Ontology highlight
ABSTRACT: Background
Cigarette smoking has a considerable health and economic burden in modern society, with increased risk of morbidity and mortality. Therefore, smoking cessation policies and medical treatments are essential. However, cessation rates are low and the abandonment of the consultation is common. The identification of characteristics that may predict adherence will help defining the best treatment strategy. This study aimed to identify predictors of follow-up loss in smoking cessation consultation.Methods
We made a retrospective observational study, including a cohort of patients who started smoking cessation consultation (April-December 2018). Clinical data from consultations was collected and analyzed with IBM SPSS Statistics (SPSS, RRID:SCR_002865).Results
SUBMITTER: Cabrita BMO
PROVIDER: S-EPMC8107513 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature