smokers enrolled in a 3-month course of simvastatine or placebo associated with behavioral cessation support, with a 9-month follow-up (ADDICSTATINE study). They were classified in 3 groups according to smoking status: abstinent, reduction ≥ 50%baseline or reduction < 50%baseline at 3 and 12 months. Impulsivity traits were assessed using the UPPS-P-scale. At 12 months, abstainers and participants who reduced smoking by 50% or more had significantly lower scores in negative and positive urgency compared to participants who reduced smoking by less than 50% ( p  = 0.011 and 0.0059). These urgency traits scores at 12 months were significantly and negatively correlated with smoking reduction at 12 months ( p  = 0.017 and 0.0012). These impulsivity traits were also associated with the smoking cessation success at 3 months. Patients who were abstinent at 3 months had also lower negative and positive urgency ( p  = 0.017 and 0.0039). Smoking cessation success at 3 and 12 months were not associated with the other impulsivity traits, sensation seeking, lack of premeditation or perseverance. Our findings suggest that positive and negative urgency are associated with smoking cessation success. Proposing better tailored-based-treatment targeting these impulsivity traits in combination with conventional treatment may help improving smoking treatment success.

In a randomized trial involving 886 smokers, e-cigarettes were more effective than nicotine-replacement therapy with respect to the 1-year abstinence rate (18% vs. 10%). Throat or mouth irritation was more common in the e-cigarette group, and nausea was more common in the nicotine-replacement group.

Substantial concerns have been raised about the neuropsychiatric safety of the smoking cessation medications varenicline and bupropion. Their efficacy relative to nicotine patch largely relies on indirect comparisons, and there is limited information on safety and efficacy in smokers with psychiatric disorders. We compared the relative neuropsychiatric safety risk and efficacy of varenicline and bupropion with nicotine patch and placebo in smokers with and without psychiatric disorders. We did a randomised, double-blind, triple-dummy, placebo-controlled and active-controlled (nicotine patch; 21 mg per day with taper) trial of varenicline (1 mg twice a day) and bupropion (150 mg twice a day) for 12 weeks with 12-week non-treatment follow-up done at 140 centres (clinical trial centres, academic centres, and outpatient clinics) in 16 countries between Nov 30, 2011, and Jan 13, 2015. Participants were motivated-to-quit smokers with and without psychiatric disorders who received brief cessation counselling at each visit. Randomisation was computer generated (1:1:1:1 ratio). Participants, investigators, and research personnel were masked to treatment assignments. The primary endpoint was the incidence of a composite measure of moderate and severe neuropsychiatric adverse events. The main efficacy endpoint was biochemically confirmed continuous abstinence for weeks 9–12. All participants randomly assigned were included in the efficacy analysis and those who received treatment were included in the safety analysis. The trial is registered at ClinicalTrials.gov (number NCT01456936) and is now closed. 8144 participants were randomly assigned, 4116 to the psychiatric cohort (4074 included in the safety analysis) and 4028 to the non-psychiatric cohort (3984 included in the safety analysis). In the non-psychiatric cohort, 13 (1·3%) of 990 participants reported moderate and severe neuropsychiatric adverse events in the varenicline group, 22 (2·2%) of 989 in the bupropion group, 25 (2·5%) of 1006 in the nicotine patch group, and 24 (2·4%) of 999 in the placebo group. The varenicline–placebo and bupropion–placebo risk differences (RDs) for moderate and severe neuropsychiatric adverse events were −1·28 (95% CI −2·40 to −0·15) and −0·08 (−1·37 to 1·21), respectively; the RDs for comparisons with nicotine patch were −1·07 (−2·21 to 0·08) and 0·13 (−1·19 to 1·45), respectively. In the psychiatric cohort, moderate and severe neuropsychiatric adverse events were reported in 67 (6·5%) of 1026 participants in the varenicline group, 68 (6·7%) of 1017 in the bupropion group, 53 (5·2%) of 1016 in the nicotine patch group, and 50 (4·9%) of 1015 in the placebo group. The varenicline–placebo and bupropion–placebo RDs were 1·59 (95% CI −0·42 to 3·59) and 1·78 (−0·24 to 3·81), respectively; the RDs versus nicotine patch were 1·22 (−0·81 to 3·25) and 1·42 (−0·63 to 3·46), respectively. Varenicline-treated participants achieved higher abstinence rates than those on placebo (odds ratio [OR] 3·61, 95% CI 3·07 to 4·24), nicotine patch (1·68, 1·46 to 1·93), and bupropion (1·75, 1·52 to 2·01). Those on bupropion and nicotine patch achieved higher abstinence rates than those on placebo (OR 2·07 [1·75 to 2·45] and 2·15 [1·82 to 2·54], respectively). Across cohorts, the most frequent adverse events by treatment group were nausea (varenicline, 25% [511 of 2016 participants]), insomnia (bupropion, 12% [245 of 2006 participants]), abnormal dreams (nicotine patch, 12% [251 of 2022 participants]), and headache (placebo, 10% [199 of 2014 participants]). Efficacy treatment comparison did not differ by cohort. The study did not show a significant increase in neuropsychiatric adverse events attributable to varenicline or bupropion relative to nicotine patch or placebo. Varenicline was more effective than placebo, nicotine patch, and bupropion in helping smokers achieve abstinence, whereas bupropion and nicotine patch were more effective than placebo. Pfizer and GlaxoSmithKline.

In this randomized trial of financial incentives in smokers, both reward-based and deposit-based incentive programs were more effective than usual care in achieving smoking cessation. Reward programs were much more commonly accepted than deposit-based programs. Financial incentives have been shown to promote a variety of health behaviors. 1 – 8 For example, in a randomized, clinical trial involving 878 General Electric employees, a bundle of incentives worth $750 for smoking cessation nearly tripled quit rates, from 5.0% to 14.7%, 8 and led to a program adapted by General Electric for its U.S. employees. 9 Although incentive programs are increasingly used by governments, employers, and insurers to motivate changes in health behavior, 10 , 11 their design is usually based on the traditional economic assumption that the size of the incentive determines its effectiveness. In contrast, behavioral economic theory suggests that incentives . . .

Electronic 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. In 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. A 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. The 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.).

In a pragmatic trial involving smokers, financial incentives were more effective than free cessation aids; free cessation aids or e-cigarettes were no more effective than usual care. Cessation rates among smokers assigned to financial incentives were less than 3%.

Electronic cigarettes (e-cigarettes) can deliver nicotine and mitigate tobacco withdrawal and are used by many smokers to assist quit attempts. We investigated whether e-cigarettes are more effective than nicotine patches at helping smokers to quit. We did this pragmatic randomised-controlled superiority trial in Auckland, New Zealand, between Sept 6, 2011, and July 5, 2013. Adult (≥18 years) smokers wanting to quit were randomised (with computerised block randomisation, block size nine, stratified by ethnicity [Māori; Pacific; or non-Māori, non-Pacific], sex [men or women], and level of nicotine dependence [>5 or ≤5 Fagerström test for nicotine dependence]) in a 4:4:1 ratio to 16 mg nicotine e-cigarettes, nicotine patches (21 mg patch, one daily), or placebo e-cigarettes (no nicotine), from 1 week before until 12 weeks after quit day, with low intensity behavioural support via voluntary telephone counselling. The primary outcome was biochemically verified continuous abstinence at 6 months (exhaled breath carbon monoxide measurement <10 ppm). Primary analysis was by intention to treat. This trial is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12610000866000. 657 people were randomised (289 to nicotine e-cigarettes, 295 to patches, and 73 to placebo e-cigarettes) and were included in the intention-to-treat analysis. At 6 months, verified abstinence was 7·3% (21 of 289) with nicotine e-cigarettes, 5·8% (17 of 295) with patches, and 4·1% (three of 73) with placebo e-cigarettes (risk difference for nicotine e-cigarette vs patches 1·51 [95% CI −2·49 to 5·51]; for nicotine e-cigarettes vs placebo e-cigarettes 3·16 [95% CI −2·29 to 8·61]). Achievement of abstinence was substantially lower than we anticipated for the power calculation, thus we had insufficient statistical power to conclude superiority of nicotine e-cigarettes to patches or to placebo e-cigarettes. We identified no significant differences in adverse events, with 137 events in the nicotine e-cigarettes group, 119 events in the patches group, and 36 events in the placebo e-cigarettes group. We noted no evidence of an association between adverse events and study product. E-cigarettes, with or without nicotine, were modestly effective at helping smokers to quit, with similar achievement of abstinence as with nicotine patches, and few adverse events. Uncertainty exists about the place of e-cigarettes in tobacco control, and more research is urgently needed to clearly establish their overall benefits and harms at both individual and population levels. Health Research Council of New Zealand.

Abstract Introduction Mindfulness training may reduce smoking rates and lessen the association between craving and smoking. This trial tested the efficacy of mindfulness training via smartphone app to reduce smoking. Experience sampling (ES) was used to measure real-time craving, smoking, and mindfulness. Methods A researcher-blind, parallel randomized controlled trial compared the efficacy of mobile mindfulness training with experience sampling (MMT-ES; Craving to Quit) versus experience sampling only (ES) to (1) increase 1-week point-prevalence abstinence rates at 6 months, and (2) lessen the association between craving and smoking. A modified intent-to-treat approach was used for treatment starters (MMT-ES n = 143; ES n = 182; 72% female, 81% white, age 41 ± 12 year). Results No group difference was found in smoking abstinence at 6 months (overall, 11.1%; MMT-ES, 9.8%; ES, 12.1%; χ2(1) = 0.43, p = .51). From baseline to 6 months, both groups showed a reduction in cigarettes per day (p < .0001), craving strength (p < .0001) and frequency (p < .0001), and an increase in mindfulness (p < .05). Using ES data, a craving by group interaction was observed (F(1,3785) = 3.71, p = .05) driven by a stronger positive association between craving and cigarettes per day for ES (t = 4.96, p < .0001) versus MMT-ES (t = 2.03, p = .04). Within MMT-ES, the relationship between craving and cigarettes per day decreased as treatment completion increased (F(1,104) = 4.44, p = .04). Conclusions Although mindfulness training via smartphone app did not lead to reduced smoking rates compared with control, our findings provide preliminary evidence that mindfulness training via smartphone app may help lessen the association between craving and smoking, an effect that may be meaningful to support quitting in the longer term. Implications This is the first reported full-scale randomized controlled trial of any smartphone app for smoking cessation. Findings provide preliminary evidence that smartphone app-based MMT-ES may lessen the association between craving and smoking. Trial registration Clinicaltrials.gov NCT02134509.

China has the highest global prevalence of cigarette smokers, accounting for more than 40% of the total cigarette consumption in the world. Considering the shortage of smoking cessation services in China, and the acceptability, feasibility, and efficacy of mobile-phone-based text messaging interventions for quitting smoking in other countries, we conducted a mobile-phone-based smoking cessation study in China. We conducted a randomized controlled trial in China across 30 cities and provinces from August 17, 2016, to May 27, 2017. Adult smokers aged 18 years and older with the intention to quit smoking were recruited and randomized to a 12-week high-frequency messaging (HFM) or low-frequency messaging (LFM) intervention (\"Happy Quit\") or to a control group in a 5:2:3 ratio. The control group received only text messages unrelated to quitting. The primary outcome was biochemically verified continuous smoking abstinence at 24 weeks. Secondary outcomes included (1) self-reported 7-day point prevalence of abstinence (i.e., not even a puff of smoke, for the last 7 days) at 1, 4, 8, 12, 16, 20, and 24 weeks; (2) self-reported continuous abstinence at 4, 12, and 24 weeks; and (3) self-reported average number of cigarettes smoked per day. A total of 1,369 participants received 12 weeks of intervention or control text messages with continued follow-up for 12 weeks. The baseline characteristics of participants among the HFM (n = 674), LFM (n = 284), and control (n = 411) groups were similar. The study sample included 1,295 (94.6%) men; participants had a mean age of 38.1 (SD 9.79) years and smoked an average of 20.1 (SD 9.19) cigarettes per day. We included the participants in an intention-to-treat analysis. Biochemically verified continuous smoking abstinence at 24 weeks occurred in 44/674 participants in the HFM group (6.5%), 17/284 participants in the LFM group (6.0%), and 8/411 participants (1.9%) in the control group; participants in both the HFM (odds ratio [OR] = 3.51, 95% CI 1.64-7.55, p < 0.001) and the LFM (OR = 3.21, 95% CI 1.36-7.54], p = 0.002) intervention groups were more likely to quit smoking than those in the control group. However, there was no difference in quit rate between the HFM and LFM interventions. We also found that the 7-day point quit rate from week 1 to week 24 ranged from approximately 10% to more than 26% with the intervention and from less than 4% to nearly 12% without the intervention. Those who continued as smokers in the HFM group smoked 1 to 3 fewer cigarettes per day than those in the LFM group over the 24 weeks of trial. Among study limitations, the participants were able to use other smoking cessation services (although very few participants reported using them), cotinine tests can only detect smoking status for a few days, and the proportion of quitters was small. Our findings demonstrate that a mobile-phone-based text messaging intervention (Happy Quit), with either high- or low-frequency messaging, led to smoking cessation in the present study, albeit in a low proportion of smokers, and can therefore be considered for use in large-scale intervention efforts in China. Mobile-phone-based interventions could be paired with other smoking cessation services for treatment-seeking smokers in China. ClinicalTrials.gov NCT02693626.

Background Cigarette smoking poses a major threat to public health. While cessation support provided by healthcare professionals is effective, its use remains low. Chatbots have the potential to serve as a useful addition. The objective of this study is to explore the possibility of using a motivational interviewing style chatbot to enhance engagement, therapeutic alliance, and perceived empathy in the context of smoking cessation. Methods A preregistered web-based experiment was conducted in which smokers ( n  = 153) were randomly assigned to either the motivational interviewing (MI)-style chatbot condition ( n  = 78) or the neutral chatbot condition ( n  = 75) and interacted with the chatbot in two sessions. In the assessment session, typical intake questions in smoking cessation interventions were administered by the chatbot, such as smoking history, nicotine dependence level, and intention to quit. In the feedback session, the chatbot provided personalized normative feedback and discussed with participants potential reasons to quit. Engagement with the chatbot, therapeutic alliance, and perceived empathy were the primary outcomes and were assessed after both sessions. Secondary outcomes were motivation to quit and perceived communication competence and were assessed after the two sessions. Results No significant effects of the experimental manipulation (MI-style or neutral chatbot) were found on engagement, therapeutic alliance, or perceived empathy. A significant increase in therapeutic alliance over two sessions emerged in both conditions, with participants reporting significantly increased motivation to quit. The chatbot was perceived as highly competent, and communication competence was positively associated with engagement, therapeutic alliance, and perceived empathy. Conclusion The results of this preregistered study suggest that talking with a chatbot about smoking cessation can help to motivate smokers to quit and that the effect of conversation has the potential to build up over time. We did not find support for an extra motivating effect of the MI-style chatbot, for which we discuss possible reasons. These findings highlight the promise of using chatbots to motivate smoking cessation. Implications for future research are discussed.