Reduction versus abrupt cessation in smokers who want to quit.

Background\ud The standard way to stop smoking is to quit abruptly on a designated quit day. A number of smokers have tried unsuccessfully to quit this way. Reducing smoking before quitting could be an alternative approach to cessation. Before this method is adopted it is important to determine whether it is at least as successful as abrupt quitting.\ud \ud Objectives\ud 1. To compare the success of reducing smoking to quit and abrupt quitting interventions. 2. To compare adverse events between arms in studies that used pharmacotherapy to aid reduction.\ud \ud Search methods\ud We searched the Cochrane Tobacco Addiction Review Group specialised register, MEDLINE, EMBASE and PsycInfo for topic specific terms combined with terms used to identify trials of tobacco addiction interventions. We also searched reference lists of relevant papers and contacted authors of ongoing trials. Date of most recent search: November 2009.\ud \ud Selection criteria\ud We included randomized controlled trials (RCTs) that recruited adults who wanted to quit smoking. Studies included at least one condition which instructed participants to reduce their smoking and then quit and one condition which instructed participants to quit abruptly.\ud \ud Data collection and analysis\ud The outcome measure was abstinence from smoking after at least six months follow-up. We pooled the included trials using a Mantel-Haenszel fixed-effect model. Trials were split for two sub-group analyses: pharmacotherapy vs no pharmacotherapy, self help therapy vs behavioural support. Adverse events were summarised as a narrative. It was not possible to compare them quantitatively as there was variation in the nature and depth of reporting across studies.\ud \ud Main results\ud Ten studies were relevant for inclusion, with a total of 3760 participants included in the meta-analysis. Three of these studies used pharmacotherapy as part of the interventions. Five studies included behavioural support in the intervention, four included self-help therapy, and the remaining study had arms which included behavioural support and arms which included self-help therapy. Neither reduction or abrupt quitting had superior abstinence rates when all the studies were combined in the main analysis (RR= 0.94, 95% CI= 0.79 to 1.13), whether pharmacotherapy was used (RR= 0.87, 95% CI= 0.65 to 1.22), or not (RR= 0.97, 95% CI= 0.78 to 1.21), whether studies included behavioural support (RR= 0.87, 95% CI= 0.64 to 1.17) or self-help therapy (RR= 0.98, 95% CI= 0.78 to1.23). We were unable to draw conclusions about the difference in adverse events between interventions, however recent studies suggest that pre-quit NRT does not increase adverse events.\ud \ud Authors' conclusions\ud Reducing cigarettes smoked before quit day and quitting abruptly, with no prior reduction, produced comparable quit rates, therefore patients can be given the choice to quit in either of these ways. Reduction interventions can be carried out using self-help materials or aided by behavioural support, and can be carried out with the aid of pre-quit NRT. Further research needs to investigate which method of reduction before quitting is the most effective, and which categories of smokers benefit the most from each method, to inform future policy and intervention development.\ud \u

Bayesian Function-on-Function Regression for Multilevel Functional Data

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data—where the unit of observation is a curve or set of curves that are finely sampled over a grid—is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images

Belief about Nicotine Modulates Subjective Craving and Insula Activity in Deprived Smokers

Little is known about the specific neural mechanisms through which cognitive factors influence craving and associated brain responses, despite the initial success of cognitive therapies in treating drug addiction. In this study, we investigated how cognitive factors such as beliefs influence subjective craving and neural activities in nicotine-addicted individuals using model-based functional magnetic resonance imaging (fMRI) and neuropharmacology. Deprived smokers (N = 24) participated in a two-by-two balanced placebo design, which crossed beliefs about nicotine (told "nicotine" vs. told "no nicotine") with the nicotine content in a cigarette (nicotine vs. placebo) which participants smoked immediately before performing a fMRI task involving reward learning. Subjects' reported craving was measured both before smoking and after the fMRI session. We found that first, in the presence of nicotine, smokers demonstrated significantly reduced craving after smoking when told "nicotine in cigarette" but showed no change in craving when told "no nicotine." Second, neural activity in the insular cortex related to craving was only significant when smokers were told "nicotine" but not when told "no nicotine." Both effects were absent in the placebo condition. Third, insula activation related to computational learning signals was modulated by belief about nicotine regardless of nicotine's presence. These results suggest that belief about nicotine has a strong impact on subjective craving and insula responses related to both craving and learning in deprived smokers, providing insights into the complex nature of belief-drug interactions

Post dural puncture headache in a pediatric patient with idiopathic intracranial hypertension

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74938/1/j.1460-9592.2004.01529.x.pd

Effected Cancer Region and Psychiatric Disorders in Smoking Cessation

https://openworks.mdanderson.org/sumexp23/1003/thumbnail.jp

Using Novel Carbon Monoxide Devices in Remote Smoking Cessation Treatment: A Utilization and Reliability Analysis

https://openworks.mdanderson.org/sumexp22/1119/thumbnail.jp

Rapid reduction versus abrupt quitting for smokers who want to stop soon: a randomised controlled non-inferiority trial

Background: The standard way to stop smoking is to stop abruptly on a quit day with no prior reduction in consumption of cigarettes. Many smokers feel that reduction is natural and if reduction programmes were offered, many more might take up treatment. Few trials of reduction versus abrupt cessation have been completed. Most are small, do not use pharmacotherapy, and do not meet the standards necessary to obtain a marketing authorisation for a pharmacotherapy.\ud Design/Methods: We will conduct a non-inferiority andomised trial of rapid reduction versus standard abrupt cessation among smokers who want to stop smoking. In the reduction arm,participants will be advised to reduce smoking consumption by half in the first week and to 25% of baseline in the second, leading up to a quit day at which participants will stop smoking completely.This will be assisted by nicotine patches and an acute form of nicotine replacement therapy. In the abrupt arm participants will use nicotine patches only, whilst smoking as normal, for two weeks prior to a quit day, at which they will also stop smoking completely. Smokers in either arm will have standard withdrawal orientated behavioural support programme with a combination of nicotine patches and acute nicotine replacement therapy post-cessation.\ud Outcomes/Follow-up: The primary outcome of interest will be prolonged abstinence from smoking, with secondary trial outcomes of point prevalence, urges to smoke and withdrawal\ud symptoms. Follow up will take place at 4 weeks, 8 weeks and 6 months post-quit day

Bayesian Regularization to Predict Neuropsychiatric adverse Events in Smoking Cessation With Pharmacotherapy

BACKGROUND: Research on risk factors for neuropsychiatric adverse events (NAEs) in smoking cessation with pharmacotherapy is scarce. We aimed to identify predictors and develop a prediction model for risk of NAEs in smoking cessation with medications using Bayesian regularization. METHODS: Bayesian regularization was implemented by applying two shrinkage priors, Horseshoe and Laplace, to generalized linear mixed models on data from 1203 patients treated with nicotine patch, varenicline or placebo. Two predictor models were considered to separate summary scores and item scores in the psychosocial instruments. The summary score model had 19 predictors or 26 dummy variables and the item score model 51 predictors or 58 dummy variables. A total of 18 models were investigated. RESULTS: An item score model with Horseshoe prior and 7 degrees of freedom was selected as the final model upon model comparison and assessment. At baseline, smokers reporting more abnormal dreams or nightmares had 16% greater odds of experiencing NAEs during treatment (regularized odds ratio (rOR) = 1.16, 95% credible interval (CrI) = 0.95 - 1.56, posterior probability P(rOR \u3e 1) = 0.90) while those with more severe sleep problems had 9% greater odds (rOR = 1.09, 95% CrI = 0.95 - 1.37, P(rOR \u3e 1) = 0.85). The prouder a person felt one week before baseline resulted in 13% smaller odds of having NAEs (rOR = 0.87, 95% CrI = 0.71 - 1.02, P(rOR \u3c 1) = 0.94). Odds of NAEs were comparable across treatment groups. The final model did not perform well in the test set. CONCLUSIONS: Worse sleep-related symptoms reported at baseline resulted in 85%-90% probability of being more likely to experience NAEs during smoking cessation with pharmacotherapy. Treatment for sleep disturbance should be incorporated in smoking cessation program for smokers with sleep disturbance at baseline. Bayesian regularization with Horseshoe prior permits including more predictors in a regression model when there is a low number of events per variable

Unintended Consequences of Incentive Provision for Behaviour Change and Maintenance around Childbirth

Financial (positive or negative) and non-financial incentives or rewards are increasingly used in attempts to influence health behaviours. While unintended consequences of incentive provision are discussed in the literature, evidence syntheses did not identify any primary research with the aim of investigating unintended consequences of incentive interventions for lifestyle behaviour change. Our objective was to investigate perceived positive and negative unintended consequences of incentive provision for a shortlist of seven promising incentive strategies for smoking cessation in pregnancy and breastfeeding. A multi-disciplinary, mixed-methods approach included involving two service-user mother and baby groups from disadvantaged areas with experience of the target behaviours as study co-investigators. Systematic reviews informed the shortlist of incentive strategies. Qualitative semi-structured interviews and a web-based survey of health professionals asked open questions on positive and negative consequences of incentives. The participants from three UK regions were a diverse sample with and without direct experience of incentive interventions: 88 pregnant women/recent mothers/partners/family members; 53 service providers; 24 experts/decision makers and interactive discussions with 63 conference attendees. Maternity and early years health professionals (n = 497) including doctors, midwives, health visitors, public health and related staff participated in the survey. Qualitative analysis identified ethical, political, cultural, social and psychological implications of incentive delivery at population and individual levels. Four key themes emerged: how incentives can address or create inequalities; enhance or diminish intrinsic motivation and wellbeing; have a positive or negative effect on relationships with others within personal networks or health providers; and can impact on health systems and resources by raising awareness and directing service delivery, but may be detrimental to other health care areas. Financial incentives are controversial and generated emotive and oppositional responses. The planning, design and delivery of future incentive interventions should evaluate unexpected consequences to inform the evidence for effectiveness, cost-effectiveness and future implementation