scholarly journals Anhedonia, depressed mood, and smoking cessation outcome.

2014 ◽  
Vol 82 (1) ◽  
pp. 122-129 ◽  
Author(s):  
Adam M. Leventhal ◽  
Megan E. Piper ◽  
Sandra J. Japuntich ◽  
Timothy B. Baker ◽  
Jessica W. Cook
Keyword(s):  
Smoking Cessation ◽  
Depressed Mood ◽  
Smoking Cessation Outcome

scholarly journals Development of Machine Learning Models for Prediction of Smoking Cessation Outcome

2021 ◽  
Vol 18 (5) ◽  
pp. 2584
Author(s):  
Cheng-Chien Lai ◽  
Wei-Hsin Huang ◽  
Betty Chia-Chen Chang ◽  
Lee-Ching Hwang
Keyword(s):  
Machine Learning ◽  
Smoking Cessation ◽  
Success Rate ◽  
Prediction Models ◽  
Smoking Status ◽  
Medical Center ◽  
Machine Learning Algorithms ◽  
Classification And Regression Tree ◽  
Support Vector ◽  
Smoking Cessation Outcome

Predictors for success in smoking cessation have been studied, but a prediction model capable of providing a success rate for each patient attempting to quit smoking is still lacking. The aim of this study is to develop prediction models using machine learning algorithms to predict the outcome of smoking cessation. Data was acquired from patients underwent smoking cessation program at one medical center in Northern Taiwan. A total of 4875 enrollments fulfilled our inclusion criteria. Models with artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LoR), k-nearest neighbor (KNN), classification and regression tree (CART), and naïve Bayes (NB) were trained to predict the final smoking status of the patients in a six-month period. Sensitivity, specificity, accuracy, and area under receiver operating characteristic (ROC) curve (AUC or ROC value) were used to determine the performance of the models. We adopted the ANN model which reached a slightly better performance, with a sensitivity of 0.704, a specificity of 0.567, an accuracy of 0.640, and an ROC value of 0.660 (95% confidence interval (CI): 0.617–0.702) for prediction in smoking cessation outcome. A predictive model for smoking cessation was constructed. The model could aid in providing the predicted success rate for all smokers. It also had the potential to achieve personalized and precision medicine for treatment of smoking cessation.

scholarly journals Predictors of Varenicline Adherence Among Cancer Patients Treated for Tobacco Dependence and its Association With Smoking Cessation

2018 ◽  
Vol 21 (8) ◽  
pp. 1135-1139 ◽  
Author(s):  
Grace Crawford ◽  
Jessica Weisbrot ◽  
Joseph Bastian ◽  
Alex Flitter ◽  
Nancy C Jao ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Cancer Patients ◽  
Depressed Mood ◽  
Sleep Problems ◽  
Treatment Success ◽  
Tobacco Dependence ◽  
Open Label ◽  
Quit Smoking ◽  
Reinforcing Effects ◽  
The Relationship

Abstract Introduction The degree to which smokers adhere to pharmacotherapy predicts treatment success. The development of interventions to increase adherence requires identification of predictors of treatment adherence, particularly among specific clinical populations. Methods Using data from a 12-week open-label phase of a clinical trial of varenicline for tobacco dependence among cancer patients (N = 207), we examined: (1) the relationship between self-reported varenicline adherence and verified smoking cessation and (2) demographic and disease-related variables, and early changes in cognition, affect, withdrawal, the reinforcing effects of smoking, and medication side effects, as correlates of varenicline adherence. Results At the end of 12 weeks, 35% of the sample had quit smoking and 52% reported taking ≥80% of varenicline. Varenicline adherence was associated with cessation (p < .001): 58% of participants who were adherent had quit smoking versus 11% of those who were not. Participants who experienced early reductions in depressed mood and satisfaction from smoking and experienced an increase in the toxic effects of smoking, showed greater varenicline adherence (p < .05); the relationship between greater adherence and improved cognition, reduced craving, and reduced sleep problems and vomiting approached significance (p < .10). Conclusions Among cancer patients treated for tobacco dependence with varenicline, adherence is associated with smoking cessation. Initial changes in depressed mood and the reinforcing effects of smoking are predictive of adherence. Implications The benefits of varenicline for treating tobacco dependence among cancer patients may depend upon boosting adherence by addressing early signs of depression and reducing the reinforcing dimensions of cigarettes.

Increased interregional functional connectivity of anterior insula is associated with improved smoking cessation outcome

2019 ◽  
Vol 14 (2) ◽  
pp. 408-415
Author(s):  
Chao Wang ◽  
Zhujing Shen ◽  
Peiyu Huang ◽  
Wei Qian ◽  
Cheng Zhou ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Functional Connectivity ◽  
Anterior Insula ◽  
Smoking Cessation Outcome

Cognitive–behavioral therapy to reduce weight concerns improves smoking cessation outcome in weight-concerned women.

2001 ◽  
Vol 69 (4) ◽  
pp. 604-613 ◽  
Author(s):  
Kenneth A. Perkins ◽  
Marsha D. Marcus ◽  
Michele D. Levine ◽  
Delia D'Amico ◽  
Amy Miller ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Cognitive Behavioral Therapy ◽  
Behavioral Therapy ◽  
Cognitive Behavioral ◽  
Weight Concerns ◽  
Smoking Cessation Outcome

Physician Referrals for Smoking Cessation: Outcome in Those Who Show and Don′t Show

1995 ◽  
Vol 24 (2) ◽  
pp. 194-200 ◽  
Author(s):  
D.L. Franke ◽  
B.N. Leistikow ◽  
K.P. Offord ◽  
L. Schmidt ◽  
R.D. Hurt
Keyword(s):  
Smoking Cessation ◽  
Smoking Cessation Outcome ◽  
Physician Referrals

Smoking Cessation Outcome Expectations Measure

1996 ◽  
Author(s):  
Arie Dijkstra ◽  
Hein De Vries ◽  
Martijntje Bakker
Keyword(s):  
Smoking Cessation ◽  
Outcome Expectations ◽  
Smoking Cessation Outcome

Predicting Smoking Cessation Outcome in a Medical Center from Stage of Readiness: Contemplation Versus Action

1994 ◽  
Vol 23 (3) ◽  
pp. 335-344 ◽  
Author(s):  
C.L. Rohren ◽  
I.T. Croghan ◽  
R.D. Hurt ◽  
K.P. Offord ◽  
Z. Marusic ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Medical Center ◽  
Stage Of Readiness ◽  
Smoking Cessation Outcome

scholarly journals History of depression and smoking cessation outcome: A meta-analysis.

2003 ◽  
Vol 71 (4) ◽  
pp. 657-663 ◽  
Author(s):  
Brian Hitsman ◽  
Belinda Borrelli ◽  
Dennis E. McChargue ◽  
Bonnie Spring ◽  
Raymond Niaura
Keyword(s):  
Smoking Cessation ◽  
Meta Analysis ◽  
History Of ◽  
History Of Depression ◽  
Smoking Cessation Outcome
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