Predictors of adolescent smoking cessation and smoking reduction

Intention to change multiple health risk behaviors and predictors of behavior change in vocational education students

Objective: No studies have examined vocational education students' intention to change multiple health risk behaviors and whether baseline characteristics predict behavior change. Participants: Paticipants were vocational education students in New South Wales, Australia. Methods: Students in the no-intervention control arm of a cluster randomized controlled trial completed an online survey at baseline and 6 months later. Results: Of 450 participants (83.3%) who reported multiple health risk behaviors at baseline, one-third (33.1%) intended to change at least two risk behaviors within 6 months. Participants experiencing symptoms of anxiety [OR = 7.43, 95% CIs 1.26-43.87; p = 0.03] and who intended to change three to four risk behaviors [OR = 23.30, 95% CIs 4.01-135.40; p = 0.001] rather than one behavior had significantly greater odds of changing at least one behavior in 6 months. Conclusions: Interventions could support vocational education students to change behaviors they wish to as well as motivate them to address other risk behaviors.

Temporal associations linking alcohol and cannabis use to cigarette smoking in young adults engaged in a tobacco cessation and relapse monitoring study

Young adulthood remains a developmental period in which cigarette smoking initiation and progression to dependence and regular use is common. Moreover, co-use of alcohol and/or cannabis with tobacco is common in this age group and may have detrimental effects on tobacco use rates and cessation outcomes. Although young adults are interested in quitting smoking, achieving abstinence remains difficult, even with evidence-based treatment strategies. Understanding proximal associations between other substance use (e.g., alcohol and cannabis) and smoking may have important treatment implications. This exploratory analysis investigated the role of alcohol and/or cannabis use in contributing to smoking events on the same day or next day among young adults engaged in a smoking cessation and relapse monitoring study. We used ecological momentary assessment (EMA) data from 43 young adults (ages 18-25; 932 observations) who smoked cigarettes daily and agreed to participate in a 5-week study that included a 2-day smoking quit attempt and provision of tobacco treatment in the form of nicotine replacement therapy, brief cessation counseling, and financial incentives for abstinence (incentives were provided only during the 2-day quit attempt). We tested multilevel time-series models of daily associations between alcohol use, cannabis use, and smoking. Consistent with hypotheses, days on which participants were more likely to drink alcohol predicted increased likelihood of smoking the next day (OR = 2.27, p =.003). This effect was significant after controlling for both the one-day lagged effect of smoking (i.e., autoregression) and the concurrent (i.e., same day) effects of drinking and cannabis use. Although there was a positive concurrent effect of cannabis use on smoking (OR = 12.86, p =.003), the one-day lagged effect of cannabis use and the concurrent effect of drinking was not significant, contrary to hypotheses. Results indicate that alcohol use presents a potential threat to successful smoking cessation that extends to the following day. This suggests a risk-window in which treatment could be supplemented with just-in-time interventions and extending the focus on co-use to include this lagged impact on cessation outcomes.

A Systematic Review of Qualitative Studies on Factors Associated With Smoking Cessation Among Adolescents and Young Adults

OBJECTIVE

To summarize findings from qualitative studies on factors associated with smoking cessation among adolescents and young adults.

DATA SOURCES

We searched Pubmed, Psychinfo, CINAHL, Embase, Web of Science, and SCOPUS databases, as well as reference lists, for peer-reviewed articles published in English or French between January 1, 2000, and November 18, 2020. We used keywords such as adolescents, determinants, cessation, smoking, and qualitative methods.

STUDY SELECTION

Of 1724 records identified, we included 39 articles that used qualitative or mixed methods, targeted adolescents and young adults aged 10-24, and aimed to identify factors associated with smoking cessation or smoking reduction.

DATA EXTRACTION

Two authors independently extracted the data using a standardized form. We assessed study quality using the National Institute for Health and Care Excellence checklist for qualitative studies.

DATA SYNTHESIS

We used an aggregative meta-synthesis approach and identified 39 conceptually distinct factors associated with smoking cessation. We grouped them into two categories: (1) environmental factors [tobacco control policies, pro-smoking norms, smoking cessation services and interventions, influence of friends and family], and (2) individual attributes (psychological characteristics, attitudes, pre-quitting smoking behavior, nicotine dependence symptoms, and other substances use). We developed a synthetic framework that captured the factors identified, the links that connect them, and their associations with smoking cessation.

CONCLUSIONS

This qualitative synthesis offers new insights on factors related to smoking cessation services, interventions, and attitudes about cessation (embarrassment when using cessation services) not reported in quantitative reviews, supplementing limited evidence for developing cessation programs for young persons who smoke.

IMPLICATIONS

Using an aggregative meta-synthesis approach, this study identified 39 conceptually distinct factors grouped into two categories: Environmental factors and individual attributes. These findings highlight the importance of considering both environmental and individual factors when developing smoking cessation programs for young persons who smoke. The study also sheds light on self-conscious emotions towards cessation, such as embarrassment when using cessation services, which are often overlooked in quantitative reviews. Overall, this study has important implications for developing effective smoking cessation interventions and policies that address the complex factors influencing smoking behavior among young persons.

Factors associated with long-term smoking relapse in those who succeeded in smoking cessation using regional smoking cessation programs

It is known that approximately 10% of successful quitters relapse annually. This study aimed to investigate the factors related to long-term smoking relapse in individuals who succeeded in maintaining smoking cessation for 6 months after attending a regional smoking cessation program. This study enrolled 943 individuals registered for the regional smoking cessation program at the Busan Smoking Cessation Center in 2018-2019 who maintained smoking cessation for 6 months. A survey was conducted using a smartphone link or through phone calls, and the data for 305 participants who finally completed the survey were analyzed. The questionnaire addressed individual, inter-individual, organizational, and community-level factors related to smoking relapse. Multivariate logistic regression analysis was performed to evaluate the factors associated with smoking relapse by period. The Cox proportional hazard regression model was used for the factors associated with smoking relapse for the entire period. The smoking relapse rate at the time of the survey was 25.4%. In the analysis of smoking relapse by period, relapse was associated with the belief that smoking relieves stress, the number of single-person households, and poor subjective health status. In the analysis of smoking relapse during the entire period, we observed a significant association with the belief that smoking relieves stress (hazard ratio [HR]: 2.65, 95% confidence interval [CI]: 1.52-4.61), single-person households (HR: 1.95, 95% CI: 1.16-3.26), and high levels of emotional stress (HR: 1.72, 95% CI: 1.04-2.85). Long-term follow-up is necessary to prevent smoking relapse in single-person households, individuals who believe that smoking relieves stress, and those experiencing high levels of subjective emotional stress. Interventional therapies for stress relief and awareness improvement in smokers need to be developed.

The Effect of Fear of COVID-19 on Smoking Cessation

Aim: We aimed to investigate the relationship between fear of COVID-19 and smoking cessation success. Methods: The study is an observational analytic study. It was conducted prospectively and we included people who applied to the smoking cessation outpatient clinic between 01 Oct 2020 and 31 Oct 2020 and agreed to participate in the study. A questionnaire prepared by the researchers, the Fear of COVID-19 Scale, and the Fagerström Test for Nicotine Dependence were applied to the participants. When necessary treatments had been initiated, a particular date is determined for each participant as a smoking cessation date. Participants were called in the 1st month and 3rd months from the smoking cessation day to enquire whether they quit smoking. Results: A total of 222 people participated in this study. The mean score of the Fear of COVID-19 Scale was calculated as 18.77±6.45. The success rate of smoking cessation in the 3rd month was 55% (n=122). No significant relationship was found between smoking cessation success and the score of the Fear of COVID-19 Scale. Conclusion: Although we cannot associate it with the fear of COVID-19 alone, we believe that the pandemic increases the success of early smoking cessation. To maintain these success rates, it is important to provide adequate support to the patients. Keywords: COVID-19, fear, smoking cessation, tobacco smoking

Multivariate Analysis of the Predicted Probability of Smoking Behavior of Foster Care Minors: Results of a Study from Romania

Background: There are a multitude of factors that influence smoking status, and minors from the social protection system are a vulnerable category in terms of smoking. Methods: The objective of this research was to assess the degree of smoking dependence and to identify potential predictors of smoking status in foster care teenagers. Smoker status was confirmed by dosing CO in the exhaled air, and the degree of dependence was assessed using the Fagerström score. We performed a multivariate logistic regression analysis. Results: From the 275 foster care minors, 22.5% were current smokers. Exhaled CO was not influenced by general demographic factors, was associated with the frequency of smoking, and was positively correlated with the estimated number of cigarettes consumed daily and with the Fagerström score. The calculated probability of being a smoker was less than 20.4% in 75% of nonsmokers, whereas 75% of actual smokers had a predicted probability higher than 30.3%. Conclusions: In addition to age, gender, social environment, previous exposure to secondhand smoking, and residential type of foster care system, the expressed opinions regarding the health effects of tobacco use were associated with smoking in foster care teenagers.

Smoking cessation among adolescents in Europe: The role of school policy and programmes

INTRODUCTION

European estimates of adolescent smoking cessation are lacking and studies on the role of schools in quit behaviour are scarce. We aimed to describe smoking cessation attempts and success among adolescents in Europe and explored the association with school policy and programmes.

METHODS

We used cross-sectional data from the 2013 and 2016-2017 surveys of the European SILNE and SILNE-R projects. We included 4,509 12-19-year-old current or ex-smokers in 67 secondary schools in seven countries (Belgium, Germany, Finland, Ireland, Italy, the Netherlands, and Portugal). School staff reported strength of smoke-free school policies (SFSPs), proportion of grades in which anti-tobacco education was offered, and whether the school offered any form of cessation support programme. Multilevel logistic regression analysis determined school-level variation and the association of school-level and individual-level variables with self-reported and self-defined quit attempts and quit success.

RESULTS

Over three quarters (77.3%) of students reported a quit attempt and half of them (50.1%) reported quit success. Prevalence rates of quit success and quit attempts, showed relatively small variations between schools within countries. Associations of smoke-free school policy, tobacco educational programmes and cessation programmes with quit attempts and quit success could not be demonstrated with statistical significance. Quit attempts and quit success were inversely associated with alcohol use, parental smoking, and friend smoking.

CONCLUSION

This study demonstrates that adolescence is an important time to encourage quitting and to support quit attempts. We did not find evidence for a contribution of school policies and programmes to quit behaviour of adolescent smokers.

New Biomarkers Based on Smoking-Related Phenotypes for Smoking Cessation Outcomes of Nicotine Replacement Therapy: A Prospective Study

Introduction:

Identifying a potent biomarker for smoking cessation can play a key role in predicting prognosis and improving treatment outcomes. This study aimed to evaluate the contribution of new biomarkers based on the levels of Cotinine (Cot) and carbon monoxide (CO) to the short- and long-term quit rates of nicotine replacement therapies (Nicotine Patch [NP] and Nicotine Lozenge [NL]).

Methods:

In this prospective interventional study, 124 smokers under treatment with the 5A’s method were selected from an outpatient smoking cessation center in district 18 of Tehran City, Iran. The study was conducted from April 2016 to December 2018. They were divided into NP (n=56) and NL (n=61) intervention groups. The levels of Cot and CO were measured using ELISA and breath analysis at the beginning of the study. Three markers were calculated: Cot/CO, Cot to cigarette per day ratio (Cot/CPD), and CO/CPD. Binary logistic regression models and generalized estimating equations models were analyzed by SPSS software, version 21 to determine the chances of quitting smoking.

Results:

Of the NP participants, 30.4% and 19.6% were abstinent after 2 and 6 months, respectively, while NL was found less effective with 19.7% for 2-month follow-up and 13.1% for 6-month follow-up. The 6-month success of quitting attempts was significantly different for the NP participants at the second half of Cot/CO (P=0.029). Of the NL participants, CO/CPD would be a superior predictor for smoking cessation success (P>0.05).

Conclusion:

The findings of this study suggested two markers of Cot/CO and CO/CPD in this order for the optimum treatment outcomes of NP and NL.

Addressing concerns about smoking cessation and mental health: theoretical review and practical guide for healthcare professionals

Smoking rates in people with depression and anxiety are twice as high as in the general population, even though people with depression and anxiety are motivated to stop smoking. Most healthcare professionals are aware that stopping smoking is one of the greatest changes that people can make to improve their health. However, smoking cessation can be a difficult topic to raise. Evidence suggests that smoking may cause some mental health problems, and that the tobacco withdrawal cycle partly contributes to worse mental health. By stopping smoking, a person's mental health may improve, and the size of this improvement might be equal to taking anti-depressants. In this theoretical review and practical guide we outline ways in which healthcare professionals can raise the topic of smoking compassionately and respectfully to encourage smoking cessation. We draw on evidence-based methods like cognitive behavioural therapy, and outline approaches that healthcare professionals can use to integrate these methods into routine care.

Knowledge, attitude, and implementation of nicotine replacement therapy by dental and medical interns in Davangere city: A cross-sectional survey

Background:

One of the prime causes of illness and premature death is smoking. Almost 50% of smokers attempt to quit the habit; however, at most, 2%–3% achieve success. The rationale is that innumerable withdrawal attempts are unplanned, and the most effective cessation aids are unacquainted. Nicotine replacement therapy (NRT) is the most common cessation aid. Furthermore, motivation from dental and medical professionals can be effective for patients to quit smoking. The study aimed to assess the knowledge, attitude, and practice regarding the implementation of NRT among dental and medical interns in Davangere city.

Materials and Methods:

A questionnaire-based survey was conducted, which included 442 dental and medical interns from two dental and two medical colleges in Davangere city, Karnataka. The questionnaire included multiple-choice questions regarding knowledge, attitude, and implementation of NRT. The response rate of interns was 93.67%.

Results:

Among dental and medical interns, there was no statistically significant difference in knowledge about NRT with P = 0.976 (P > 0.05). However, a statistically significant difference existed regarding attitude and implementation in the interns about NRT among dental and medical interns with P = 0.001 (P < 0.05). Among dental and medical interns, dental interns had a positive attitude and implementation toward NRT than medical interns.

Conclusion:

The overview implicated that the dental interns had better vision than medical interns; however, both the groups' comprehension concerning NRT is scanty and advocates education about the fundamentals of NRT either via workshop or by continuing dental education programs.

Cannabis and Alcohol Co-Use in a Smoking Cessation Pharmacotherapy Trial for Adolescents and Emerging Adults

INTRODUCTION

The co-use of cannabis and alcohol among tobacco-using youth is common. Alcohol co-use is associated with worse tobacco cessation outcomes, but results are mixed regarding the impact of cannabis on tobacco outcomes and if co-use leads to increased use of non-treated substances. This secondary analysis from a youth smoking cessation trial aimed to (1) evaluate the impact of cannabis or alcohol co-use on smoking cessation, (2) examine changes in co-use during the trial, and (3) explore secondary effects of varenicline on co-use.

METHODS

The parent study was a 12-week, randomized clinical trial of varenicline for smoking cessation among youth (ages 14-21, N = 157; Mage = 19, 40% female; 76% White). Daily cigarette, cannabis, and alcohol use data were collected via daily diaries during treatment and Timeline Follow-back for 14 weeks post-treatment.

RESULTS

Baseline cannabis co-users (68%) had double the odds of continued cigarette smoking throughout the trial compared with noncannabis users, which was pronounced in males and frequent cannabis users. Continued smoking during treatment was associated with higher probability of concurrent cannabis use. Baseline alcohol co-users (80%) did not have worse smoking outcomes compared with nonalcohol users, but continued smoking was associated with higher probability of concurrent drinking. Varenicline did not affect co-use.

CONCLUSIONS

Inconsistent with prior literature, results showed that alcohol co-users did not differ in smoking cessation, whereas cannabis co-users had poorer cessation outcomes. Youth tobacco treatment would benefit from added focus on substance co-use, particularly cannabis, but may need to be tailored appropriately to promote cessation.

IMPLICATIONS

Among youth cigarette smokers enrolled in a pharmacotherapy evaluation clinical trial, alcohol and/or cannabis co-use was prevalent. The co-use of cannabis affected smoking cessation outcomes, but more so for males and frequent cannabis users, whereas alcohol co-use did not affect smoking cessation. Reductions in smoking were accompanied by concurrent reductions in alcohol or cannabis use. Substance co-use does not appear to affect all youth smokers in the same manner and treatment strategies may need to be tailored appropriately for those with lower odds of smoking cessation.

Effect of Additional Motivational Interviewing on Smoking Abstinence for 1-Year among Korean Adolescents: Results from A Comparative Retrospective Study in Quitline

The aim of this study was to evaluate the effect of additional motivational enhancement through telephone-based counseling on short- and long-term smoking abstinence among Korean adolescents.

METHODS

A comparative retrospective study was conducted based on the longitudinal follow up in Quitline from 2010 to 2017. A total of 533 and 178 adolescent smokers voluntarily participated in the 1-year quitting counseling only (group A, who were ready to quit) and the additional 4-week motivational interviewing before 1-year quitting counseling (group B, who were ambivalent about quitting), respectively. The outcomes were self-reported continuous abstinence at 30-day, 6-month, and 1-year follow up. Logistic regression was applied to estimate the effect of potential factors, including motivational enhancement, on cessation outcome.

RESULTS

At baseline, adolescents in group B had a lower motivation to quit than those in group A (p < 0.001). The successful quit rates at 30-day, 6-month, and 1-year follow up were 37.2%, 12.8%, and 11.4% in group A and 33.7%, 15.2%, and 11.2% in group B, respectively. After adjusting factors as appropriate, successful quit rates in group B were not significantly different from the rates in group A. Higher self-efficacy increased the successful quit rate at 30-day, 6-month, and 1-year follow up, similar in subgroup analysis by gender. Never-drinking showed significant association with 30-day successful quit in the whole population and among boys. The lower number of smoking triggers was associated with an increased 30-day successful quit rate among boys only.

CONCLUSIONS

Counseling for motivational enhancement could be a promising approach for better quitting outcomes. Improving self-efficacy and eliminating smoking triggers should be continuously strengthened during the quitting process.

Predictors of Smoking Cessation in a Lifestyle-Focused Text-Message Support Programme Delivered to People with Coronary Heart Disease: An Analysis From the Tobacco Exercise and Diet Messages (TEXTME) Randomised Clinical Trial

Background:

Studies have demonstrated the effectiveness of text message-based prevention programs on smoking cessation, including our recently published TEXTME randomised controlled trial. However, little is known about the predictors of smoking cessation in this context and if other clinically important factors interact with the program to lead to quitting. Hence, the objective of this study was to first assess the predictors of smoking cessation in TEXTME and then determine if the effect of texting on quitting was modified by interactions with important clinical variables. This will allow us to better understand how text messaging works and thus help optimise future text-message based prevention programs.

Methods

This sub-analysis used data collected as part of the TEXTME trial which recruited 710 participants (377 current smokers at baseline) between September 2011 and November 2013 from a large tertiary hospital in Sydney, Australia. Smokers at baseline were analysed at 6 months and grouped into those who quit and those who did not. Univariate analyses were performed to determine associations between the main outcome and clinically important baseline factors selected a priori. A multiple binominal logistic regression analysis was conducted to develop a predictive model for the dependent variable smoking cessation. A test of interaction between the intervention group and baseline variables selected a priori with the outcome smoking cessation was performed.

Results

Univariate analysis identified receiving text-messages, age, and mean number of cigarettes smoked each day as being associated with quitting smoking. After adjusting for age, receiving the text-messaging program (OR 2.34; 95%CI 1.43-3.86; p<0.01) and mean number of cigarettes smoked per day (OR 1.02; 95%CI 1.00-1.04; p=0.03) were independent predictors for smoking cessation. LDL-C showed a significant interaction effect with the intervention (High LDL*Intervention OR 3.77 (95%CI 2.05-6.94); Low LDL*Intervention OR 1.42 (95%CI 0.77-2.60); P=0.03).

Conclusions

Smoking quantity at baseline is independently associated with smoking cessation and higher LDL-C may interact with the intervention to result in quitting smoking. Those who have a higher baseline risk maybe more motivated towards beneficial lifestyle change including quitting smoking, and thus more likely to respond to mHealth smoking cessation programs. The effect of text-messages on smoking cessation was independent of age, gender, psychosocial parameters, education, and baseline control of risk factors in a secondary prevention cohort.

Predictors of long-term smoking cessation among smokers enrolled in a university smoking cessation program: A longitudinal study

Many lifelong smokers establish smoking habits during young adulthood. A university can be an effective setting for early smoking cessation. We evaluated long-term predictors of smoking cessation among smokers in a university setting.We longitudinally followed a cohort of smokers enrolled in a university smoking cessation program in Seoul, South Korea. Sociodemographic factors, smoking-related variables, and changes in smoking habits were assessed during 6-week visit sessions and follow-up telephone interviews conducted 1 year or more later.A total of 205 participants were followed up (mean follow-up duration: 27.1 months). Cessation rates were 47.3% at the end of the visit sessions and 28.8% at follow-up. The long-term persistent smoking rate was significantly higher among individuals with peers who smoked (odds ratio [OR] = 8.64; 95% confidence interval [CI] = 1.75, 42.80), with family members who smoked (OR = 3.28; 95% CI = 1.20, 9.00), and who smoked 10 to 19 cigarettes/day (OR = 4.83; 95% CI = 1.49, 15.69). Conversely, persistent smoking was less likely among those who attended the program regularly (OR = 0.84 per visit; 95% CI = 0.72, 0.99) and attempted quitting more frequently (OR = 0.93 per attempt; 95% CI = 0.87, 0.99). Use of smoking cessation medications (varenicline or bupropion) was not significantly associated with long-term quitting (OR = 0.71; 95% CI = 0.26, 1.93).Peer influences were the strongest predictors of failure in long-term cessation among smokers who attempted to quit. Similarly, the existence of smokers in the family was negatively associated with successful quitting. Regular attendance at a smoking cessation program and a high number of attempts to quit were positively associated with successful quitting. Targeting peer and family smoking groups together rather than targeting individual smokers alone, implementing active cessation programs encouraging regular attendance, and providing comprehensive antismoking environments might be effective strategies in a university setting.

Mobile phone text messaging and app-based interventions for smoking cessation

BACKGROUND

Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

SEARCH METHODS

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

SELECTION CRITERIA

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

MAIN RESULTS

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I² = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I² = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I² = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I² = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I² = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Factors associated with quit attempts and smoking cessation in Brazil: findings from the International Tobacco Control Brazil Survey

OBJECTIVES

This study aimed to identify factors associated with attempting to quit and successful smoking cessation in a population-based sample of Brazilian smokers.

STUDY DESIGN

This is a prospective cohort study.

METHODS

Data came from the first two waves of the International Tobacco Control Brazil Survey, conducted in 2009 and 2012/2013 in three cities: Rio de Janeiro, São Paulo, and Porto Alegre. Data were collected from 488 adults (aged ≥18 years) who smoked at Wave 1 and who were resurveyed at Wave 2. Crude and adjusted relative risks for two outcomes (making a quit attempt between Wave 1 and Wave 2 and successfully quitting by Wave 2) were estimated. Multivariable multilevel logistic regression models were used, whereby variables were added to the models in a series of blocks.

RESULTS

Nearly two-thirds (65.6%) of smokers attempted to quit between waves, and 23.4% had quit at Wave 2. Intention to quit smoking at Wave 1 was the only variable associated with attempt to quit by Wave 2 (odds ratio [OR] = 2.85; 95% confidence interval [CI] 1.64-4.94; P < 0.001). Smokers of higher socio-economic status (OR high versus low = 1.80; 95% CI 1.05-3.10; P = 0.03) and lower nicotine dependence (OR low Heaviness of Smoking Index [HSI] versus high HSI = 1.94; 95% CI 1.10-3.43; P = 0.02) were more likely to successfully quit. The presence of another adult smoker at home was negatively related to successful quitting (OR = 0.50; 95% CI 0.26-0.94; P = 0.03).

CONCLUSIONS

These results are generally consistent with prior research and have potential to inform governmental interventions to promote tobacco cessation, particularly among disadvantaged groups.

A systematic review of anxiety across smoking stages in adolescents and young adults

BACKGROUND

In adolescence and young adults, inconsistence of the association between anxiety and smoking remains to be investigated and clarified. The aim of this study is investigated and clarified the association between anxiety and smoking stages in adolescence and young adults.

METHODS

The data on the causal influence of anxiety on smoking in adolescents and young adults aged 14 to 25 years old was retrieved from electronic databases.

RESULTS

Nineteen of 668 articles were subjected to a systematic review. Definitional differences with respect to smoking stages constrained homogeneity across the nineteen analyzed reports. Anxiety appears to play a more consistent risk role for nicotine dependent (ND) smokers than for non-nicotine dependent (non-ND) regular or daily smokers. Anxious non-ND smokers are at higher risk to become nicotine dependent.

CONCLUSIONS

A ununified definition of smoking stages is responsible for the production of inconsistent results. The analysis reinforced anxiety as a significant risk factor for smoking in one's lifetime. Anxious non-ND smokers are the key target for interventions aimed at preventing nicotine dependence and smoking-related health problems.

Tobacco cessation interventions for young people

BACKGROUND

Most tobacco control programmes for adolescents are based around prevention of uptake, but teenage smoking is still common. It is unclear if interventions that are effective for adults can also help adolescents to quit. This is the update of a Cochrane Review first published in 2006.

OBJECTIVES

To evaluate the effectiveness of strategies that help young people to stop smoking tobacco.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register in June 2017. This includes reports for trials identified in CENTRAL, MEDLINE, Embase and PsyclNFO.

SELECTION CRITERIA

We included individually and cluster-randomized controlled trials recruiting young people, aged under 20 years, who were regular tobacco smokers. We included any interventions for smoking cessation; these could include pharmacotherapy, psycho-social interventions and complex programmes targeting families, schools or communities. We excluded programmes primarily aimed at prevention of uptake. The primary outcome was smoking status after at least six months' follow-up among those who smoked at baseline.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed the eligibility of candidate trials and extracted data. We evaluated included studies for risk of bias using standard Cochrane methodology and grouped them by intervention type and by the theoretical basis of the intervention. Where meta-analysis was appropriate, we estimated pooled risk ratios using a Mantel-Haenszel fixed-effect method, based on the quit rates at six months' follow-up.

MAIN RESULTS

Forty-one trials involving more than 13,000 young people met our inclusion criteria (26 individually randomized controlled trials and 15 cluster-randomized trials). We judged the majority of studies to be at high or unclear risk of bias in at least one domain. Interventions were varied, with the majority adopting forms of individual or group counselling, with or without additional self-help materials to form complex interventions. Eight studies used primarily computer or messaging interventions, and four small studies used pharmacological interventions (nicotine patch or gum, or bupropion). There was evidence of an intervention effect for group counselling (9 studies, risk ratio (RR) 1.35, 95% confidence interval (CI) 1.03 to 1.77), but not for individual counselling (7 studies, RR 1.07, 95% CI 0.83 to 1.39), mixed delivery methods (8 studies, RR 1.26, 95% CI 0.95 to 1.66) or the computer or messaging interventions (pooled RRs between 0.79 and 1.18, 9 studies in total). There was no clear evidence for the effectiveness of pharmacological interventions, although confidence intervals were wide (nicotine replacement therapy 3 studies, RR 1.11, 95% CI 0.48 to 2.58; bupropion 1 study RR 1.49, 95% CI 0.55 to 4.02). No subgroup precluded the possibility of a clinically important effect. Studies of pharmacotherapies reported some adverse events considered related to study treatment, though most were mild, whereas no adverse events were reported in studies of behavioural interventions. Our certainty in the findings for all comparisons is low or very low, mainly because of the clinical heterogeneity of the interventions, imprecision in the effect size estimates, and issues with risk of bias.

AUTHORS' CONCLUSIONS

There is limited evidence that either behavioural support or smoking cessation medication increases the proportion of young people that stop smoking in the long-term. Findings are most promising for group-based behavioural interventions, but evidence remains limited for all intervention types. There continues to be a need for well-designed, adequately powered, randomized controlled trials of interventions for this population of smokers.

Physical Activity and Quit Motivation Moderators of Adolescent Smoking Reduction

OBJECTIVES

We examined participant characteristics as moderators of adolescents' smoking cessation outcomes as a function of intervention: Not-on-Tobacco (N-O-T), N-O-T with a physical activity (PA) module (N-O-T+FIT), or Brief Intervention (BI).

METHODS

We randomly assigned youth (N = 232) recruited from public high schools to an intervention, and measured their baseline levels of PA and motivation to quit. The number of cigarettes/day for weekdays and weekends was obtained at baseline and 3-month follow-up.

RESULTS

Across timepoints, cigarette use declined for youth in N-O-T (p = .007) and N-O-T+FIT (ps < .02), but not BI (n.s.). For N-O-T+FIT youth, the steepest declines in weekday smoking occurred for those with high PA levels (p = .02). Weekend cigarette use decreased for N-O-T+FIT youth with moderate-high levels of intrinsic motivation to quit (ps < .04).

CONCLUSIONS

Adolescents may benefit from interventions designed to address the barriers faced during a quit attempt, including their motivation to make a change and their engagement in other healthy behaviors such as physical activity.

[Structural Equation Modeling on Smoking Cessation Intention in Male Technical High School Students]

PURPOSE

This study was done to develop and test a structural model on smoking cessation intention in technical high school men. The conceptual model was based on the theory of reasoned action and health promotion model.

METHODS

From May 29 to April 13, 2015, 413 technical high school students who smoked completed a structured questionnaire. Data were analyzed to calculate the direct and indirect effects of factors affecting smoking cessation intention. The SPSS WIN 20.0 and AMOS 21.0 programs were used.

RESULTS

The hypothetical model was a good fit for the data. The model fit indices were χ²/df=2.36, GFI=.95, AGFI=.92, NFI=0.97, and RMSEA=.05. Self-esteem had direct and indirect effects on smoking cessation intention. Attitude, subjective norm, and self-efficacy had direct effects on smoking cessation intention. Smoking knowledge and environmental factor had indirect effects on smoking cessation intention. This model explained 87.0% of the variance in smoking cessation intention.

CONCLUSION

These results indicate that technical high school students' intention to stop smoking can be improved through an increase in self-esteem, negative environmental factors, attitude toward smoking cessation, subjective norm about smoking cessation, and self-efficacy for smoking cessation.

Cigarette Smoking Reduction in Pregnant Women With Opioid Use Disorder

OBJECTIVES

Nearly 95% of women with opioid use disorder continue to smoke cigarettes during pregnancy. Despite this prevalence and the well documented adverse effects of smoking on birth outcomes, cigarette smoking is underaddressed in this population. This study examines factors associated with successful smoking reduction among pregnant women with opioid use disorder and the impact of smoking reduction on maternal and birth outcomes.

METHODS

This study is a secondary data analysis of maternal smoking reduction and infant birth outcomes among pregnant women with opioid use disorder (N = 118), enrolled in a randomized controlled trial of a contingency management intervention in which escalating monetary vouchers were provided to women who met escalating smoking-reduction targets.

RESULTS

Participants' ability to meet higher smoking reduction targets was associated with less cocaine use at baseline (P = 0.022), higher carbon monoxide levels at baseline (P = 0.039), fewer prior quit attempts (P = 0.016), participation in the contingency management intervention, and greater adherence with the parent trial protocol. Some clinically relevant associations were found between smoking reduction and birth outcomes, including birth weight, spontaneous abortions, and neonatal abstinence syndrome treatment, but these differences did not reach statistical significance.

CONCLUSIONS

Contingency management promotes smoking reduction, but other factors may be associated with such reduction, including baseline smoking and illicit drug use, prior quit attempts, and willingness to participate in the incentives program. Clinicians caring for pregnant women with opioid use disorder may see greater smoking behavior change if they first encourage smoking reduction before recommending smoking cessation. Future research is needed to determine the level of smoking reduction needed to positively impact birth outcomes.

Text Messaging-Based Interventions for Smoking Cessation: A Systematic Review and Meta-Analysis

BACKGROUND

Tobacco use is one of the leading preventable global health problems producing nearly 6 million smoking-related deaths per year. Interventions delivered via text messaging (short message service, SMS) may increase access to educational and support services that promote smoking cessation across diverse populations.

OBJECTIVE

The purpose of this meta-analysis is to (1) evaluate the efficacy of text messaging interventions on smoking outcomes, (2) determine the robustness of the evidence, and (3) identify moderators of intervention efficacy.

METHODS

Electronic bibliographic databases were searched for records with relevant key terms. Studies were included if they used a randomized controlled trial (RCT) to examine a text messaging intervention focusing on smoking cessation. Raters coded sample and design characteristics, and intervention content. Summary effect sizes, using random-effects models, were calculated and potential moderators were examined.

RESULTS

The meta-analysis included 20 manuscripts with 22 interventions (N=15,593; 8128 (54%) women; mean age=29) from 10 countries. Smokers who received a text messaging intervention were more likely to abstain from smoking relative to controls across a number of measures of smoking abstinence including 7-day point prevalence (odds ratio (OR)=1.38, 95% confidence interval (CI)=1.22, 1.55, k=16) and continuous abstinence (OR=1.63, 95% CI=1.19, 2.24, k=7). Text messaging interventions were also more successful in reducing cigarette consumption relative to controls (d+=0.14, 95% CI=0.05, 0.23, k=9). The effect size estimates were biased when participants who were lost to follow-up were excluded from the analyses. Cumulative meta-analysis using the 18 studies (k=19) measuring abstinence revealed that the benefits of using text message interventions were established only after only five RCTs (k=5) involving 8383 smokers (OR=1.39, 95% CI=1.15, 1.67, P<.001). The inclusion of the subsequent 13 RCTs (k=14) with 6870 smokers did not change the established efficacy of text message interventions for smoking abstinence (OR=1.37, 95% CI=1.25, 1.51, P<.001). Smoking abstinence rates were stronger when text messaging interventions (1) were conducted in Asia, North America, or Europe, (2) sampled fewer women, and (3) recruited participants via the Internet.

CONCLUSIONS

The evidence for the efficacy of text messaging interventions to reduce smoking behavior is well-established. Using text messaging to support quitting behavior, and ultimately long-term smoking abstinence, should be a public health priority.

Mobile phone-based interventions for smoking cessation

BACKGROUND

Access to mobile phones continues to increase exponentially globally, outstripping access to fixed telephone lines, fixed computers and the Internet. Mobile phones are an appropriate and effective option for the delivery of smoking cessation support in some contexts. This review updates the evidence on the effectiveness of mobile phone-based smoking cessation interventions.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation in people who smoke and want to quit.

SEARCH METHODS

For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialised Register in April 2015. We also searched the UK Clinical Research Network Portfolio for current projects in the UK, and the ClinicalTrials.gov register for ongoing or recently completed studies. We searched through the reference lists of identified studies and attempted to contact the authors of ongoing studies. We applied no restrictions on language or publication date.

SELECTION CRITERIA

We included randomised or quasi-randomised trials. Participants were smokers of any age who wanted to quit. Studies were those examining any type of mobile phone-based intervention for smoking cessation. This included any intervention aimed at mobile phone users, based around delivery via mobile phone, and using any functions or applications that can be used or sent via a mobile phone.

DATA COLLECTION AND ANALYSIS

Review authors extracted information on risk of bias and methodological details using a standardised form. We considered participants who dropped out of the trials or were lost to follow-up to be smoking. We calculated risk ratios (RR) and 95% confidence intervals (CI) for each included study. Meta-analysis of the included studies used the Mantel-Haenszel fixed-effect method. Where meta-analysis was not possible, we presented a narrative summary and descriptive statistics.

MAIN RESULTS

This updated search identified 12 studies with six-month smoking cessation outcomes, including seven studies completed since the previous review. The interventions were predominantly text messaging-based, although several paired text messaging with in-person visits or initial assessments. Two studies gave pre-paid mobile phones to low-income human immunodeficiency virus (HIV)-positive populations - one solely for phone counselling, the other also included text messaging. One study used text messages to link to video messages. Control programmes varied widely. Studies were pooled according to outcomes - some providing measures of continuous abstinence or repeated measures of point prevalence; others only providing 7-day point prevalence abstinence. All 12 studies pooled using their most rigorous 26-week measures of abstinence provided an RR of 1.67 (95% CI 1.46 to 1.90; I(2) = 59%). Six studies verified quitting biochemically at six months (RR 1.83; 95% CI 1.54 to 2.19).

AUTHORS' CONCLUSIONS

The current evidence supports a beneficial impact of mobile phone-based smoking cessation interventions on six-month cessation outcomes. While all studies were good quality, the fact that those studies with biochemical verification of quitting status demonstrated an even higher chance of quitting further supports the positive findings. However, it should be noted that most included studies were of text message interventions in high-income countries with good tobacco control policies. Therefore, caution should be taken in generalising these results outside of this type of intervention and context.

Smoking Cessation Failure Among Korean Adolescents

The aim of this study was to identify smoking cessation failure subgroups among Korean adolescents. Participants were 379 smoking adolescents who joined a smoking cessation program. A questionnaire and a cotinine urine test were administered before the program began. Three months after the program ended, the cotinine urine test was repeated. A decision-tree model identified seven subgroups with low or high smoking cessation rates. The predictors of smoking cessation were intention to stop smoking, initiation of smoking, amount of cigarette use, self-efficacy, and paternal smoking status. The subgroup with the lowest smoking cessation rate included adolescents who did not have any intention to stop smoking and who had started smoking after eighth grade, and none of the participants in this group stopped smoking. The results of this study provide crucial information for tailored smoking cessation programs.

Biomarkers of Response to Smoking Cessation Pharmacotherapies: Progress to Date

For the past 30 years, research examining predictors of successful smoking cessation treatment response has focused primarily on clinical variables, such as levels of tobacco dependence, craving, and self-efficacy. However, recent research has begun to determine biomarkers (such as genotype, nicotine and metabolite levels, and brain imaging findings) that may have utility in predicting smoking cessation. For genotype, genes associated with nicotinic acetylcholine receptors (nAChRs) and related proteins have been found to predict response to first-line medications (e.g. nicotine replacement therapy [NRT], bupropion, or varenicline) or quitting over time without a controlled treatment trial. For nicotine and metabolite levels, function of the cytochrome P450 2A6 liver enzyme, which can be assessed with the nicotine metabolite ratio or via genotype, has been found to predict response, with slow nicotine metabolizers having less severe nicotine dependence and a greater likelihood of quitting with NRT than normal metabolizers. For brain imaging, decreased activation of brain regions associated with emotion regulation and increased connectivity in emotion regulation networks, increased responsiveness to pleasant cues, and altered activation with the Stroop effect have been found in smokers who quit with the first-line medications listed above or counseling. In addition, our group recently demonstrated that lower pre-treatment brain nAChR density is associated with a greater chance of quitting smoking with NRT or placebo. Several of these studies found that specific biomarkers may provide additional information for predicting response beyond subjective symptom or rating scale measures, thereby giving an initial indication that biomarkers may, in the future, be useful for guiding smoking cessation treatment intensity, duration, and type.