Smoking cessation for improving mental health.

There is a common perception that smoking generally helps people to manage stress, and may be a form of 'self-medication' in people with mental health conditions. However, there are biologically plausible reasons why smoking may worsen mental health through neuroadaptations arising from chronic smoking, leading to frequent nicotine withdrawal symptoms (e.g. anxiety, depression, irritability), in which case smoking cessation may help to improve rather than worsen mental health. To examine the association between tobacco smoking cessation and change in mental health. We searched the Cochrane Tobacco Addiction Group's Specialised Register, Cochrane Central Register of Controlled Trials, MEDLINE, Embase, PsycINFO, and the trial registries clinicaltrials.gov and the International Clinical Trials Registry Platform, from 14 April 2012 to 07 January 2020. These were updated searches of a previously-conducted non-Cochrane review where searches were conducted from database inception to 13 April 2012.  SELECTION CRITERIA: We included controlled before-after studies, including randomised controlled trials (RCTs) analysed by smoking status at follow-up, and longitudinal cohort studies. In order to be eligible for inclusion studies had to recruit adults who smoked tobacco, and assess whether they quit or continued smoking during the study. They also had to measure a mental health outcome at baseline and at least six weeks later. We followed standard Cochrane methods for screening and data extraction. Our primary outcomes were change in depression symptoms, anxiety symptoms or mixed anxiety and depression symptoms between baseline and follow-up. Secondary outcomes  included change in symptoms of stress, psychological quality of life, positive affect, and social impact or social quality of life, as well as new incidence of depression, anxiety, or mixed anxiety and depression disorders. We assessed the risk of bias for the primary outcomes using a modified ROBINS-I tool.  For change in mental health outcomes, we calculated the pooled standardised mean difference (SMD) and 95% confidence interval (95% CI) for the difference in change in mental health from baseline to follow-up between those who had quit smoking and those who had continued to smoke. For the incidence of psychological disorders, we calculated odds ratios (ORs) and 95% CIs. For all meta-analyses we used a generic inverse variance random-effects model and quantified statistical heterogeneity using I2. We conducted subgroup analyses to investigate any differences in associations between sub-populations, i.e. unselected people with mental illness, people with physical chronic diseases. We assessed the certainty of evidence for our primary outcomes (depression, anxiety, and mixed depression and anxiety) and our secondary social impact outcome using the eight GRADE considerations relevant to non-randomised studies (risk of bias, inconsistency, imprecision, indirectness, publication bias, magnitude of the effect, the influence of all plausible residual confounding, the presence of a dose-response gradient). We included 102 studies representing over 169,500 participants. Sixty-two of these were identified in the updated search for this review and 40 were included in the original version of the review.  Sixty-three studies provided data on change in mental health, 10 were included in meta-analyses of incidence of mental health disorders, and 31 were synthesised narratively.  For all primary outcomes, smoking cessation was associated with an improvement in mental health symptoms compared with continuing to smoke: anxiety symptoms (SMD -0.28, 95% CI -0.43 to -0.13; 15 studies, 3141 participants; I2 = 69%; low-certainty evidence); depression symptoms: (SMD -0.30, 95% CI -0.39 to -0.21; 34 studies, 7156 participants; I2 = 69%' very low-certainty evidence);  mixed anxiety and depression symptoms (SMD -0.31, 95% CI -0.40 to -0.22; 8 studies, 2829 participants; I2 = 0%; moderate certainty evidence).  These findings were robust to preplanned sensitivity analyses, and subgroup analysis generally did not produce evidence of differences in the effect size among subpopulations or based on methodological characteristics. All studies were deemed to be at serious risk of bias due to possible time-varying confounding, and three studies measuring depression symptoms were judged to be at critical risk of bias overall. There was also some evidence of funnel plot asymmetry. For these reasons, we rated our certainty in the estimates for anxiety as low, for depression as very low, and for mixed anxiety and depression as moderate. For the secondary outcomes, smoking cessation was associated with an improvement in symptoms of stress (SMD -0.19, 95% CI -0.34 to -0.04; 4 studies, 1792 participants; I2 = 50%), positive affect (SMD 0.22, 95% CI 0.11 to 0.33; 13 studies, 4880 participants; I2 = 75%), and psychological quality of life (SMD 0.11, 95% CI 0.06 to 0.16; 19 studies, 18,034 participants; I2 = 42%). There was also evidence that smoking cessation was not associated with a reduction in social quality of life, with the confidence interval incorporating the possibility of a small improvement (SMD 0.03, 95% CI 0.00 to 0.06; 9 studies, 14,673 participants; I2 = 0%). The incidence of new mixed anxiety and depression was lower in people who stopped smoking compared with those who continued (OR 0.76, 95% CI 0.66 to 0.86; 3 studies, 8685 participants; I2 = 57%), as was the incidence of anxiety disorder (OR 0.61, 95% CI 0.34 to 1.12; 2 studies, 2293 participants; I2 = 46%). We deemed it inappropriate to present a pooled estimate for the incidence of new cases of clinical depression, as there was high statistical heterogeneity (I2 = 87%). Taken together, these data provide evidence that mental health does not worsen as a result of quitting smoking, and very low- to moderate-certainty evidence that smoking cessation is associated with small to moderate improvements in mental health.  These improvements are seen in both unselected samples and in subpopulations, including people diagnosed with mental health conditions. Additional studies that use more advanced methods to overcome time-varying confounding would strengthen the evidence in this area.

Taylor GM ，Lindson N ，Farley A ，Leinberger-Jabari A ，Sawyer K ，Te Water Naudé R ，Theodoulou A ，King N ，Burke C ，Aveyard P ... -  《Cochrane Database of Systematic Reviews》

Electronic cigarettes for smoking cessation.

Electronic cigarettes (ECs) are handheld electronic vaping devices that produce an aerosol by heating an e-liquid. 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. To examine the safety, tolerability, and effectiveness of using EC to help people who smoke tobacco achieve long-term smoking abstinence, in comparison to non-nicotine EC, other smoking cessation treatments, and no treatment. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 February 2024 and the Cochrane Tobacco Addiction Group's Specialized Register to 1 February 2023, reference-checked, and contacted study authors. We included trials randomizing people who smoke to an EC or control condition. We included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report an eligible outcome. We followed standard Cochrane methods for screening and data extraction. We used the risk of bias tool (RoB 1) and GRADE to assess the certainty of evidence. Critical outcomes were abstinence from smoking after at least six months, adverse events (AEs), and serious adverse events (SAEs). Important outcomes were biomarkers, toxicants/carcinogens, and longer-term EC use. 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 pairwise and network meta-analyses (NMA). We included 90 completed studies (two new to this update), representing 29,044 participants, of which 49 were randomized controlled trials (RCTs). Of the included studies, we rated 10 (all but one contributing to our main comparisons) at low risk of bias overall, 61 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. Nicotine EC results in increased quit rates compared to nicotine replacement therapy (NRT) (high-certainty evidence) (RR 1.59, 95% CI 1.30 to 1.93; I2 = 0%; 7 studies, 2544 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6 more). The rate of occurrence of AEs is probably similar between groups (moderate-certainty evidence (limited by imprecision)) (RR 1.03, 95% CI 0.91 to 1.17; I2 = 0%; 5 studies, 2052 participants). SAEs were rare, and there is insufficient evidence to determine whether rates differ between groups due to very serious imprecision (RR 1.20, 95% CI 0.90 to 1.60; I2 = 32%; 6 studies, 2761 participants; low-certainty evidence). Nicotine EC probably results in increased quit rates compared to non-nicotine EC (moderate-certainty evidence, limited by imprecision) (RR 1.46, 95% CI 1.09 to 1.96; I2 = 4%; 6 studies, 1613 participants). In absolute terms, this might lead to an additional three quitters per 100 (95% CI 1 to 7 more). There is probably little to no difference in the rate of AEs between these groups (moderate-certainty evidence) (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 840 participants). There is insufficient evidence to determine whether rates of SAEs differ between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 9 studies, 1412 participants; low-certainty evidence). Compared to behavioural support only/no support, quit rates may be higher for participants randomized to nicotine EC (low-certainty evidence due to issues with risk of bias) (RR 1.96, 95% CI 1.66 to 2.32; I2 = 0%; 11 studies, 6819 participants). In absolute terms, this represents an additional four quitters per 100 (95% CI 3 to 5 more). There was some evidence that (non-serious) AEs may be more common in people randomized to nicotine EC (RR 1.18, 95% CI 1.10 to 1.27; I2 = 6%; low-certainty evidence; 6 studies, 2351 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 0.93, 95% CI 0.68 to 1.28; I2 = 0%; 12 studies, 4561 participants; very low-certainty evidence). Results from the NMA were consistent with those from pairwise meta-analyses for all critical outcomes. There was inconsistency in the AE network, which was explained by a single outlying study contributing the only direct evidence for one of the nodes. 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 both clinically significant harm and benefit. 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 or no treatment also suggests benefit, but is less certain due to risk of bias inherent in the study design. Confidence intervals were, for the most part, wide for data on AEs, SAEs, and other safety markers, with no evidence for a difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT, but low-certainty evidence for increased AEs compared with behavioural support/no support. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but longer, larger studies are needed to fully evaluate EC safety. Our included studies tested regulated nicotine-containing EC; illicit products and/or products containing other active substances (e.g. tetrahydrocannabinol (THC)) may have different harm profiles. 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 to decision-makers, this 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.

Lindson N ，Butler AR ，McRobbie H ，Bullen C ，Hajek P ，Wu AD ，Begh R ，Theodoulou A ，Notley C ，Rigotti NA ，Turner T ，Livingstone-Banks J ，Morris T ，Hartmann-Boyce J ... -  《Cochrane Database of Systematic Reviews》

Electronic cigarettes for smoking cessation.

Lindson N ，Butler AR ，McRobbie H ，Bullen C ，Hajek P ，Begh R ，Theodoulou A ，Notley C ，Rigotti NA ，Turner T ，Livingstone-Banks J ，Morris T ，Hartmann-Boyce J ... -  《Cochrane Database of Systematic Reviews》

Strategies to improve smoking cessation rates in primary care.

Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials). To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers. We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020. We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer. We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs). We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation. There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.

Lindson N ，Pritchard G ，Hong B ，Fanshawe TR ，Pipe A ，Papadakis S ... -  《Cochrane Database of Systematic Reviews》

Interventions for quitting vaping.

There is limited guidance on the best ways to stop using nicotine-containing vapes (otherwise known as e-cigarettes) and ensure long-term abstinence, whilst minimising the risk of tobacco smoking and other unintended consequences. Treatments could include pharmacological interventions, behavioural interventions, or both. To conduct a living systematic review assessing the benefits and harms of interventions to help people stop vaping compared to each other or to placebo or no intervention. To also assess how these interventions affect the use of combustible tobacco, and whether the effects vary based on participant characteristics. We searched the following databases from 1 January 2004 to 24 April 2024: CENTRAL; MEDLINE; Embase; PsycINFO; ClinicalTrials.gov (through CENTRAL); World Health Organization International Clinical Trials Registry Platform (through CENTRAL). We also searched the references of eligible studies and abstracts from the Society for Research on Nicotine and Tobacco 2024 conference, and contacted study authors. Randomised controlled trials (RCTs) recruiting people of any age using nicotine-containing vapes, regardless of tobacco smoking status. Studies had to test an intervention designed to support people to quit vaping, and plan to measure at least one of our outcomes. Critical outcomes: vaping cessation; change in combustible tobacco use at six months or longer; number of participants reporting serious adverse events (SAEs) at one week or longer. We used the Cochrane RoB 1 tool to assess bias in the included studies. We followed standard Cochrane methods for screening and data extraction. We grouped studies by comparisons and outcomes reported, and calculated individual study and pooled effects, as appropriate. We used random-effects Mantel-Haenszel methods to calculate risk ratios (RR) with 95% confidence intervals (CI) for dichotomous outcomes. We used random-effects inverse variance methods to calculate mean differences and 95% CI for continuous outcomes. We assessed the certainty of the evidence using the GRADE approach. Nine RCTs, representing 5209 participants motivated to stop using nicotine-containing vapes at baseline, are included. In six studies, participants were abstinent from smoking tobacco cigarettes at baseline, although most studies included some participants who had previously smoked. Eight studies included participants aged 18 or older, three included only young adults (18 to 24 years), and one included 13- to 17-year-olds only. We judged three studies at low risk, three at high risk, and three at unclear risk of bias. Pharmacological interventions for quitting nicotine vaping Studies assessed combination nicotine replacement therapy (NRT), cytisine, and varenicline as pharmacological interventions for quitting vaping in comparison to placebo or no/minimal support (control). The point estimate for combination NRT indicated possible benefit, but the CI incorporated the possibility of no benefit and a potential benefit of control (very low-certainty evidence due to imprecision and risk of bias; RR 2.57, 95% CI 0.29 to 22.93; 1 study, 16 participants). The one study investigating cytisine did not report vaping cessation rates at six months or longer. Varenicline increased vaping cessation rates at six months, but the evidence was low certainty due to imprecision (RR 2.00, 95% CI 1.09 to 3.68; 1 study, 140 participants). Zero participants reported SAEs in the studies of combination NRT versus no/minimal support (1 study, 508 participants; low-certainty evidence due to imprecision) and cytisine versus placebo (1 study, 159 participants; low-certainty evidence due to imprecision). Three studies investigating varenicline measured the number of participants reporting SAEs. However, only one study reported an SAE (in the intervention arm); therefore, the effect estimate was calculated based on that single study (RR 2.60, 95% CI 0.11 to 62.16; 95 participants; low-certainty evidence due to imprecision). Behavioural interventions for quitting nicotine vaping Studies assessed reducing nicotine concentration and vaping behaviour (1 study) and text message-based interventions (3 studies) as behavioural interventions for stopping vaping in comparison to no/minimal support (control). In one study, the point estimate suggested nicotine/vaping reduction increased vaping cessation compared to minimal support at six-month follow-up, but the CI incorporated the possibility of no intervention effect and higher cessation rates in the control arm (RR 3.38, 95% CI 0.43 to 26.30; 17 participants; very low-certainty due to imprecision and risk of bias). There was low-certainty evidence (downgraded two levels due to indirectness) that text message-based interventions may have increased vaping cessation rates compared to control in 13- to 24-year-olds (RR 1.32, 95% CI 1.19 to 1.47; I2 = 0%; 2 studies, 4091 participants). The one study investigating nicotine/vaping behaviour reduction did not report on SAEs. One of the studies investigating text message-based interventions did report on SAEs; however, zero events were reported in both study arms (508 participants; low-certainty evidence due to imprecision). No studies reported change in combustible tobacco smoking at six-month follow-up or longer. There is low-certainty evidence that text message-based interventions designed to help people stop nicotine vaping may help more youth and young adults to successfully stop than no/minimal support, and low-certainty evidence that varenicline may also help people quit vaping. Data exploring the effectiveness of combination NRT, cytisine, and nicotine/vaping behaviour reduction are inconclusive due to risk of bias and imprecision. Most studies that measured SAEs reported none; however, more data are needed to draw clear conclusions. Of note, data from studies investigating these interventions for quitting smoking have not demonstrated serious concerns about SAEs. No studies assessed the change in combustible tobacco smoking, including relapse to or uptake of tobacco smoking, at six-month follow-up or longer. It is important that future studies measure this so the complete risk profile of relevant interventions can be considered. We identified 20 ongoing RCTs. Their incorporation into the evidence base and the continued identification of new studies is imperative to inform clinical and policy guidance on the best ways to stop vaping. Therefore, we will continue to update this review as a living systematic review by running searches monthly and updating the review when relevant new evidence that will strengthen or change our conclusions emerges. Cancer Research UK (PRCPJT-Nov22/100012). National Institute of Health Research (NIHR206123) REGISTRATION: Protocol available via DOI: 10.1002/14651858.CD016058.

Butler AR ，Lindson N ，Livingstone-Banks J ，Notley C ，Turner T ，Rigotti NA ，Fanshawe TR ，Dawkins L ，Begh R ，Wu AD ，Brose L ，Conde M ，Simonavičius E ，Hartmann-Boyce J ... -  《Cochrane Database of Systematic Reviews》