Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials 2008 Issue 4, MEDLINE (1966 to January 2009), and EMBASE (1980 to January 2009). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate a pooled effect was estimated using a Mantel-Haenszel fixed effect method. MAIN RESULTS: We included eleven trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that CO measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other seven trials. One trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12; 95% CI 1.24 to 3.62). One trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77; 95% CI 1.04 to 7.41) but enrolled a population of light smokers. Five trials failed to detect evidence of a significant effect. One of these tested CO feedback alone and CO + genetic susceptibility as two different intervention; none of the three possible comparisons detected significant effects. Three others used a combination of CO and spirometry feedback in different settings, and one tested for a genetic marker. AUTHORS' CONCLUSIONS: There is little evidence about the effects of most types of biomedical tests for risk assessment. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. Only two pairs of studies were similar enough in term of recruitment, setting, and intervention to allow meta-analysis.

A systematic review of longitudinal population-based studies on the predictors of smoking cessation in adolescent and young adult smokers.

OBJECTIVE: To describe the determinants of self-initiated smoking cessation of duration of at least 6 months as identified in longitudinal population-based studies of adolescent and young adult smokers. METHODS: A systematic search of the PubMed and EMBASE databases using smoking, tobacco, cessation, quit and stop as keywords was performed. Limits included articles related to humans, in English, published between January 1984 and August 2010, and study population aged 10-29 years. A total of 4502 titles and 871 abstracts were reviewed independently by 2 and 3 reviewers, respectively. Nine articles were retained for data abstraction. Data on study location, timeframe, duration of follow-up, number of data collection points, sample size, age/grade of participants, number of quitters, smoking status at baseline, definition of cessation, covariates and analytic method were abstracted from each article. The number of studies that reported a statistically significant association between each determinant investigated and cessation were tabulated, from among all studies that assessed the determinant. RESULTS: Despite heterogeneity in methods across studies, five factors robustly predicted quitting across studies in which the factor was investigated: not having friends who smoke, not having intentions to smoke in the future, resisting peer pressure to smoke, being older at first use of cigarette and having negative beliefs about smoking. CONCLUSIONS: The literature on longitudinal predictors of cessation in adolescent and young adult smokers is not well developed. Cessation interventions for this population will remain less than optimally effective until there is a solid evidence base on which to develop interventions.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH METHODS: For the most recent update, we searched the Cochrane Collaboration Tobacco Addiction Group Specialized Register in July 2012 for studies added since the last update in 2009. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate, a pooled effect was estimated using a Mantel-Haenszel fixed-effect method. MAIN RESULTS: We included 15 trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that carbon monoxide (CO) measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other 11 trials due to the presence of substantial clinical heterogeneity. Of the remaining 11 trials, two trials detected statistically significant benefits: one trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12, 95% CI 1.24 to 3.62) and one trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77, 95% CI 1.04 to 7.41) but enrolled a population of light smokers and was judged to be at unclear risk of bias in two domains. Nine further trials did not detect significant effects. One of these tested CO feedback alone and CO combined with genetic susceptibility as two different interventions; none of the three possible comparisons detected significant effects. One trial used CO measurement, one used ultrasonography of carotid arteries and two tested for genetic markers. The four remaining trials used a combination of CO and spirometry feedback in different settings. AUTHORS' CONCLUSIONS: There is little evidence about the effects of most types of biomedical tests for risk assessment on smoking cessation. Of the fifteen included studies, only two detected a significant effect of the intervention. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial but the evidence is not optimal. A trial of carotid plaque screening using ultrasound also detected a significant effect, but a second larger study of a similar feedback mechanism did not detect evidence of an effect. Only two pairs of studies were similar enough in terms of recruitment, setting, and intervention to allow meta-analyses; neither of these found evidence of an effect. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.

Biomedical risk assessment as an aid for smoking cessation.

BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. We reviewed systematically data on smoking cessation rates from controlled trials that used biomedical risk assessment and feedback. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched he Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1966 to 2004), and EMBASE (1980 to 2004). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. MAIN RESULTS: From 4049 retrieved references, we selected 170 for full text assessment. We retained eight trials for data extraction and analysis. One of the eight used CO alone and CO + Genetic Susceptibility as two different intervention groups, giving rise to three possible comparisons. Three of the trials isolated the effect of exhaled CO on smoking cessation rates resulting in the following odds ratios (ORs) and 95% confidence intervals (95% CI): 0.73 (0.38 to 1.39), 0.93 (0.62 to 1.41), and 1.18 (0.84 to 1.64). Combining CO measurement with genetic susceptibility gave an OR of 0.58 (0.29 to 1.19). Exhaled CO measurement and spirometry were used together in three trials, resulting in the following ORs (95% CI): 0.6 (0.25 to 1.46), 2.45 (0.73 to 8.25), and 3.50 (0.88 to 13.92). Spirometry results alone were used in one other trial with an OR of 1.21 (0.60 to 2.42).Two trials used other motivational feedback measures, with an OR of 0.80 (0.39 to 1.65) for genetic susceptibility to lung cancer alone, and 3.15 (1.06 to 9.31) for ultrasonography of carotid and femoral arteries performed in light smokers (average 10 to 12 cigarettes a day). AUTHORS' CONCLUSIONS: Due to the scarcity of evidence of sufficient quality, we can make no definitive statements about the effectiveness of biomedical risk assessment as an aid for smoking cessation. Current evidence of lower quality does not however support the hypothesis that biomedical risk assessment increases smoking cessation in comparison with standard treatment. Only two studies were similar enough in term of recruitment, setting, and intervention to allow pooling of data and meta-analysis.

A critique of evaluated adolescent smoking cessation programmes

Rates of adolescent smoking appear to be on the increase, with a number of authors documenting increases in the 1990's. However, the issue of prevention rather than cessation has received greater attention in tobacco control programmes among youth. This review provides details of published school based and other tobacco cessation programmes for adolescents and compares their efficacy. Variations in outcome measures were noted with the programmes. Environmental risk factors such as economic deprivation, concurrent use of alcohol and illicit substances and a minority ethnic background have been associated with greater smoking rates among youth. It is suggested that tobacco cessation initiatives need to be considered in the context of improving adolescents lifestyle choices. Specific cessation programmes should also address issues such as appropriate follow-up and validation. (C) 2002 The Association for Professionals in Services for Adolescents. Published by Elsevier Science Ltd. All rights reserved.

Individual variation in psychological and psychomotor symptoms following smoking cessation: the implications for treatment

Some commonly experienced signs and symptoms occur during abstinence from tobacco, but specific signs and symptoms and their intensity vary greatly from individual to individual. The aim of this study was to re-examine psychological and psychomotor symptoms in smokers in the general population, and to explore the individual variation in these. Quitting smokers (n = 123) reported their experiences pre- and post-cessation, on a questionnaire developed for the study. Analysis of variance and frequency analysis showed significant decreases between pre- and post-cessation on positive experiences (F = 9.81, p < 0.0001) but no significant change on negative experiences, suggesting a loss of pleasure rather than increased negative affect upon quitting. The variance of the pre- to post-cessation difference score suggested wide variation in the reporting of withdrawal symptoms. These results lead us to consider the implications for treatment, using cognitive therapies and moderating the significant emphasis that is at present put on withdrawal.

Identifying Distinct Quitting Trajectories after an Unassisted Smoking Cessation Attempt: An Ecological Momentary Assessment Study

Objectives: This study aimed at identifying distinct quitting trajectories over 29 days after an unassisted smoking ces- sation attempt by ecological momentary assessment (EMA). In order to validate these trajectories we tested if they predict smoking frequency up to six months later. Methods: EMA via mobile phones was used to collect real time data on smoking (yes/no) after an unassisted quit attempt over 29 days. Smoking frequency one, three and six months after the quit attempt was assessed with online questionnaires. Latent class growth modeling was used to analyze the data of 230 self-quitters. Results: Four different quitting trajectories emerged: quitter (43.9%), late quitter (11.3%), returner (17%) and persistent smoker (27.8%). The quitting trajectories predicted smoking frequency one, three and six months after the quit attempt (all p < 0.001). Conclusions: Outcome after a smoking cessation attempt is better described by four distinct trajectories instead of a binary variable for abstinence or relapse. In line with the relapse model by Marlatt and Gordon, late quitter may have learned how to cope with lapses during one month after the quitting attempt. This group would have been allocated to the relapse group in traditional outcome studies.

Effects of depressive symptoms on antecedents of lapses during a smoking cessation attempt: an ecological momentary assessment study

AIMS: To investigate pathways through which momentary negative affect and depressive symptoms affect risk of lapse during smoking cessation attempts. DESIGN: Ecological momentary assessment was carried out during 2 weeks after an unassisted smoking cessation attempt. A 3-month follow-up measured smoking frequency. SETTING: Data were collected via mobile devices in German-speaking Switzerland. PARTICIPANTS: A total of 242 individuals (age 20-40, 67% men) reported 7112 observations. MEASUREMENTS: Online surveys assessed baseline depressive symptoms and nicotine dependence. Real-time data on negative affect, physical withdrawal symptoms, urge to smoke, abstinence-related self-efficacy and lapses. FINDINGS: A two-level structural equation model suggested that on the situational level, negative affect increased the urge to smoke and decreased self-efficacy (β = 0.20; β = -0.12, respectively), but had no direct effect on lapse risk. A higher urge to smoke (β = 0.09) and lower self-efficacy (β = -0.11) were confirmed as situational antecedents of lapses. Depressive symptoms at baseline were a strong predictor of a person's average negative affect (β = 0.35, all P < 0.001). However, the baseline characteristics influenced smoking frequency 3 months later only indirectly, through influences of average states on the number of lapses during the quit attempt. CONCLUSIONS: Controlling for nicotine dependence, higher depressive symptoms at baseline were associated strongly with a worse longer-term outcome. Negative affect experienced during the quit attempt was the only pathway through which the baseline depressive symptoms were associated with a reduced self-efficacy and increased urges to smoke, all leading to the increased probability of lapses.

An examination of spirituality, self efficacy, and smoking cessation among adults in Houston, Texas

Over the past decade there has been a growing interest in the association between spirituality and health outcomes. Little is known about the role of spirituality among adult smokers who are motivated to stop smoking. The purpose of this dissertation is to examine the relations among immutable individual differences, spirituality, and self efficacy among adults motivated to stop smoking. The first paper of this dissertation systematically reviewed literature to measure the concordance between spirituality and smoking status among adults in the United States. The second paper of this dissertation explored the association between spirituality and smoking cessation. We hypothesized that higher levels of spirituality were positively associated with smoking cessation. The third paper of this dissertation examined the association between perceived self efficacy and spirituality. We hypothesized that both high levels of self efficacy and spirituality were positively associated with smoking cessation.^ A total of 152 citations were identified based on the preliminary search of databases and reference lists. After a preliminary title- and abstract-based review, 17 full text articles were retrieved for further assessment. Of these, eight met the criteria for inclusion. Results of the systematic review suggest that there is inconsistent evidence to support or refute an association between spirituality and smoking status among adults.^ Smokers (N = 200) at least 18 years of age enrolled in a minimal contact smoking cessation intervention in Houston, Texas completed questionnaires. To examine our hypotheses we conducted cross-sectional analyses of responses to questions included in selected baseline questions and the final in-person visit three weeks post-quit day. Results of the logistic regression analyses indicated that individuals with higher levels of spirituality and self efficacy were significantly more likely to abstain from smoking. The positive association is also evident when controlling for employment, income, race, education, and nicotine dependence. The interaction between self efficacy and spirituality was not statistically significant in predicting smoking abstinence.^ Recommendations for future research and implications for smoking cessation interventions are discussed. Further research in this area would benefit from using standard measures of abstinence, recruiting larger and more diverse populations, and using longitudinal study designs.^

AN INVESTIGATION OF THE POSSIBLE RELATIONSHIP BETWEEN CERTAIN PHYSIOLOGICAL AND PSYCHOLOGICAL MEASURES AND SMOKING CESSATION IN A SELF - SELECTED POPULATION

This study focused on the possible relationship between certain physiological and psychological variables and the cessation of smoking. The population studied was employees enrolled in a multimodality smoking cessation program at the local offices of a major American corporation. In order to be eligible to participate, each individual must have become a non-smoker by the end of the smoking cessation program.^ Three physiological measures were taken on each individual while performing a relaxation exercise; (1) Electromyogram (EMG), (2) Galvanic Skin Response (GSR), and (3) Skin Temperature. The psychological measure consisted of the variable "anxiety" in the Cattell 16-PF personality inventory. Individual's self report of their smoking status was verified through a test for expired carbon monoxide levels.^ For the total population (N-31) no significant relationships were found between the physiological and psychological variable measured and cessation; however, with the removal of two cases discovered during the post-test interview to be influenced by external factors of high caffeine level and a severe family crisis, the measure of EMG, attained significance in discriminating between the successful and unsuccessful in Smoking Cessation. ^

Spit & lies: Does social desirability predict smoking cessation success?

This study examines the role of socially desirable responding (SDR) on smoking cessation program success. SDR is the tendency for individuals to give responses that put themselves in what they perceive to be a socially desirable light. ^ This research is a secondary analysis of data from Project Cognition, a study designed to examine the associations between performance on cognitive assessments and subsequent relapse to smoking. Adult smokers (N=183) were recruited from the greater Houston area to participate in the smoking cessation study. In this portion of the research, participants' smoking status was assessed on their quit day (QD), one week after QD, and four weeks after QD. Primary outcome measures were self-reported relapse, true cessation determined by biological measure, discrepancies between self-reported smoking status and biological assessments of smoking, and dropping out. ^ Primary predictor measures were the Balanced Inventory of Desirable Responding (BIDR) and self-reported motivation to quit smoking. The BIDR is a 40-item questionnaire that assesses Self-deceptive Enhancement (SDE; the tendency to give self-reports that are honest but positively biased) and Impression Management (IM; deliberate self-presentation to an audience). Scores were used to create a dichotomous BIDR total score group variable, a dichotomous SDE group variable, and a dichotomous IM group variable. Participants at one standard deviation above the mean were in the "high" group, and scores below one standard deviation were in the "normal" group. In addition, age, race, and gender were analyzed as covariates. ^ The overall findings of this study suggest that in the general population BIDR informs participants' self-reports and the IM and SDR subscales inform participants' behavior. BIDR predicted self-reported relapse in the general population and trended toward indicating that a participant will claim smoking cessation success when biological measures indicate otherwise. SDE interacted with motivation to predict biologically verified cessation success. There was no main effect for BIDR, IM, or SDE predicting drop out; however, IM interacted with age to predict participants' likelihood of drop out. Used in conjunction, the BIDR, IM subscale, and SDR subscale can be used to more accurately tailor smoking cessation programs to the needs of individual participants.^

The prospects for immunotherapy in smoking cessation

Context Smoking is a major preventable cause of death and disability that is maintained by dependence on nicotine. Smoking cessation reduces mortality and morbidity. Although existing pharmacological aids to smoking cessation and relapse prevention (nicotine replacement therapy and bupropion) improve on unassisted quitting and behavioural methods, they are only modestly effective. More effective pharmacological methods are required that improve compliance, reduce side-effects, and can be used in combination with existing cessation methods. Starting point A nicotine vaccine is a promising immunotherapeutic approach to smoking cessation and relapse prevention. Such a vaccine would induce the immune system to form specific antibodies to nicotine to prevent it from crossing the blood-brain barrier to act on receptor sites in the central nervous system. Recent studies in rats provide proof of principle by showing that nicotine-specific antibodies can prevent the reinstatement of nicotine self-administration (N Lindblom et al, Respiration 2002; 69: 254–60) and block dopamine release in the shell of the nucleus accumbens (Sde Villiers et al, Respiration 2002; 69: 247–53). A phase 1 trial of a human cocaine vaccine has also recently been successfully completed (T Kosten et al, Vaccine 2002; 20: 1196–204). A safe and effective human nicotine vaccine would potentially have fewer side-effects and better compliance than existing smoking-cessation pharmacotherapies. It could also be used in combination with some of them (eg, bupropion). Where next? The most promising clinical application of a human nicotine vaccine is likely to be in relapse prevention in abstinent smokers. A vaccine may also have a role in preparing smokers to quit. Clinical trials of safety and efficacy in human smokers and ex-smokers are warranted. If a nicotine vaccine proves to be safe and effective, the health-care system will need to ensure that it is registered for clinical use and that the poorer members of the community (among whom smoking prevalence is now highest in developed countries) have access to the vaccine. The community will need to be appropriately informed about the role of a nicotine vaccine to ensure that it is not prematurely used for preventive purposes in children and adolescents.