Behavioural interventions for smoking cessation: an overview and network meta-analysis

Interventions for smoking cessation in hospitalised patients

BACKGROUND

In 2020, 32.6% of the world's population used tobacco. Smoking contributes to many illnesses that require hospitalisation. A hospital admission may prompt a quit attempt. Initiating smoking cessation treatment, such as pharmacotherapy and/or counselling, in hospitals may be an effective preventive health strategy. Pharmacotherapies work to reduce withdrawal/craving and counselling provides behavioural skills for quitting smoking. This review updates the evidence on interventions for smoking cessation in hospitalised patients, to understand the most effective smoking cessation treatment methods for hospitalised smokers.

OBJECTIVES

To assess the effects of any type of smoking cessation programme for patients admitted to an acute care hospital.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was 7 September 2022.

SELECTION CRITERIA

We included randomised and quasi-randomised studies of behavioural, pharmacological or multicomponent interventions to help patients admitted to hospital quit. Interventions had to start in the hospital (including at discharge), and people had to have smoked within the last month. We excluded studies in psychiatric, substance and rehabilitation centres, as well as studies that did not measure abstinence at six months or longer.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our primary outcome was abstinence from smoking assessed at least six months after discharge or the start of the intervention. We used the most rigorous definition of abstinence, preferring biochemically-validated rates where reported. We used GRADE to assess the certainty of the evidence.

MAIN RESULTS

We included 82 studies (74 RCTs) that included 42,273 participants in the review (71 studies, 37,237 participants included in the meta-analyses); 36 studies are new to this update. We rated 10 studies as being at low risk of bias overall (low risk in all domains assessed), 48 at high risk of bias overall (high risk in at least one domain), and the remaining 24 at unclear risk. Cessation counselling versus no counselling, grouped by intensity of intervention Hospitalised patients who received smoking cessation counselling that began in the hospital and continued for more than a month after discharge had higher quit rates than patients who received no counselling in the hospital or following hospitalisation (risk ratio (RR) 1.36, 95% confidence interval (CI) 1.24 to 1.49; 28 studies, 8234 participants; high-certainty evidence). In absolute terms, this might account for an additional 76 quitters in every 1000 participants (95% CI 51 to 103). The evidence was uncertain (very low-certainty) about the effects of counselling interventions of less intensity or shorter duration (in-hospital only counselling ≤ 15 minutes: RR 1.52, 95% CI 0.80 to 2.89; 2 studies, 1417 participants; and in-hospital contact plus follow-up counselling support for ≤ 1 month: RR 1.04, 95% CI 0.90 to 1.20; 7 studies, 4627 participants) versus no counselling. There was moderate-certainty evidence, limited by imprecision, that smoking cessation counselling for at least 15 minutes in the hospital without post-discharge support led to higher quit rates than no counselling in the hospital (RR 1.27, 95% CI 1.02 to 1.58; 12 studies, 4432 participants). Pharmacotherapy versus placebo or no pharmacotherapy Nicotine replacement therapy helped more patients to quit than placebo or no pharmacotherapy (RR 1.33, 95% CI 1.05 to 1.67; 8 studies, 3838 participants; high-certainty evidence). In absolute terms, this might equate to an additional 62 quitters per 1000 participants (95% CI 9 to 126). There was moderate-certainty evidence, limited by imprecision (as CI encompassed the possibility of no difference), that varenicline helped more hospitalised patients to quit than placebo or no pharmacotherapy (RR 1.29, 95% CI 0.96 to 1.75; 4 studies, 829 participants). Evidence for bupropion was low-certainty; the point estimate indicated a modest benefit at best, but CIs were wide and incorporated clinically significant harm and clinically significant benefit (RR 1.11, 95% CI 0.86 to 1.43, 4 studies, 872 participants). Hospital-only intervention versus intervention that continues after hospital discharge Patients offered both smoking cessation counselling and pharmacotherapy after discharge had higher quit rates than patients offered counselling in hospital but not offered post-discharge support (RR 1.23, 95% CI 1.09 to 1.38; 7 studies, 5610 participants; high-certainty evidence). In absolute terms, this might equate to an additional 34 quitters per 1000 participants (95% CI 13 to 55). Post-discharge interventions offering real-time counselling without pharmacotherapy (RR 1.23, 95% CI 0.95 to 1.60, 8 studies, 2299 participants; low certainty-evidence) and those offering unscheduled counselling without pharmacotherapy (RR 0.97, 95% CI 0.83 to 1.14; 2 studies, 1598 participants; very low-certainty evidence) may have little to no effect on quit rates compared to control. Telephone quitlines versus control To provide post-discharge support, hospitals may refer patients to community-based telephone quitlines. Both comparisons relating to these interventions had wide CIs encompassing both possible harm and possible benefit, and were judged to be of very low certainty due to imprecision, inconsistency, and risk of bias (post-discharge telephone counselling versus quitline referral: RR 1.23, 95% CI 1.00 to 1.51; 3 studies, 3260 participants; quitline referral versus control: RR 1.17, 95% CI 0.70 to 1.96; 2 studies, 1870 participants).

AUTHORS' CONCLUSIONS

Offering hospitalised patients smoking cessation counselling beginning in hospital and continuing for over one month after discharge increases quit rates, compared to no hospital intervention. Counselling provided only in hospital, without post-discharge support, may have a modest impact on quit rates, but evidence is less certain. When all patients receive counselling in the hospital, high-certainty evidence indicates that providing both counselling and pharmacotherapy after discharge increases quit rates compared to no post-discharge intervention. Starting nicotine replacement or varenicline in hospitalised patients helps more patients to quit smoking than a placebo or no medication, though evidence for varenicline is only moderate-certainty due to imprecision. There is less evidence of benefit for bupropion in this setting. Some of our evidence was limited by imprecision (bupropion versus placebo and varenicline versus placebo), risk of bias, and inconsistency related to heterogeneity. Future research is needed to identify effective strategies to implement, disseminate, and sustain interventions, and to ensure cessation counselling and pharmacotherapy initiated in the hospital is sustained after discharge.

Unveiling the Impact of Electronic Cigarettes (EC) on Health: An Evidence-Based Review of EC as an Alternative to Combustible Cigarettes

Cigarette smoking has been considered a major public health concern due to its serious impact on health. However, smokers intending to quit may find long-term abstinence challenging. When smoking an electronic cigarette (EC), users can experience a sensation and taste similar to that of smoking a combustible cigarette. Therefore, manufacturers promote these products as a viable substitute for combustible cigarettes. However, several researchers report the serious health impacts experienced by EC users. Therefore, this review aims to examine the health impacts of EC use. Based on the findings of the research papers reported in the literature, the role of EC as a smoking cessation tool is unclear. Several researchers have also reported a significant association between EC usage among non-smokers at baseline and the future initiation of combustible cigarette smoking. EC use significantly impacts user health. The nicotine that is present in EC e-liquids can elevate blood pressure, resulting in blood vessel constriction and an increase in heart rate, ultimately leading the body to an ischemic condition, resulting in myocardial infarction (MI), stroke, and increased arterial stiffness. Researchers report a higher likelihood of prediabetes among EC users; its usage was associated with higher OR of having asthma attacks and higher OR of reporting depression and has an impact on birth outcomes among pregnant women. Men using EC are more likely to report erectile dysfunction than non-users. EC also has a significant impact on oral health, which includes periodontal diseases, mucosal lesions, irritation in the mouth and throat, reduced salivary flow, and an increased risk of developing cancer. The physical injury resulting from exploding EC is another health concern. The frequently burned areas included the hands, face, genitalia, and thighs. Marketers promote EC as an alternative to combustible cigarettes and a tool for quitting smoking. However, the Food and Drug Administration has not approved them for smoking cessation. EC can have a serious impact on the health of their users; hence, the findings of this paper have several implications, including the need for regulation of the sales and marketing of these products and educating the users on the impact of these products on their health and safety.

Long-Term Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial

BACKGROUND

Increased smartphone ownership has led to the development of mobile smoking cessation programs. Although the related body of evidence, gathered through the conduct of randomized controlled trials (RCTs), has grown in quality and rigor, there is a need for longer-term data to assess associated smoking cessation durability.

OBJECTIVE

The primary aim was to compare smoking cessation outcomes at 52 weeks in adult smokers randomized to a mobile smoking cessation program, Pivot (intervention), versus QuitGuide (control). The secondary aims included comparison of other smoking-related behaviors, outcomes and participant feedback, and exploratory analyses of baseline factors associated with smoking cessation.

METHODS

In this remote pilot RCT, cigarette smokers in the United States were recruited on the web. Participants were offered 12 weeks of free nicotine replacement therapy (NRT). Data were self-reported via a web-based questionnaire with videoconference biovalidation in participants who reported 7-day point-prevalence abstinence (PPA). Outcomes focused on cessation rates with additional assessment of quit attempts, cigarettes per day (CPD), self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire, NRT use, and participant feedback. Cessation outcomes included self-reported 7- and 30-day PPA, abstinence from all tobacco products, and continuous abstinence. PPA and continuous abstinence were biovalidated using witnessed breath carbon monoxide samples. Exploratory post hoc regression analyses were performed to identify baseline variables associated with smoking cessation.

RESULTS

Participants comprised 188 smokers (n=94, 50% in the Pivot group and n=94, 50% in the QuitGuide group; mean age 46.4, SD 9.2 years; n=104, 55.3% women; n=128, 68.1% White individuals; mean CPD 17.6, SD 9.0). Several cessation rates were higher in the Pivot group (intention to treat): self-reported continuous abstinence was 20% (19/94) versus 9% (8/94; P=.03) for QuitGuide, biochemically confirmed abstinence was 31% (29/94) versus 18% (17/94; P=.04) for QuitGuide, and biochemically confirmed continuous abstinence was 19% (18/94) versus 9% (8/94; P=.046) for QuitGuide. More Pivot participants (93/94, 99% vs 80/94, 85% in the QuitGuide group; P<.001) placed NRT orders (mean 3.3, SD 2.0 vs 1.8, SD 1.6 for QuitGuide; P<.001). Pivot participants had increased self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire (mean point increase 3.2, SD 7.8, P<.001 vs 1.0, SD 8.5, P=.26 for QuitGuide). QuitGuide participants made more mean quit attempts (7.0, SD 6.3 for Pivot vs 9.5, SD 7.5 for QuitGuide; P=.01). Among those who did not achieve abstinence, QuitGuide participants reported greater CPD reduction (mean -34.6%, SD 35.5% for Pivot vs -46.1%, SD 32.3% for QuitGuide; P=.04). Among those who reported abstinence, 90% (35/39) of Pivot participants and 90% (26/29) of QuitGuide participants indicated that their cessation program helped them quit.

CONCLUSIONS

This pilot RCT supports the long-term effectiveness of the Pivot mobile smoking cessation program, with abstinence rates durable to 52 weeks.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

My future-self has (not) quit smoking: An experimental study into the effect of a future-self intervention on smoking-related self-identity constructs

OBJECTIVES

Envisioning one's (non)smoking future may make (un)desired future identities more accessible, salient, and personally relevant and facilitate smoking cessation. The current study assessed whether a future-self intervention can weaken smoker self-identity and expected identity loss when quitting smoking, and strengthen quitter- and nonsmoker self-identity, while accounting for personal factors-socioeconomic position, nicotine dependence, consideration of future consequences, and clarity of the envisioned future-self. Additionally, it examined the association between smoking-related identity and quitting intention and behavior.

METHODS

This longitudinal online experimental study randomized 233 adult smokers to an intervention condition (where they completed mental imagery, visual, and verbal tasks about a future (non)smoking self), or to a passive control condition. Smoker-, quitter-, nonsmoker self-identity and identity loss were measured post-intervention and after one- and three-months. Quit intention and attempts were measured at baseline and after one month.

RESULTS

There was a consistent increase in non-smoker self-identity, and decrease in smoker self-identity and identity loss over a period of six months for all participants, but no significant difference in smoking-related identity between the intervention and control group. While personal factors did not moderate the effect of the intervention, we found that smoking-related identity constructs do vary with nicotine dependence, consideration of future consequences, and clarity of the envisioned future-self. Quitting behavior is primarily associated with non-smoker self-identity.

CONCLUSIONS

Although the future-self intervention did not significantly influence smoking-related identity or behavior, identity-in particular, non-smoker self-identity-is important to consider in smoking cessation interventions. More research is needed to find effective operationalizations for identity-based interventions in the context of smoking.

Perceived Stress and Smoking Cessation: The Role of Smoking Urges

Despite the fact that perceived stress is related to abstinence smoking outcomes, no studies have investigated the mediational effect of specific tobacco-related variables on this relationship. This study aimed to explore the indirect effect of perceived stress on abstinence at the end of treatment through smoking urges. The sample comprised 260 treatment-seeking smokers (58.5% female; Mage = 46.00; SD = 11.1) who underwent psychological smoking cessation treatment. The brief version of the Questionnaire of Smoking Urges (QSU) and the Perceived Stress Scale (PSS14) were used. Mediation analyses were conducted in which smoking urges and their dimensions were potential mediators in the relationship between perceived stress and abstinence at the end of treatment. The results showed a non-significant direct effect of perceived stress on abstinence. However, a significant indirect effect was found through smoking urges (QSU-total) and, specifically, through smoking urges associated with the expectation of negative affect relief (QSU-Factor 2). A non-significant indirect effect through smoking urges related to the expectation of tobacco use as a pleasurable experience (QSU-Factor 1) was also found. Analyzing possible mediator variables could contribute to understanding previous conflicting data. These findings point to potential interest in including treatment components targeting perceived stress and smoking urges to improve the effectiveness of smoking cessation treatments.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, although some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 July 2022, and reference-checked and contacted study authors.  SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants, or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses.

MAIN RESULTS

We included 78 completed studies, representing 22,052 participants, of which 40 were RCTs. Seventeen of the 78 included studies were new to this review update. Of the included studies, we rated ten (all but one contributing to our main comparisons) at low risk of bias overall, 50 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was high certainty that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (RR 1.63, 95% CI 1.30 to 2.04; I2 = 10%; 6 studies, 2378 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6). There was moderate-certainty evidence (limited by imprecision) that the rate of occurrence of AEs was similar between groups (RR 1.02, 95% CI 0.88 to 1.19; I2 = 0%; 4 studies, 1702 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.12, 95% CI 0.82 to 1.52; I2 = 34%; 5 studies, 2411 participants). There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 1840 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 8 studies, 1272 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.66, 95% CI 1.52 to 4.65; I2 = 0%; 7 studies, 3126 participants). In absolute terms, this represents an additional two quitters per 100 (95% CI 1 to 3). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that (non-serious) AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.03, 95% CI 0.54 to 1.97; I2 = 38%; 9 studies, 1993 participants).  Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued EC use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that ECs with nicotine increase quit rates compared to NRT and moderate-certainty evidence that they increase quit rates compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Sex-Related Differences in Oxidative, Platelet, and Vascular Function in Chronic Users of Heat-not-Burn vs. Traditional Combustion Cigarettes

Smoking is still a major cardiovascular risk factor, despite many public awareness campaigns and dedicated interventions. Recently, modified risk products (MRP), e.g., heat-not-burn cigarettes (HNBCs), have been introduced as surrogates of traditional combustion cigarettes (TCCs). Although these products are promoted as healthier than TCCs, few studies have been conducted to assess it. This work is a sex-focused sub-study of a prospective observational study in which apparently healthy chronic TCC smokers were age-matched with regular HNBC users. Blood samples were collected for biochemical assays and blood pressure and flow-mediated dilation (FMD) were measured. Out of 60 subjects, 33 (55%) were women, and 27 (45%) men, with 11 (33%) vs. 9 (33%) non-smokers, respectively, 10 (30%) vs. 10 (37%) TCC smokers, and 12 (36%) vs. 8 (30%) HNBC smokers (p = 0.946). Bivariate and multivariable analyses showed no statistically significant between-sex differences in NO, H2O2, sCD40L, sNox2-dp, sP-selectin, platelet aggregation, cotinine or FMD, overall, in non-smokers, in TCC smokers, or in HNBC smokers (all p > 0.05). HNBCs appeared safer than TCCs when focusing on Nox2-dp (p = 0.026) and sP-selectin (p = 0.050) but had similar levels of the other measured markers. In conclusion, HNBCs have similar detrimental effects on women and men’s oxidative stress (H2O2: p = 0.49; sNox2-dp: p = 0.31) and platelet activation (sP-selectin: p = 0.33; platelet aggregation p = 0.87).

Using Biological Feedback to Promote Health Behavior Change in Adults: Protocol for a Scoping Review

Background

Many health conditions can be prevented, managed, or improved through behavioral interventions. As a component of health behavior change interventions, biological feedback is of particular interest given recent advances in wearable biosensing technology, digital health apps, and personalized health and wellness. Nevertheless, there is a paucity of literature to guide the design and implementation of interventions that incorporate biological feedback to motivate health behavior change.

Objective

The goal of this scoping review is to deeply explore the use of biological feedback as a component of health behavior change interventions that target adults. The objectives of the review include (1) mapping the domains of research that incorporate biological feedback and (2) describing the operational characteristics of using biological feedback in the context of health behavior change.

Methods

A comprehensive list of search terms was developed to capture studies from a wide range of domains. The studies to be included are randomized controlled trials published as primary research articles, theses, or dissertations targeting adults 18 years and older, who use biological feedback to change a health-related behavior. The following electronic databases were searched: Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials, EBSCOhost, PsycINFO, and ProQuest Dissertations & Theses Global. The screening and data extraction process will be guided by the Joanna Briggs Institute Manual for Evidence Synthesis and conducted by trained reviewers.

Results

Database searches were completed in June 2021. A total of 50,459 unique records were returned after the removal of 48,634 duplicate records. The scoping review is planned for completion in 2022.

Conclusions

To our knowledge, this will be the first scoping review to map the literature that uses biological feedback as a component of health behavior change interventions targeting adults. The findings will be used to develop a framework to guide the design and implementation of future health behavior change interventions that incorporate biological feedback.

Trial Registration

OSF Registries OSF.IO/YP5WA; https://osf.io/yp5wa

International Registered Report Identifier (IRRID)

DERR1-10.2196/32579

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update conducted as part of a living systematic review.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 May 2021, and reference-checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting.   SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses.

MAIN RESULTS

We included 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.30, 95% CI 0.89 to 1.90: I2 = 0; 4 studies, 1424 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.06, 95% CI 0.47 to 2.38; I2 = 0; 5 studies, 792 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that non-serious AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants), and again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 participants).  Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to NRT and compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect  evidence of harm from nicotine EC, but longest follow-up was two years and the  number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update of a review first published in 2014.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 February 2021, together with reference-checking and contact with study authors.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and randomized cross-over trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. To be included, studies had to report abstinence from cigarettes at six months or longer and/or data on adverse events (AEs) or other markers of safety at one week or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included changes in carbon monoxide, blood pressure, heart rate, blood oxygen saturation, lung function, and levels of known carcinogens/toxicants. We used a fixed-effect Mantel-Haenszel model to calculate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data from these studies in meta-analyses.

MAIN RESULTS

We included 56 completed studies, representing 12,804 participants, of which 29 were RCTs. Six of the 56 included studies were new to this review update. Of the included studies, we rated five (all contributing to our main comparisons) at low risk of bias overall, 41 at high risk overall (including the 25 non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.69, 95% confidence interval (CI) 1.25 to 2.27; I2 = 0%; 3 studies, 1498 participants). In absolute terms, this might translate to an additional four successful quitters per 100 (95% CI 2 to 8). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar) (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs occurred rarely, with no evidence that their frequency differed between nicotine EC and NRT, but very serious imprecision led to low certainty in this finding (RR 1.37, 95% CI 0.77 to 2.41: I2 = n/a; 2 studies, 727 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.70, 95% CI 1.03 to 2.81; I2 = 0%; 4 studies, 1057 participants). In absolute terms, this might again lead to an additional four successful quitters per 100 (95% CI 0 to 11). These trials mainly used older EC with relatively low nicotine delivery. There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.60, 95% CI 0.15 to 2.44; I2 = n/a; 4 studies, 494 participants). Compared to behavioral support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.70, 95% CI 1.39 to 5.26; I2 = 0%; 5 studies, 2561 participants). In absolute terms this represents an increase of seven per 100 (95% CI 2 to 17). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was no evidence that the rate of SAEs differed, but some evidence that non-serious AEs were more common in people randomized to nicotine EC (AEs: RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants; SAEs: RR 1.17, 95% CI 0.33 to 4.09; I2 = 5%; 6 studies, 1011 participants, very low certainty). Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons and hence evidence for these is limited, with confidence intervals often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to ECs without nicotine and compared to NRT. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the size of effect, particularly when using modern EC products. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, though evidence indicated no difference in AEs between nicotine and non-nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect any clear evidence of harm from nicotine EC, but longest follow-up was two years and the overall number of studies was small. The evidence is limited mainly by imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Behavioural interventions for smoking cessation: an overview and network meta-analysis

BACKGROUND

Smoking is a leading cause of disease and death worldwide. In people who smoke, quitting smoking can reverse much of the damage. Many people use behavioural interventions to help them quit smoking; these interventions can vary substantially in their content and effectiveness.

OBJECTIVES

To summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts and to conduct a network meta-analysis to determine how modes of delivery; person delivering the intervention; and the nature, focus, and intensity of behavioural interventions for smoking cessation influence the likelihood of achieving abstinence six months after attempting to stop smoking; and whether the effects of behavioural interventions depend upon other characteristics, including population, setting, and the provision of pharmacotherapy. To summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary.

METHODS

This work comprises two main elements. 1. We conducted a Cochrane Overview of reviews following standard Cochrane methods. We identified Cochrane Reviews of behavioural interventions (including all non-pharmacological interventions, e.g. counselling, exercise, hypnotherapy, self-help materials) for smoking cessation by searching the Cochrane Library in July 2020. We evaluated the methodological quality of reviews using AMSTAR 2 and synthesised data from the reviews narratively. 2. We used the included reviews to identify randomised controlled trials of behavioural interventions for smoking cessation compared with other behavioural interventions or no intervention for smoking cessation. To be included, studies had to include adult smokers and measure smoking abstinence at six months or longer. Screening, data extraction, and risk of bias assessment followed standard Cochrane methods. We synthesised data using Bayesian component network meta-analysis (CNMA), examining the effects of 38 different components compared to minimal intervention. Components included behavioural and motivational elements, intervention providers, delivery modes, nature, focus, and intensity of the behavioural intervention. We used component network meta-regression (CNMR) to evaluate the influence of population characteristics, provision of pharmacotherapy, and intervention intensity on the component effects. We evaluated certainty of the evidence using GRADE domains. We assumed an additive effect for individual components.

MAIN RESULTS

We included 33 Cochrane Reviews, from which 312 randomised controlled trials, representing 250,563 participants and 845 distinct study arms, met the criteria for inclusion in our component network meta-analysis. This represented 437 different combinations of components. Of the 33 reviews, confidence in review findings was high in four reviews and moderate in nine reviews, as measured by the AMSTAR 2 critical appraisal tool. The remaining 20 reviews were low or critically low due to one or more critical weaknesses, most commonly inadequate investigation or discussion (or both) of the impact of publication bias. Of note, the critical weaknesses identified did not affect the searching, screening, or data extraction elements of the review process, which have direct bearing on our CNMA. Of the included studies, 125/312 were at low risk of bias overall, 50 were at high risk of bias, and the remainder were at unclear risk. Analyses from the contributing reviews and from our CNMA showed behavioural interventions for smoking cessation can increase quit rates, but effectiveness varies on characteristics of the support provided. There was high-certainty evidence of benefit for the provision of counselling (odds ratio (OR) 1.44, 95% credibility interval (CrI) 1.22 to 1.70, 194 studies, n = 72,273) and guaranteed financial incentives (OR 1.46, 95% CrI 1.15 to 1.85, 19 studies, n = 8877). Evidence of benefit remained when removing studies at high risk of bias. These findings were consistent with pair-wise meta-analyses from contributing reviews. There was moderate-certainty evidence of benefit for interventions delivered via text message (downgraded due to unexplained statistical heterogeneity in pair-wise comparison), and for the following components where point estimates suggested benefit but CrIs incorporated no clinically significant difference: individual tailoring; intervention content including motivational components; intervention content focused on how to quit. The remaining intervention components had low-to very low-certainty evidence, with the main issues being imprecision and risk of bias. There was no evidence to suggest an increase in harms in groups receiving behavioural support for smoking cessation. Intervention effects were not changed by adjusting for population characteristics, but data were limited. Increasing intensity of behavioural support, as measured through the number of contacts, duration of each contact, and programme length, had point estimates associated with modestly increased chances of quitting, but CrIs included no difference. The effect of behavioural support for smoking cessation appeared slightly less pronounced when people were already receiving smoking cessation pharmacotherapies.

AUTHORS' CONCLUSIONS

Behavioural support for smoking cessation can increase quit rates at six months or longer, with no evidence that support increases harms. This is the case whether or not smoking cessation pharmacotherapy is also provided, but the effect is slightly more pronounced in the absence of pharmacotherapy. Evidence of benefit is strongest for the provision of any form of counselling, and guaranteed financial incentives. Evidence suggested possible benefit but the need of further studies to evaluate: individual tailoring; delivery via text message, email, and audio recording; delivery by lay health advisor; and intervention content with motivational components and a focus on how to quit. We identified 23 economic evaluations; evidence did not consistently suggest one type of behavioural intervention for smoking cessation was more cost-effective than another. Future reviews should fully consider publication bias. Tools to investigate publication bias and to evaluate certainty in CNMA are needed.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. People who smoke report using ECs to stop or reduce smoking, but some organisations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This review is an update of a review first published in 2014.

OBJECTIVES

To evaluate the effect and safety of using electronic cigarettes (ECs) to help people who smoke achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO for relevant records to January 2020, together with reference-checking and contact with study authors.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and randomized cross-over trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. To be included, studies had to report abstinence from cigarettes at six months or longer and/or data on adverse events (AEs) or other markers of safety at one week or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, AEs, and serious adverse events (SAEs). Secondary outcomes included changes in carbon monoxide, blood pressure, heart rate, blood oxygen saturation, lung function, and levels of known carcinogens/toxicants. We used a fixed-effect Mantel-Haenszel model to calculate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data from these studies in meta-analyses.

MAIN RESULTS

We include 50 completed studies, representing 12,430 participants, of which 26 are RCTs. Thirty-five of the 50 included studies are new to this review update. Of the included studies, we rated four (all which contribute to our main comparisons) at low risk of bias overall, 37 at high risk overall (including the 24 non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.69, 95% confidence interval (CI) 1.25 to 2.27; I2 = 0%; 3 studies, 1498 participants). In absolute terms, this might translate to an additional four successful quitters per 100 (95% CI 2 to 8). There was low-certainty evidence (limited by very serious imprecision) of no difference in the rate of adverse events (AEs) (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs occurred rarely, with no evidence that their frequency differed between nicotine EC and NRT, but very serious imprecision led to low certainty in this finding (RR 1.37, 95% CI 0.77 to 2.41: I2 = n/a; 2 studies, 727 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.71, 95% CI 1.00 to 2.92; I2 = 0%; 3 studies, 802 participants). In absolute terms, this might again lead to an additional four successful quitters per 100 (95% CI 0 to 12). These trials used EC with relatively low nicotine delivery. There was low-certainty evidence, limited by very serious imprecision, that there was no difference in the rate of AEs between these groups (RR 1.00, 95% CI 0.73 to 1.36; I2 = 0%; 2 studies, 346 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.25, 95% CI 0.03 to 2.19; I2 = n/a; 4 studies, 494 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.50, 95% CI 1.24 to 5.04; I2 = 0%; 4 studies, 2312 participants). In absolute terms this represents an increase of six per 100 (95% CI 1 to 14). However, this finding was very low-certainty, due to issues with imprecision and risk of bias. There was no evidence that the rate of SAEs varied, but some evidence that non-serious AEs were more common in people randomized to nicotine EC (AEs: RR 1.17, 95% CI 1.04 to 1.31; I2 = 28%; 3 studies, 516 participants; SAEs: RR 1.33, 95% CI 0.25 to 6.96; I2 = 17%; 5 studies, 842 participants). Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate over time with continued use. Very few studies reported data on other outcomes or comparisons and hence evidence for these is limited, with confidence intervals often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to ECs without nicotine and compared to NRT. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the degree of effect, particularly when using modern EC products. Confidence intervals were wide for data on AEs, SAEs and other safety markers. Overall incidence of SAEs was low across all study arms. We did not detect any clear evidence of harm from nicotine EC, but longest follow-up was two years and the overall number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information for decision-makers, this review is now a living systematic review. We will run searches monthly from December 2020, with the review updated as relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further.

OBJECTIVES

To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy).

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer.

DATA COLLECTION AND ANALYSIS

For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model.

MAIN RESULTS

Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.