Adherence to treatment to help quit smoking: effects of task performance and coping with withdrawal symptoms

The effects of nicotine withdrawal on exercise-related physical ability and sports performance in nicotine addicts: a systematic review and meta-analysis

BACKGROUND

Previous research has established that nicotine withdrawal can ameliorate cardiovascular and pulmonary function in smokers. Nevertheless, the impact on physical fitness and athletic performance remains under-investigated.

OBJECTIVE

To evaluating the impacts of nicotine withdrawal on both exercise performance and exercise-associated physical capabilities in nicotine-dependent individuals.

STUDY DESIGN

A comprehensive systematic review and meta-analysis.

DATA SOURCES

The data was compiled from databases such as PubMed, Scopus, Web of Science, Cochrane Central, and EBSCO.

STUDY SELECTION

The selection criteria required studies to elucidate the effects of nicotine withdrawal on exercise performance or exercise-related physical abilities. Moreover, the selected studies needed to provide discernible experimental results.

DATA SYNTHESIS AND ANALYSIS

The random effects model was employed in data analysis, utilizing the standardized mean difference (SMD) and the 95% confidence intervals (95% CIs) to estimate participants' exercise performance and physical abilities, referencing the Mean ±SD during baseline and withdrawal states.

RESULTS

Out of the selected studies, 10 trials were included, encompassing 13,538 participants aged 18 to 65 years. The findings suggest that nicotine withdrawal could potentially enhance sports performance (SMD = 0.45, 95% CI: 0.03 to 0.88; I^2 = 83%), particularly in terms of aerobic capacity. Short-term nicotine withdrawal (spanning 12 to 24 hours) might lead to a decline in participants' physical abilities in certain aspects like reaction time and sustained attention (SMD = -0.83, 95% CI: -1.91 to 0.25; I^2 = 79%), whereas long-term withdrawal (lasting 48 hours or more) demonstrated an opposing trend (SMD = 0.25, 95% CI: 0.12 to 0.39; I^2 = 81%). Overall, the results show that long-term nicotine withdrawal exhibited some positive impacts on sports performance and exercise-related physical ability, with the withdrawal duration being an indicator of subsequent physical performance.

CONCLUSIONS

Mid- to long-term (≥3 months) nicotine withdrawal significantly improved the exercisers' exercise-related physical ability and sports performance. Conversely, short-term (≤24 hours) nicotine withdrawal considerably hampered exercisers' performance and physical cognition. It is suggested that exercises avoid abrupt nicotine cessation prior to competitions, as long-term nicotine withdrawal has been shown to significantly enhance exercise-related physiological capacities and athletic performance. By referring to existing literatures we also found that athletes with existing nicotine addiction may could consume nicotine 15-30 minutes before competition to enhance athletic performance and physical function.PROSPERO registration number CRD42023411381.

Duration of varenicline prescription and efficacy of smoking cessation treatment: an observational study in Taiwan

Although varenicline has had a significant effect on smoking cessation in randomized clinical trials, the dose-effect of varenicline treatment for smoking cessation in real-world settings remains unclear. This study aimed to evaluate the association between the duration of varenicline prescription and smoking cessation in Taiwan after adjusting for potential confounding effects and endogeneity bias. A total of 5106 Taiwanese participants received varenicline monotherapy for smoking cessation between March 2012 and September 2016. Multinomial logistic regression (MLR) was used to analyze the association between varenicline prescription duration and smoking cessation, stratified by the frequency of smoking clinic visits and propensity scores of early stopping of smoking cessation treatment. Compared to the reference of nonquitting, longer durations of varenicline prescription were associated with the greater likelihood of immediate and complete quitting (OR = 1.08, 95% CI = 1.02-1.14) and late quitting (OR = 1.14, 95% CI = 1.07-1.20). Among those who were more likely to continue visiting smoking clinics, longer use of varenicline was significantly associated with an increase in immediate-and-complete quitting (OR = 1.19, 95% CI = 1.15-1.23) and late quitting (OR = 1.24, 95% CI = 1.20-1.28). Varenicline prescription duration was not associated with smoking cessation among smokers who visited smoking clinics once. The relationship between varenicline prescription duration and smoking cessation was modified by the frequency of smoking clinic visits and was dependent on quitting process patterns. Encouraging smokers to continue visiting the smoking cessation clinic and use medication will help smoking cessation efforts in Taiwan.

Longitudinal associations between e-cigarette use, cigarette smoking, physical activity and recreational screen time in Canadian adolescents

INTRODUCTION

This study examined longitudinal associations between e-cigarette use, cigarette smoking, physical activity, and recreational screen time (ST) in a cohort of Canadian adolescents (ages 14-17 years; grades 9-12).

METHODS

Data from 5,951 adolescents who participated in COMPASS Year 4 (2015-16; baseline) and Year 6 (2017-18; follow-up) were used. Exposures included e-cigarette use and cigarette smoking. Outcomes included cut-points for moderate- to vigorous- physical activity (MVPA; ≥ 60 min/d), muscular strengthening exercises (MSE; ≥ 3 time/wk), participation in sport (SP; intramural or competitive), and recreational screen time (ST; ≤ 430 min/day). Generalized linear mixed models were performed.

RESULTS

E-cigarette use (16.6% vs 39.2%), cigarette smoking (0.9% vs 4.7%) and dual use (0.8% vs 4.1%) increased from baseline to follow-up. SP (70.8% vs 61.3%) and the prevalence of meeting MVPA (49.8% vs 42.1%) and MSE cut-points (54.0% vs 45.3%) decreased from baseline to follow-up. Recreational ST remained similar from baseline to follow-up. New e-cigarette use at follow-up was associated with maintenance of SP and meeting MVPA and MSE cut-points, but also with increased ST. New cigarette smoking at follow-up was associated with maintaining high ST and low SP. Cigarette smoking at baseline and follow-up was associated with maintaining high ST, low MSE, and low SP. Cigarette smoking cessation at follow-up was associated with increasing MVPA and MSE, decreasing ST, and maintaining low SP.

CONCLUSION

Given the clustering and co-occurring unhealthy behavioral patterns, intervention strategies to promote healthy lifestyles should take a holistic approach, by targeting multiple behavioral changes simultaneously.

IMPLICATIONS

This investigation highlighted that, unhealthy behaviors, particularly e-cigarette use, cigarette smoking, and excessive use of screens, tend to co-occur among Canadian adolescents. Therefore, intervention strategies to promote healthy lifestyles should take a holistic approach, by targeting multiple behavioral changes simultaneously particularly in school and community settings. As an exception, new and stable e-cigarette use appears to co-occur with achieving sufficient levels of physical activity. Increasing awareness about the risk of e-cigarette use may target population groups that are physically and socially active (e.g., athletes, sport teams).

Impulsivity and Compulsivity and Their Relationship with Non-Adherence to Treatment in the Prison Population

The main challenge of interventions in penitentiary institutions is the re-education and reintegration of inmates, i.e., that inmates have the intention and ability to live law-abiding lives. Therefore, an increase in self-control or, on the contrary, the decrease or elimination of impulsive versus compulsive behaviors becomes necessary. This study aimed to evaluate the role of impulsivity versus compulsivity in treatment adherence in the prison population. The study included 134 men from the Penitentiary Center of Granada who were divided into two groups. Group 1 was considered treatment adherent, and Group 2 was considered non-adherent to treatment. The following instruments were used: Symptom Inventory (SCL-90-R), Addiction Severity Index (EuropASI), Impulsivity Scale (UPPS-P), and Compulsive Belief Questionnaire (OBQ-44). Statistically significant differences were found in impulsivity in the dimensions of negative urgency, sensation seeking, and positive urgency, with higher scores in all cases for the non-adherent group than for the adherent group. We also found statistically significant differences in responsibility/inhibition, perfectionism/uncertainty, and importance/control, with higher scores for the non-adherent group compared to the adherent group. Treatment adherence is inversely related to impulsive and compulsive behaviors.

Exercise interventions for smoking cessation

BACKGROUND

Taking regular exercise, whether cardiovascular-type exercise or resistance exercise, may help people to give up smoking, particularly by reducing cigarette withdrawal symptoms and cravings, and by helping to manage weight gain.

OBJECTIVES

To determine the effectiveness of exercise-based interventions alone, or combined with a smoking cessation programme, for achieving long-term smoking cessation, compared with a smoking cessation intervention alone or other non-exercise intervention.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register for studies, using the term 'exercise' or 'physical activity' in the title, abstract or keywords. The date of the most recent search was May 2019.

SELECTION CRITERIA

We included randomised controlled trials that compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme alone or another non-exercise control group. Trials were required to recruit smokers wishing to quit or recent quitters, to assess abstinence as an outcome and have follow-up of at least six months.

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 (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of comparison, as either smoking cessation or relapse prevention. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models.

MAIN RESULTS

We identified 24 eligible trials with a total of 7279 adult participants randomised. Two studies focused on relapse prevention among smokers who had recently stopped smoking, and the remaining 22 studies were concerned with smoking cessation for smokers who wished to quit. Eleven studies were with women only and one with men only. Most studies recruited fairly inactive people. Most of the trials employed supervised, group-based cardiovascular-type exercise supplemented by a home-based exercise programme and combined with a multi-session cognitive behavioural smoking cessation programme. The comparator in most cases was a multi-session cognitive behavioural smoking cessation programme alone. Overall, we judged two studies to be at low risk of bias, 11 at high risk of bias, and 11 at unclear risk of bias. Among the 21 studies analysed, we found low-certainty evidence, limited by potential publication bias and by imprecision, comparing the effect of exercise plus smoking cessation support with smoking cessation support alone on smoking cessation outcomes (RR 1.08, 95% CI 0.96 to 1.22; I² = 0%; 6607 participants). We excluded one study from this analysis as smoking abstinence rates for the study groups were not reported. There was no evidence of subgroup differences according to the type of exercise promoted; the subgroups considered were: cardiovascular-type exercise alone (17 studies), resistance training alone (one study), combined cardiovascular-type and resistance exercise (one study) and type of exercise not specified (two studies). The results were not significantly altered when we excluded trials with high risk of bias, or those with special populations, or those where smoking cessation intervention support was not matched between the intervention and control arms. Among the two relapse prevention studies, we found very low-certainty evidence, limited by risk of bias and imprecision, that adding exercise to relapse prevention did not improve long-term abstinence compared with relapse prevention alone (RR 0.98, 95% CI 0.65 to 1.47; I² = 0%; 453 participants).

AUTHORS' CONCLUSIONS

There is no evidence that adding exercise to smoking cessation support improves abstinence compared with support alone, but the evidence is insufficient to assess whether there is a modest benefit. Estimates of treatment effect were of low or very low certainty, because of concerns about bias in the trials, imprecision and publication bias. Consequently, future trials may change these conclusions.

What Factors Influence Non-Adherence to the Smoking Cessation Program?

OBJECTIVES

To improve our knowledge and understand how to deal with non-adherence to the support programs and to determine the rate and possible factors related to non-adherence in subjects who attended our smoking cessation clinic.

MATERIALS AND METHODS

This was a case-control study that included 550 subjects who applied to our smoking cessation clinic between June 1, 2011 and December 31, 2011. After a 1-year follow-up period, subjects were divided into two groups: adherent (controls) and non-adherent (cases). Sociodemographic and clinical parameters and smoking habits were evaluated. A p value <0.05 was considered significant.

RESULTS

Of the 550 subjects, the number of cases (non-adherent) was 135 (24.6%), and the number of controls (adherent) was 415 (75.4%). Age to begin smoking was significantly young in subjects with non-adherence to the program (p=0.026). The rate of receiving pharmacotherapy was significantly high in subjects with adherence (p<0.0001). No difference was found between the groups according to varenicline, bupropion, nicotine gum, or combined therapy use, whereas nicotine patch use alone significantly increased the rate of non-adherence (p=0.022). Multivariable logistic regression analysis showed that the age to begin smoking (p=0.045, odds ratio (OR): 1.05, 95% confidence interval (CI): 0.86-0.99) and pharmacotherapy (p<0.0001, OR: 5.00, 95% CI: 2.80-8.94) were independent variables that affected adherence to the program.

CONCLUSION

Care should be taken in the follow-up period when providing no pharmacotherapy and with subjects who started smoking at a young age.

Blended Smoking Cessation Treatment: Exploring Measurement, Levels, and Predictors of Adherence

Background

Blended face-to-face and Web-based treatment is a promising way to deliver cognitive behavioral therapy. Since adherence has been shown to be a measure for treatment’s acceptability and a determinant for treatment’s effectiveness, in this study, we explored adherence to a new blended smoking cessation treatment (BSCT).

Objective

The objective of our study was to (1) develop an adequate method to measure adherence to BSCT; (2) define an adequate degree of adherence to be used as a threshold for being adherent; (3) estimate adherence to BSCT; and (4) explore the possible predictors of adherence to BSCT.

Methods

The data of patients (N=75) were analyzed to trace adherence to BSCT delivered at an outpatient smoking cessation clinic. In total, 18 patient activities (eg, using a Web-based smoking diary tool or responding to counselors’ messages) were selected to measure adherence; the degree of adherence per patient was compared with quitting success. The minimum degree of adherence of patients who reported abstinence was examined to define a threshold for the detection of adherent patients. The number of adherent patients was calculated for each of the 18 selected activities; the degree of adherence over the course of the treatment was displayed; and the number of patients who were adherent was analyzed. The relationship between adherence and 33 person-, smoking-, and health-related characteristics was examined.

Results

The method for measuring adherence was found to be adequate as adherence to BSCT correlated with self-reported abstinence (P=.03). Patients reporting abstinence adhered to at least 61% of BSCT. Adherence declined over the course of the treatment; the percentage of adherent patients per treatment activity ranged from 82% at the start of the treatment to 11%-19% at the final-third of BSCT; applying a 61% threshold, 18% of the patients were classified as adherent. Marital status and social modeling were the best independent predictors of adherence. Patients having a partner had 11-times higher odds of being adherent (OR [odds ratio]=11.3; CI: 1.33-98.99; P=.03). For social modeling, graded from 0 (=partner and friends are not smoking) to 8 (=both partner and nearly all friends are smoking), each unit increase was associated with 28% lower odds of being adherent (OR=0.72; CI: 0.55-0.94; P=.02).

Conclusions

The current study is the first to explore adherence to a blended face-to-face and Web-based treatment (BSCT) based on a substantial group of patients. It revealed a rather low adherence rate to BSCT. The method for measuring adherence to BSCT could be considered adequate because the expected dose-response relationship between adherence and quitting could be verified. Furthermore, this study revealed that marital status and social modeling were independent predictors of adherence.

Trial Registration

Netherlands Trial Registry NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113 (Archived by WebCite at http://www.webcitation.org/71BAPwER8).

Success rates in smoking cessation: Psychological preparation plays a critical role and interacts with other factors such as psychoactive substances

INTRODUCTION

The aim of this study was to identify factors associated with the results of smoking cessation attempts.

METHODS

Data were collected in Clermont-Ferrand from a smoking cessation clinic between 1999 and 2009 (1,361 patients). Smoking cessation was considered a success when patients were abstinent 6 months after the beginning of cessation. Multivariate logistic regression was used to investigate the association between abstinence and different factors.

RESULTS

The significant factors were a history of depression (ORadjusted = 0.57, p = 0.003), state of depression at the initial consultation (ORa = 0.64, p = 0.005), other psychoactive substances (ORa = 0.52, p<0.0001), heart, lung and Ear-Nose-Throat diseases (ORa = 0.65, p = 0.005), age (ORa = 1.04, p<0.0001), the Richmond test (p<0.0001; when the patient's motivation went from insufficient to moderate, the frequency of abstinence was twice as high) and the Prochaska algorithm (p<0.0001; when the patient went from the 'pre-contemplation' to the 'contemplation' level, the frequency of success was four times higher). A high score in the Richmond test had a greater impact on success with increasing age (significant interaction: p = 0.01). In exclusive smokers, the contemplation level in the Prochaska algorithm was enough to obtain a satisfactory abstinence rate (65.5%) whereas among consumers of other psychoactive substances, it was necessary to reach the preparation level in the Prochaska algorithm to achieve a success rate greater than 50% (significant interaction: p = 0.02).

CONCLUSION

The psychological preparation of the smoker plays a critical role. The management of smoking cessation must be personalized, especially for consumers of other psychoactive substances and/or smokers with a history of depression.

Trends in Smoking Status and Utilization of Smoking Cessation Agents Among Females with Cardiovascular Diseases

BACKGROUND

In the United States, cigarette smoking accounts for almost 20% of all deaths attributed to heart disease. More women than men die each year of cardiovascular diseases (CVDs). Women who smoke have shown to be at a higher risk of cardiac deaths. The current study aims to determine the trend in smoking prevalence among women with CVD and their utilization of smoking cessation agents from 2004 to 2011.

MATERIALS AND METHODS

This was a retrospective exploratory study using Medical Expenditure Panel Survey data from 2004 to 2011. All female respondents with any one cardiovascular condition were identified. Descriptive statistics were carried out to obtain the number of female patients with CVD, their smoking status, and their use of smoking cessation agents. Furthermore, disparities in smoking status and smoking cessation agent utilization with respect to race and ethnicity were studied.

RESULTS

Among total CVD patients, 53% were females, which corresponded to 25.3 million females in the United States. Around 12.3% among them were current smokers. Only 6.9% among these females used smoking cessation agents. Smoking trends in females were inconsistent throughout the 8 years. Overall, the trend showed a decrease in the percentage of female smokers, while use of smoking cessation agents remained low from 2004 to 2011. Whites and non-Hispanics had more current smokers and women using smoking cessation agents.

CONCLUSION

The eight-year trend shows that the use of smoking cessation agents among females is very low, particularly among non-whites and Hispanics. This is of great concern and future efforts could focus on increasing the utilization of smoking cessation agents and collectively decreasing the risk of smoking in CVD by healthcare professionals.