75 resultados para Marihuana Smoking
Resumo:
OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.
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OBJECTIVES This study analyses the changes in smoking habits over the course of 1 year in a group of patients referred to an oral medicine unit. MATERIALS AND METHODS Smoking history and behaviour were analysed at baseline and after 1 year based on a self-reported questionnaire and on exhaled carbon monoxide levels [in parts per million (ppm)]. During the initial examination, all smokers underwent tobacco use prevention and cessation counselling. RESULTS Of the initial group of 121 patients, 98 were examined at the follow-up visit. At the baseline examination, 33 patients (33.67 %) indicated that they were current smokers. One year later, 14 patients (42.24 % out of the 33 smokers of the initial examination) indicated that they had attempted to stop smoking at least once over the follow-up period and 15.15 % (5 patients) had quit smoking. The mean number of cigarettes smoked per day by current smokers decreased from 13.10 to 12.18 (p = 0.04). The exhaled CO level measurements showed very good correlation with a Spearman's coefficient 0.9880 for the initial visit, and 0.9909 for the follow-up examination. For current smokers, the consumption of one additional cigarette per day elevated the CO measurements by 0.77 ppm (p < 0.0001) at the baseline examination and by 0.84 ppm (p < 0.0001) at the 1-year follow-up. CONCLUSIONS In oral health care, where smoking cessation is an important aspect of the treatment strategy, the measurement of exhaled carbon monoxide shows a very good correlation with a self-reported smoking habit. CLINICAL RELEVANCE Measurement of exhaled carbon monoxide is a non-invasive, simple and objective measurement technique for documenting and monitoring smoking cessation and reduction.
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The Health Action Process Approach (HAPA) assumes that volitional processes are important for effective behavioral change. However, intraindividual associations have not yet been tested in the context of smoking cessation. This study examined the inter- and intraindividual associations between volitional HAPA variables and daily smoking before and after a quit attempt. Overall, 100 smokers completed daily surveys on mobile phones from 10 days before until 21 days after a self-set quit date, including self-efficacy, action planning, action control, and numbers of cigarettes smoked. Negative associations between volitional variables and daily numbers of cigarettes smoked emerged at the inter- and intraindividual level. Except for interindividual action planning, associations were stronger after the quit date than before the quit date. Self-efficacy, planning and action control were identified as critical inter- and intraindividual processes in smoking cessation, particularly after a self-set quit attempt when actual behavior change is performed.
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The dual-effects model of social control proposes that social control leads to increased psychological distress but also to better health practices. However, findings are inconsistent, and recent research suggests that the most effective control is unnoticed by the receiver (i. e., invisible). Yet, investigations of the influence of invisible control on daily negative affect and smoking have been limited. Using daily diaries, we investigated how invisible social control was associated with negative affect and smoking. Overall, 100 smokers (72.0 % men, age M = 40.48, SD = 9.82) and their nonsmoking partners completed electronic diaries from a self-set quit date for 22 consecutive days, reporting received and provided social control, negative affect, and daily smoking. We found in multilevel analyses of the within-person process that on days with higher-than-average invisible control, smokers reported more negative affect and fewer cigarettes smoked. Findings are in line with the assumptions of the dual-effects model of social control: Invisible social control increased daily negative affect and simultaneously reduced smoking at the within-person level.
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AIMS To estimate physical activity trajectories for people who quit smoking, and compare them to what would have been expected had smoking continued. DESIGN, SETTING AND PARTICIPANTS A total of 5115 participants in the Coronary Artery Risk Development in Young Adults Study (CARDIA) study, a population-based study of African American and European American people recruited at age 18-30 years in 1985/6 and followed over 25 years. MEASUREMENTS Physical activity was self-reported during clinical examinations at baseline (1985/6) and at years 2, 5, 7, 10, 15, 20 and 25 (2010/11); smoking status was reported each year (at examinations or by telephone, and imputed where missing). We used mixed linear models to estimate trajectories of physical activity under varying smoking conditions, with adjustment for participant characteristics and secular trends. FINDINGS We found significant interactions by race/sex (P = 0.02 for the interaction with cumulative years of smoking), hence we investigated the subgroups separately. Increasing years of smoking were associated with a decline in physical activity in black and white women and black men [e.g. coefficient for 10 years of smoking: -0.14; 95% confidence interval (CI) = -0.20 to -0.07, P < 0.001 for white women]. An increase in physical activity was associated with years since smoking cessation in white men (coefficient 0.06; 95% CI = 0 to 0.13, P = 0.05). The physical activity trajectory for people who quit diverged progressively towards higher physical activity from the expected trajectory had smoking continued. For example, physical activity was 34% higher (95% CI = 18 to 52%; P < 0.001) for white women 10 years after stopping compared with continuing smoking for those 10 years (P = 0.21 for race/sex differences). CONCLUSIONS Smokers who quit have progressively higher levels of physical activity in the years after quitting compared with continuing smokers.
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Weight gain is often associated with smoking cessation and may discourage smokers from quitting. This study estimated the weight gained one year after smoking cessation and examined the risk factors associated with weight gain in order to identify socio-demographic groups at higher risk of increased weight after quitting. We analyzed data from 750 adults in two randomized controlled studies that included smokers motivated to quit and found a gradient in weight gain according to the actual duration of abstinence during follow-up. Subjects who were abstinent for at least 40 weeks gained 4.6 kg (SD = 3.8) on average, compared to 1.2 kg (SD = 2.6) for those who were abstinent less than 20 weeks during the 1-year follow-up. Considering the duration of abstinence as an exposure variable, we found an age effect and a significant interaction between sex and the amount of smoking before quitting: younger subjects gained more weight than older subjects; among light smokers, men gained more weight on average than women one year after quitting, while the opposite was observed among heavy smokers. Young women smoking heavily at baseline had the highest risk of weight gain after quitting.
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PURPOSE: The worldwide prevalence of human papillomavirus (HPV) infection is estimated at 9-13 %. Persistent infection can lead to the development of malignant and nonmalignant diseases. Low-risk HPV types are mostly associated with benign lesions such as anogenital warts. In the present systematic review, we examined the impact of smoking on HPV infection and the development of anogenital warts, respectively. METHODS: A systematic literature search was performed using MEDLINE database for peer-reviewed articles published from January 01, 1985 to November 30, 2013. Pooled rates of HPV prevalence were compared using the χ (2) test. RESULTS: In both genders, smoking is associated with higher incidence and prevalence rates for HPV infection, whereas the latter responds to a dose-effect relationship. The overall HPV prevalence for smoking patients was 48.2 versus 37. 5 % for nonsmoking patients (p < 0.001) (odds ratio (OR) = 1.5, 95 % confidence interval (CI) 1.4-1.7). Smoking does also increase persistence rates for high-risk HPV infection, while this correlation is debatable for low-risk HPV. The incidence and recurrence rates of anogenital warts are significantly increased in smokers. CONCLUSIONS: Most current data demonstrate an association between smoking, increased anogenital HPV infection, and development of anogenital warts. These data add to the long list of reasons for making smoking cessation a keystone of patient health.
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Objectives Social support receipt from one's partner is assumed to be beneficial for successful smoking cessation. However, support receipt can have costs. Recent research suggests that the most effective support is unnoticed by the receiver (i.e., invisible). Therefore, this study examined the association between everyday levels of dyadic invisible emotional and instrumental support, daily negative affect, and daily smoking after a self-set quit attempt in smoker–non-smoker couples. Methods Overall, 100 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date on for 22 consecutive days, reporting daily invisible emotional and instrumental social support, daily negative affect, and daily smoking. Results Same-day multilevel analyses showed that at the between-person level, higher individual mean levels of invisible emotional and instrumental support were associated with less daily negative affect. In contrast to our assumption, more receipt of invisible emotional and instrumental support was related to more daily cigarettes smoked. Conclusions The findings are in line with previous results, indicating invisible support to have beneficial relations with affect. However, results emphasize the need for further prospective daily diary approaches for understanding the dynamics of invisible support on smoking cessation.
Resumo:
Objectives: The dual-effects model of social control proposes that social control leads to better health practices, but also arouses psychological distress. However, findings are inconsistent in relation to health behavior and psychological distress. Recent research suggests that the most effective control is unnoticed by the receiver (i.e., invisible). There is some evidence that invisible social control is beneficial for positive and negative affective reactions. Yet, investigations of the influence of invisible social control on daily smoking and distress have been limited. In daily diaries, we investigated how invisible social control is associated with number of cigarettes smoked and negative affect on a daily basis. Methods: Overall, 99 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date for 22 consecutive days within the hour before going to bed, reporting received and provided social control, daily number of cigarettes smoked, and negative affect. Results: Multilevel analyses indicated that between-person levels of invisible social control were associated with lower negative affect, whereas they were unrelated to number of cigarettes smoked. On days with higher-than-average invisible social control, smokers reported less cigarettes smoked and more negative affect. Conclusions: Between-person level findings indicate that invisible social control can be beneficial for negative affect. However, findings on the within-person level are in line with the assumptions of the dual-effects model of social control: Invisible social control reduced daily smoking and simultaneously increased daily negative affect within person.
Resumo:
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.