Predictors of early versus late smoking abstinence within a 24-month disease management program

Association Between Comorbid Psychiatric Disorders and Persistent Smoking After a Diagnosis of Chronic Obstructive Pulmonary Disease Among Patients Seeking Treatment at a Tertiary Care Hospital in India

Introduction Smoking cessation is the most effective approach to slowing down the progression of chronic obstructive pulmonary disease (COPD). Despite this, almost half of COPD patients continue to smoke after diagnosis. COPD patients with current smoking status are more likely to have concurrent psychiatric comorbidities, for instance, depression and anxiety. These psychiatric disorders can contribute to the persistence of smoking in individuals with COPD. This study aimed to investigate predictors of smoking persistence in COPD patients. Materials and methods A cross-sectional study was conducted in the Outpatient Department (OPD) of the Department of Pulmonary Medicine in a tertiary care hospital from August 2018 to July 2019. Patients with COPD were screened for their smoking status. All subjects were then personally assessed for any psychiatric comorbidity using the Mini International Neuropsychiatric Interview (MINI), the Patient Health Questionnaire-9 (PHQ-9), and the Anxiety Inventory for Respiratory (AIR) Disease. Logistic regression was performed to compute the odds ratio (OR).  Results The study included a total of 87 COPD patients. Of the 87 COPD patients, 50 were current smokers, and 37 were past smokers. COPD patients with psychiatric disorders were four times more likely to continue smoking than those without psychiatric comorbidities (OR: 4.62, 95% CI: 1.46-14.54). The results showed that increasing PHQ-9 scores by one unit in COPD patients increased the likelihood of continuing to smoke by 27 percent. Conclusion In our multivariate analysis, current depression was found as a significant predictor of continued smoking in COPD patients. The present results are consistent with reports from previous research that depressive symptoms are associated with continued smoking in patients with COPD. COPD patients who are currently smoking should be examined for psychiatric disorders and treated concurrently to achieve effective smoking cessation.

Indicators related to smoking cessation in Brazil, National Health Survey, 2013 and 2019 editions

OBJECTIVE

To describe the indicators of smoking cessation in 2013 and 2019 for Brazil and federative units, according to sociodemographic variables, collected in the National Health Survey (PNS).

METHODS

Cross-sectional, population-based and descriptive study with data from the 2013 and 2019 PNS, a household survey collected by trained interviewers. The prevalence of ex-smokers and the proportion of smokers who tried to quit smoking in the 12 months prior to the interview, and respective confidence intervals (95%CI) were calculated, according to sociodemographic variables. Additionally, the percentage variation between the years was calculated.

RESULTS

In 2013, the prevalence of ex-smokers was 17.5% (95%CI 16.9;18.0) and, in 2019, 26.6% (95%CI 26.1;27.2). In 2013, 51.1% tried to quit smoking (95%CI 49.3;52.9) and, in 2019, 46.6% (95%CI 45.0;48.3).

CONCLUSION

It is important to strengthen and maintain strategies for coping with tobacco use in Brazil, to increase the current smoker's willingness and ability to quit smoking.

The Promise of Polygenic Risk Prediction in Smoking Cessation: Evidence From Two Treatment Trials

INTRODUCTION

Tobacco use disorder is a complex behavior with a strong genetic component. Genome-wide association studies (GWAS) on smoking behaviors allow for the creation of polygenic risk scores (PRSs) to approximate genetic vulnerability. However, the utility of smoking-related PRSs in predicting smoking cessation in clinical trials remains unknown.

AIMS AND METHODS

We evaluated the association between polygenic risk scores and bioverified smoking abstinence in a meta-analysis of two randomized, placebo-controlled smoking cessation trials. PRSs of smoking behaviors were created using the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium summary statistics. We evaluated the utility of using individual PRS of specific smoking behavior versus a combined genetic risk that combines PRS of all four smoking behaviors. Study participants came from the Transdisciplinary Tobacco Use Research Centers (TTURCs) Study (1091 smokers of European descent), and the Genetically Informed Smoking Cessation Trial (GISC) Study (501 smokers of European descent).

RESULTS

PRS of later age of smoking initiation (OR [95% CI]: 1.20, [1.04-1.37], p = .0097) was significantly associated with bioverified smoking abstinence at end of treatment. In addition, the combined PRS of smoking behaviors also significantly predicted bioverified smoking abstinence (OR [95% CI] 0.71 [0.51-0.99], p = .045).

CONCLUSIONS

PRS of later age at smoking initiation may be useful in predicting smoking cessation at the end of treatment. A combined PRS may be a useful predictor for smoking abstinence by capturing the genetic propensity for multiple smoking behaviors.

IMPLICATIONS

There is a potential for polygenic risk scores to inform future clinical medicine, and a great need for evidence on whether these scores predict clinically meaningful outcomes. Our meta-analysis provides early evidence for potential utility of using polygenic risk scores to predict smoking cessation amongst smokers undergoing quit attempts, informing further work to optimize the use of polygenic risk scores in clinical care.

The Impact of Psychiatric Disorder Diagnosis on Motivation to Quit and Stage of Change Among Patients at a Hospital-Based Outpatient Smoking Cessation Clinic

Smoking is among the greatest international public health concerns, causing excessive levels of preventable premature death, disability, and economic costs. The prevalence of tobacco use among people with psychiatric disorders (PDs) remains persistently high relative to the general population, highlighting the need to improve smoking cessation (SC) strategies in this group. We aimed to assess the associations between having a PD and baseline motivation to quit (MtQ) smoking and Prochaska's stage of change (SoC), two clinically important metrics linked to SC outcomes. Methods: This retrospective chart review included patients who completed a baseline visit at a hospital-based outpatient SC clinic (N = 896). Multivariate hierarchical logistic and linear regression models were developed to assess variables associated with MtQ (importance and confidence in quitting) and SoC, primarily PD category (externalizing, internalizing, externalizing/internalizing, psychotic or no PD) and secondarily, demographics, physical health history, and tobacco use/dependence metrics. Results: The variables negatively associated with MtQ were female sex (p = .011), older age (p = .038), deriving income from social assistance (p < .001), and age at smoking initiation (p = .005), whereas ≥ 1 quit attempt in the past year predicted higher MtQ (p < .0001). Being in the preparative/action SoC (versus the pre-contemplative/contemplative) was associated with income from social assistance (OR 0.39, p = .001), more daily cigarettes smoked (OR 0.98, p = .005) and ≥ 1 past-year quit attempt (OR 1.69, p = .013). Conclusions: Having a PD was not associated with either MtQ or SoC. Deriving income from social assistance predicted lower MtQ and SoC. Having made ≥ 1 quit attempt in the past year was associated with higher MtQ and SoC. Our study suggests that people with PDs are as motivated to quit smoking and ready for change as people without PDs, and smoking cessation efforts should be amplified in this group to address the disproportionately high level of tobacco use, especially because having at least one quit attempt may enhance MtQ and SoC.

Factors Associated with Successful Smoking Cessation According to Age Group: Findings of an 11-Year Korea National Survey

Previous studies suggest that factors related to smoking cessation may vary with age. This study examined the factors affecting smoking cessation by age among Korean adult male smokers using data from the Korea National Health and Nutrition Examination Survey from 2007 to 2018 (excluding 2013). Logistic regression analyses were used to investigate various factors associated with smoking cessation in three different age groups. Out of a total of 15,492 individuals, 31.5% of the 3523 individuals aged 19-39 years (young adult), 54.7% of the 7390 individuals aged 40-64 years (middle-aged), and 78.6% of the 4589 individuals aged ≥65 years (older adults) succeeded in quitting. In the young adult and middle-aged groups, being married was associated with successful quitting, and lifetime smoking was associated with unsuccessful quitting. Willpower and several comorbidities were related to successful cessation in the middle-aged and older adult groups. Skipping any meal, which suggests unhealthy behavior, was negatively related to quitting in the young adult group. We observed that factors associated with smoking cessation success or failure differed by age, which should be considered when developing smoking cessation policies and programs.

Motivational interviewing for smoking cessation

BACKGROUND

Motivational Interviewing (MI) is a directive patient-centred style of counselling, designed to help people to explore and resolve ambivalence about behaviour change. It was developed as a treatment for alcohol abuse, but may help people to a make a successful attempt to stop smoking.

OBJECTIVES

To evaluate the efficacy of MI for smoking cessation compared with no treatment, in addition to another form of smoking cessation treatment, and compared with other types of smoking cessation treatment. We also investigated whether more intensive MI is more effective than less intensive MI for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register for studies using the term motivat* NEAR2 (interview* OR enhanc* OR session* OR counsel* OR practi* OR behav*) in the title or abstract, or motivation* as a keyword. We also searched trial registries to identify unpublished studies. Date of the most recent search: August 2018.

SELECTION CRITERIA

Randomised controlled trials in which MI or its variants were offered to smokers to assist smoking cessation. We excluded trials that did not assess cessation as an outcome, with follow-up less than six months, and with additional non-MI intervention components not matched between arms. We excluded trials in pregnant women as these are covered elsewhere.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Smoking cessation was measured after at least six months, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RR) and 95% confidence intervals (CI) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of comparison. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models. We extracted data on mental health outcomes and quality of life and summarised these narratively.

MAIN RESULTS

We identified 37 eligible studies involving over 15,000 participants who smoked tobacco. The majority of studies recruited participants with particular characteristics, often from groups of people who are less likely to seek support to stop smoking than the general population. Although a few studies recruited participants who intended to stop smoking soon or had no intentions to quit, most recruited a population without regard to their intention to quit. MI was conducted in one to 12 sessions, with the total duration of MI ranging from five to 315 minutes across studies. We judged four of the 37 studies to be at low risk of bias, and 11 to be at high risk, but restricting the analysis only to those studies at low or unclear risk did not significantly alter results, apart from in one case - our analysis comparing higher to lower intensity MI.We found low-certainty evidence, limited by risk of bias and imprecision, comparing the effect of MI to no treatment for smoking cessation (RR = 0.84, 95% CI 0.63 to 1.12; I2 = 0%; adjusted N = 684). One study was excluded from this analysis as the participants recruited (incarcerated men) were not comparable to the other participants included in the analysis, resulting in substantial statistical heterogeneity when all studies were pooled (I2 = 87%). Enhancing existing smoking cessation support with additional MI, compared with existing support alone, gave an RR of 1.07 (95% CI 0.85 to 1.36; adjusted N = 4167; I2 = 47%), and MI compared with other forms of smoking cessation support gave an RR of 1.24 (95% CI 0.91 to 1.69; I2 = 54%; N = 5192). We judged both of these estimates to be of low certainty due to heterogeneity and imprecision. Low-certainty evidence detected a benefit of higher intensity MI when compared with lower intensity MI (RR 1.23, 95% CI 1.11 to 1.37; adjusted N = 5620; I2 = 0%). The evidence was limited because three of the five studies in this comparison were at risk of bias. Excluding them gave an RR of 1.00 (95% CI 0.65 to 1.54; I2 = n/a; N = 482), changing the interpretation of the results.Mental health and quality of life outcomes were reported in only one study, providing little evidence on whether MI improves mental well-being.

AUTHORS' CONCLUSIONS

There is insufficient evidence to show whether or not MI helps people to stop smoking compared with no intervention, as an addition to other types of behavioural support for smoking cessation, or compared with other types of behavioural support for smoking cessation. It is also unclear whether more intensive MI is more effective than less intensive MI. All estimates of treatment effect were of low certainty because of concerns about bias in the trials, imprecision and inconsistency. Consequently, future trials are likely to change these conclusions. There is almost no evidence on whether MI for smoking cessation improves mental well-being.

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.

Motivation to quit or reduce gambling: Associations between Self-Determination Theory and the Transtheoretical Model of Change

Motivation for change and recovery from addiction has been commonly assessed using the Transtheoretical Model's stages of change. Analogous to readiness for change, this measure of motivation may not recognize other elements of motivation relevant to successful change. The aim of this study was to examine the relationship between stages of change and reasons for change according to the Self-Determination Theory among problem gamblers motivated to quit. Motivations for change were examined for 200 adult problem gamblers with intent to quit in the next 6 months (contemplation stage) or 30 days (preparation stage). Analyses revealed that higher autonomous motivation for quitting gambling predicted greater likelihood of being in the preparation stage, whereas those with higher external motivation for change were less likely to be farther along the stage of change continuum. The findings suggest that autonomous motivations relate to readiness for quitting gambling, and may predict successful resolution from problem gambling.

Dependence and motivation to stop smoking as predictors of success of a quit attempt among smokers seeking help to quit

INTRODUCTION

It is not known how well motivation to stop smoking predicts abstinence in a clinical sample relative to the most widely used measure of cigarette dependence.

METHODS

A secondary analysis was conducted from a trial with 864 smokers making quit attempt. Fagerström Test of Cigarette Dependence (FTCD), Heaviness of Smoking Index (HSI), and motivation to stop smoking (composite of determination to quit and importance of quitting) were measured at baseline. Continuous smoking abstinence, validated by expired-air carbon monoxide, was assessed at 4weeks, 6months and 12months post-quit date. FTCD, HSI, non-HSI items in FTCD, and motivation were assessed as predictors of abstinence.

RESULTS

In multiple-logistic regressions, controlling for age, gender and medication use, lower scores for FTCD, HSI and non-HSI all significantly predicted abstinence at all follow-ups, while motivation did not predict abstinence at any time. Likelihood ratio tests showed that the FTCD contributed most to the model at 4weeks and 6months; at 12months FTCD and non-HSI equally contributed most to the model. At 4weeks and 6months, predictions were improved by combining HSI and non-HSI components, compared with using these components alone.

CONCLUSIONS

Cigarette dependence, measured by the FTCD, or by its HSI or non-HSI components, predicts both short-term and medium-term outcomes of attempts to stop smoking in treatment-seeking smokers involved in a clinical trial, whereas strength of motivation to stop predicts neither. Both the HSI and non-HSI components may be considered as briefer alternatives to the full FTCD.

Longitudinal Care Improves Cessation in Smokers Who Do Not Initially Respond to Treatment by Increasing Cessation Self-Efficacy, Satisfaction, and Readiness to Quit: A Mediated Moderation Analysis

BACKGROUND

The Tobacco Longitudinal Care study was a randomized controlled trial for smoking cessation. It demonstrated that longitudinal care for smoking cessation, in which telephone-based counseling and nicotine replacement therapy were offered for 12 months, was more effective than the standard 8-week treatment.

PURPOSE

This study aims to identify for whom and how longitudinal care increased the likelihood of abstinence.

METHODS

Mediated moderation analyses were utilized across three time points.

RESULTS

There was a trend towards smokers who did not respond to treatment (i.e., were still smoking) by 21 days being more likely to be abstinent at 6 months if they received longitudinal care rather than usual care. Similarly, those who did not respond to treatment by 3 months were more likely to be abstinent at 12 months if they received longitudinal care. At both time points, the likelihood of abstinence did not differ across treatment conditions among participants who responded to treatment (i.e., quit smoking). The effect on 6-month outcomes was mediated by satisfaction and readiness to quit. Cessation self-efficacy, satisfaction, and readiness to quit mediated the effect on 12-month outcomes. The effect of treatment condition on the likelihood of abstinence at 18 months was not moderated by response to treatment at 6 months.

CONCLUSIONS

Smokers who did not respond to initial treatment benefited from longitudinal care. Differential effects of treatment condition were not observed among those who responded to early treatment. Conditional assignment to longitudinal care may be useful. Determining for whom and how interventions work over time will advance theory and practice.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Effective pharmacotherapies are available to help people who are trying to stop smoking, but quitting can still be difficult and providing higher levels of behavioural support may increase success rates further.

OBJECTIVES

To evaluate the effect of 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.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in May 2015 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

Randomized or quasi-randomized controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount of behavioural support. The intervention condition had to involve person-to-person contact. The control condition could receive less intensive personal contact, or just written information. We did not include studies that used a contact-matched control to evaluate differences between types or components of support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

One author prescreened search results and two authors agreed inclusion or exclusion of potentially relevant trials. One author extracted data and another checked them.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 Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Forty-seven studies met the inclusion criteria with over 18,000 participants in the relevant arms. There was little evidence of statistical heterogeneity (I² = 18%) so we pooled all studies in the main analysis. There was evidence of a small but statistically significant benefit from more intensive support (RR 1.17, 95% CI 1.11 to 1.24) for abstinence at longest follow-up. All but four of the included studies provided four or more sessions of support to the intervention group. Most trials used NRT. We did not detect significant effects for studies where the pharmacotherapy was nortriptyline (two trials) or varenicline (one trial), but this reflects the absence of evidence.In subgroup analyses, studies that provided at least four sessions of personal contact for the intervention and no personal contact for the control had slightly larger estimated effects (RR 1.25, 95% CI 1.08 to 1.45; 6 trials, 3762 participants), although a formal test for subgroup differences was not significant. Studies where all intervention counselling was via telephone (RR 1.28, 95% CI 1.17 to 1.41; 6 trials, 5311 participants) also had slightly larger effects, and the test for subgroup differences was significant, but this subgroup analysis was not prespecified. In this update, the benefit of providing additional behavioural support was similar for the subgroup of trials in which all participants, including controls, had at least 30 minutes of personal contact (RR 1.18, 95% CI 1.06 to 1.32; 21 trials, 5166 participants); previously the evidence of benefit in this subgroup had been weaker. This subgroup was not prespecified and a test for subgroup differences was not significant. We judged the quality of the evidence to be high, using the GRADE approach. We judged a small number of trials to be at high risk of bias on one or more domains, but findings were not sensitive to their exclusion.

AUTHORS' CONCLUSIONS

Providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking has a small but important effect. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 25%, based on a pooled estimate from 47 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support.

Predictors of tobacco smoking abstinence among tuberculosis patients in South Africa

This study examines predictors of smoking cessation in tuberculosis patients with high HIV co-infection rates in a South African primary care setting. Current smokers were randomly allocated to brief motivational interviewing (n = 205) or receipt of a brief message (n = 204). Multi-level logistic regression was performed to identify predictors of sustained 3- and 6-month abstinence and 7-day point prevalence abstinence (PPA) at 1 month, with the facility as a random effect. The intervention was ineffective among smokers with high nicotine-dependence at 1 month, but was effective for all smokers over longer periods. Higher baseline self-efficacy predicted the 1-month 7-day PPA, but not sustained abstinence. HIV-positive participants' odds of sustained abstinence were about three times higher than those of their HIV-negative counterparts. Results support a more intensive motivational intervention and/or coping skills' training to increase self-efficacy and abstinence rates. Tobacco cessation services can be introduced in tuberculosis services where high HIV co-infection rates occur.

Knowing quitters predicts smoking cessation in a homeless population

OBJECTIVES

To examine the impact of knowing quitters on cessation among homeless smokers.

METHODS

Secondary analysis of data derived from a community-based randomized controlled trial of 430 homeless smokers. We conducted multivariable logistic regression analysis to determine whether knowing quitters impacted the likelihood of cessation (salivary cotinine ≤ 20 ng/ml) at 26-week follow-up.

RESULTS

Multivariable logistic regression showed cessation was more likely for smokers who knew ≥ 5 quitters compared with those who knew no quitters (Odds Ratio = 3.79, CI = 1.17, 12.27, p = .008), adjusting for age, education, income, and time to first cigarette in morning.

CONCLUSIONS

Knowing former smokers was associated with increased likelihood of achieving smoking abstinence among homeless smokers.

Ongoing self-engagement in quit attempts and cessation outcomes among rural smokers who were unable to quit after 2 years of repeated interventions

PURPOSE

As many smokers experience repeated failures with cessation attempts, it has been postulated that we may create a cadre of highly resistant smokers who are unlikely to engage in treatment or succeed in quitting. Our purpose was to follow a group of recalcitrant rural smokers and examine their ongoing engagement in smoking cessation activities.

METHODS

At the end of a 24-month disease management program for rural smokers, we identified participants who reported ongoing daily smoking despite exposure to 4 previous cycles of smoking cessation interventions. At month 36 (1 year after conclusion of the study), we contacted these participants and assessed changes in smoking status and ongoing engagement in cessation activities over the preceding 6 months. We assessed quit attempts and use of pharmacotherapy during the prior 6 months, as well as smoking abstinence at 36 months.

FINDINGS

Among 333 recalcitrant smokers, 49% reported at least one 24-hour quit attempt during the preceding 6 months, 29% tried smoking cessation pharmacotherapy, and 5% quit smoking. Significant predictors of having at least one 24-hour quit attempt were lower numbers of cigarettes smoked per day, being in preparation stage of change, and more pharmacotherapy-assisted quit attempts during the original 24-month trial. Higher motivation to quit and more previous pharmacotherapy-assisted quit attempts significantly predicted cessation medication use. Use of varenicline was strongly associated with cessation.

CONCLUSIONS

Many recalcitrant rural smokers continue to engage in treatment and make quit attempts even in the absence of active interventions.

Prevalência da abstinência ao tabaco de pacientes tratados em unidades de saúde e fatores relacionados

O objetivo é conhecer a prevalência e identificar as variáveis relacionadas com a abstinência do tabaco em pacientes tratados nos Grupos de Apoio Terapêutico ao Tabagista (GATT) em unidades de saúde do município de Vitória (ES), no ano de 2009. Estudo transversal com 160 participantes do GATT que participaram de 75% das sessões. Realizada entrevista por telefone, 9 a 20 meses após o tratamento, e usado dados secundários do roteiro de entrevista inicial. Na análise estatística, foram utilizados os testes qui-quadrado e Fisher. A significância estatística foi 5%. Eram abstinentes 28,7%, recaíram 51,9% e 19,4% não pararam de fumar. Houve diferença estatística entre os grupos nas variáveis estado civil (0,039), tentativas anteriores para parar de fumar (0,029), quantidade de cigarros fumados por dia (0,019), uso de fármacos (0,001) e transtorno do humor referidos (0,040). O grupo de abstinente teve mais casados, tentou mais vezes parar de fumar, fumou menos cigarro/dia, apresentou menos ansiedade/alteração do humor. A abstinência foi semelhante a outros estudos e o maior percentual de sujeitos recaiu.

Behavioural interventions as adjuncts to pharmacotherapy for smoking cessation

BACKGROUND

Effective pharmacotherapies are available to help people who are trying to stop smoking, but quitting can still be difficult and providing higher levels of behavioural support may increase success rates further.

OBJECTIVES

To evaluate the effect of 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.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in July 2012 for records with any mention of pharmacotherapy, including any type of NRT, bupropion, nortriptyline or varenicline that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount of behavioural support. Controls could receive less intensive personal contact, or just written information. We did not include studies that used a contact matched control to evaluate differences between types or components of support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

Search results were prescreened by one author and inclusion or exclusion of potentially relevant trials was agreed by both authors. Data were extracted by one author and checked by the other.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 Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Thirty-eight studies met the inclusion criteria with over 15,000 participants in the relevant arms. There was very little evidence of statistical heterogeneity (I² = 3%) so all studies were pooled in the main analysis. There was evidence of a small but statistically significant benefit from more intensive support (RR 1.16, 95% CI 1.09 to 1.24) for abstinence at longest follow-up. All but two of the included studies provided four or more sessions of support. Most trials used nicotine replacement therapy. Significant effects were not detected for studies where the pharmacotherapy was nortriptyline (two trials) or varenicline (one trial), but this reflects the absence of evidence. In subgroup analyses, studies that provided at least four sessions of personal contact for the intervention and no personal contact for the control had slightly larger effects (six trials, RR 1.25, 95% CI 1.08 to 1.45), as did studies where all intervention counselling was via telephone (six trials, RR 1.28, 95% CI 1.17 to 1.41). Weaker evidence for a benefit of providing additional behavioural support was seen in the trials where all participants, including those in the control condition, had at least 30 minutes of personal contact (18 trials, RR 1.11, 95% CI 0.99 to 1.25). None of the differences between subgroups were significant, and the last two subgroup analyses were not prespecified. No trials were judged at high risk of bias on any domain.

AUTHORS' CONCLUSIONS

Providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking has a small but important effect. Increasing the amount of behavioural support is likely to increase the chance of success by about 10 to 25%, based on a pooled estimate from 38 trials. A subgroup analysis of a small number of trials suggests the benefit could be a little greater when the contrast is between a no contact control and a behavioural intervention that provides at least four sessions of contact. Subgroup analysis also suggests that there may be a smaller incremental benefit from providing even more intensive support via more or longer sessions over and above some personal contact.

Simultaneous evaluation of abstinence and relapse using a Markov chain model in smokers enrolled in a two-year randomized trial

BACKGROUND

GEE and mixed models are powerful tools to compare treatment effects in longitudinal smoking cessation trials. However, they are not capable of assessing the relapse (from abstinent back to smoking) simultaneously with cessation, which can be studied by transition models.

METHODS

We apply a first-order Markov chain model to analyze the transition of smoking status measured every 6 months in a 2-year randomized smoking cessation trial, and to identify what factors are associated with the transition from smoking to abstinent and from abstinent to smoking. Missing values due to non-response are assumed non-ignorable and handled by the selection modeling approach.

RESULTS

Smokers receiving high-intensity disease management (HDM), of male gender, lower daily cigarette consumption, higher motivation and confidence to quit, and having serious attempts to quit were more likely to become abstinent (OR = 1.48, 1.66, 1.03, 1.15, 1.09 and 1.34, respectively) in the next 6 months. Among those who were abstinent, lower income and stronger nicotine dependence (OR = 1.72 for ≤ vs. > 40 K and OR = 1.75 for first cigarette ≤ vs. > 5 min) were more likely to have relapse in the next 6 months.

CONCLUSIONS

Markov chain models allow investigation of dynamic smoking-abstinence behavior and suggest that relapse is influenced by different factors than cessation. The knowledge of treatments and covariates in transitions in both directions may provide guidance for designing more effective interventions on smoking cessation and relapse prevention.

Dependence and withdrawal-induced craving predict abstinence in an incentive-based model of smoking relapse

INTRODUCTION

Understanding factors that render some individuals more vulnerable to smoking relapse during the early stages of a quit attempt is critical to tailoring treatment efforts. Development of laboratory models of relapse can provide a framework for identifying underlying mechanisms that may contribute to vulnerability. Here, we explored predictors of abstinence in a novel incentive-based model of relapse.

METHODS

Fifty-six nontreatment seeking daily smokers completed several nicotine dependence measures prior to participating in a 1-week abstinence incentive test. During the abstinence procedure, participants earned monetary reinforcement for each biochemically verified day of abstinence according to a descending schedule of reinforcement.

RESULTS

Compliance with the procedure was excellent. All but 3 participants were able to initiate abstinence; nearly 70% lapsed as incentives were reduced. Scores on the Fagerström Test for Nicotine Dependence (FTND), number of cigarettes smoked per day, and self-reported craving on the first day of abstinence each independently predicted time to lapse. The single item of time to first cigarette in the morning on the FTND significantly predicted time to lapse, even when controlling for other significant predictors just listed. The Nicotine Dependence Syndrome Scale (NDSS) and Wisconsin Inventory of Smoking Dependence Motives did not predict lapse, but the NDSS did predict reinitiation of abstinence among those experiencing an initial lapse.

CONCLUSIONS

These findings partially replicate those of previous full-scale clinical trials and support the feasibility and validity of an incentive-based model of relapse. The time-limited and laboratory-based nature of this model has the potential to further investigations of underlying mechanisms contributing to relapse.