Literature DB >> 31302376

Dynamic, data-driven typologies of long-term smoking, cessation, and their correlates: Findings from the International Tobacco Control (ITC) Netherlands Survey.

Valéria Lima Passos1, Rik Crutzen2, Johannes T Feder3, Marc C Willemsen4, Paul Lemmens5, Karin Hummel6.   

Abstract

RATIONALE: Efforts towards tobacco control are numerous, but relapse rates for smoking cessations remain high. Behavioral changes necessary for continuous cessation appear complex, variable and subject to social, biological, psychological and environmental determinants. Currently, most cessation studies concentrate on short-to midterm behavioral changes. Besides, they use fixed typologies, thereby failing to capture the temporal changes in smoking/cessation behaviors, and its determinants.
OBJECTIVE: To obtain long-term, data-driven longitudinal patterns or profiles of smoking, cessation, and related determinants in a cohort of adult smokers, and to investigate their dynamic links.
METHODS: The dataset originated from the International Tobacco Control (ITC) Netherlands Project, waves 2008 to 2016. Temporal dynamics of smoking/cessation, psychosocial constructs, and time-varying determinants of smoking were extracted with Group-Based Trajectory Modeling technique. Their associations were investigated via multiple regression models.
RESULTS: Substantial heterogeneity of smoking and cessation behaviors was unveiled. Most respondents were classified as persistent smokers, albeit with distinct levels of consumption. For a minority, cessation could be sustained between 1 and 8 years, while others showed relapsing or fluctuating smoking behavior. Links between smoking/cessation trajectories with those of psychosocial and sociodemographic variables were diverse. Notably, changes in two variables were aligned to behavioral changes towards cessation: decreasing number of smoking peers and attaining a higher self-perceived control.
CONCLUSION: The unveiled heterogeneity of smoking behavior over time and the varied cross-dependencies between smoking data-driven typologies and those of underlying risk factors underscore the need of individually tailored approaches for motivational quitting.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cessation trajectories; Constructs; Group-based; International Tobacco Control (ITC) Netherlands; Long term; Psychosocial; Smoking; Trajectory modeling

Year:  2019        PMID: 31302376     DOI: 10.1016/j.socscimed.2019.112393

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  2 in total

1.  Classification of drug use patterns.

Authors:  Christiaan H Righolt; Geng Zhang; Salaheddin M Mahmud
Journal:  Pharmacol Res Perspect       Date:  2020-12

2.  Identification of smoking cessation phenotypes as a basis for individualized counseling: An explorative real-world cohort study.

Authors:  Maciej Paciorkowski; Florent Baty; Susanne Pohle; Esther Bürki; Martin Brutsche
Journal:  Tob Induc Dis       Date:  2022-09-23       Impact factor: 5.163

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.