Smoking Cessation Interventions in Clinical Practice

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Epidemiology & Public Health".

Deadline for manuscript submissions: closed (20 October 2021) | Viewed by 4468

Special Issue Editor


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Guest Editor
University of North Carolina Wilmington, Wilmington, NC, USA
Interests: smoking cessation

Special Issue Information

Dear colleagues, 

Worldwide, tobacco use causes more than 7 million deaths per year. Suppose the pattern of smoking all over the globe does not change. In that case, more than 8 million people a year will die from diseases related to tobacco use by 2030.  Substantial clinical evidence shows that quitting smoking is one of the most important things a person can do for their health. It's vital to enhance the effectiveness of tobacco cessation interventions. Up until recently, almost only abrupt quitting has been prescribed as the quitting method. However, licensed cessation intervention success rates have been less than satisfying, and new ways have been sought to abstinence. This special issue will look for creative smoking cessation studies and some edifying success stories in tackling tobacco addiction. In this Special Issue, papers on all methods and approaches from complete abstinence from nicotine to harm reduction by, e.g., stopping smoking and switching to other nicotine products, will be considered.

We welcome a broad range of studies examining smoking cessation and quitting intervention and strategies for this Special Issue. In particular, we welcome original research articles or systematic reviews that focus on the following:

  • Clinical trials on existing or new nicotine replacement therapy and or pharmacological treatments
  • Behavioral modifications cessation studies
  • Studies on new tobacco/nicotine products, such as e-cigarettes, snus, and heat but not burn tobacco products
  • Smoking cessation among minority groups
  • Smoking cessation in low and middle-income countries 

Dr. Linda Haddad
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smoking cessation
  • Quitting tobacco products
  • Nicotine addiction
  • Barriers for quitting
  • Tobacco dependency
  • Alternative tobacco products
  • Vaporized nicotine products
  • Evaluation studies

Published Papers (1 paper)

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Research

13 pages, 670 KiB  
Article
Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users
by Jeeyae Choi, Hee-Tae Jung, Anastasiya Ferrell, Seoyoon Woo and Linda Haddad
J. Clin. Med. 2021, 10(5), 972; https://doi.org/10.3390/jcm10050972 - 2 Mar 2021
Cited by 10 | Viewed by 3871
Abstract
Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and [...] Read more.
Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and environmental determinants that cause nicotine addiction in youth e-cigarette or hookah users and build nicotine addiction prediction models using machine learning algorithms. A total of 6511 participants were identified as ever having used e-cigarettes or hookah from the National Youth Tobacco Survey (2019) datasets. Prediction models were built by Random Forest with ReliefF and Least Absolute Shrinkage and Selection Operator (LASSO). ReliefF identified important predictor variables, and the Davies–Bouldin clustering evaluation index selected the optimal number of predictors for Random Forest. A total of 193 predictor variables were included in the final analysis. Performance of prediction models was measured by Root Mean Square Error (RMSE) and Confusion Matrix. The results suggested high performance of prediction. Identified predictor variables were aligned with previous research. The noble predictors found, such as ‘witnessed e-cigarette use in their household’ and ‘perception of their tobacco use’, could be used in public awareness or targeted e-cigarette and hookah youth education and for policymakers. Full article
(This article belongs to the Special Issue Smoking Cessation Interventions in Clinical Practice)
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