Unknown

Dataset Information

Follow-up loss in smoking cessation consultation: can we predict and prevent it?


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

altmetric image

Publications

Sorry, this publication's infomation has not been loaded in the Indexer, please go directly to PUBMED or Altmetric.

Similar Datasets