Identifying relevant intersections in relation to motivation and attempt to stop smoking by using a combination of methods to develop robust predictive models and resampling techniques: A cross-sectional study of the German population.

ABSTRACT:

Aims

To illustrate robust intersections of co-occurring factors for two predictors of smoking cessation, motivation to stop smoking (MTSS) and past year-quit attempts (QA), by using means to develop robust predictive models such as bootstrap resampling, scoring rules to evaluate the predictive accuracy and spline functions.

Design, setting and participants

Cross-sectional data from the German Study on Tobacco Use (DEBRA). Past-years smokers (≥18 years, n = 13 245) from 22 survey waves (2016-2020) were included. The sample (mean age 46.8 years, 46.7% women) was randomly divided into learning (70%) and validation data (30%). Less than 20% in both data sets had tried to stop smoking within the preceding 12 months.

Measurements

Multinomial regression (for MTSS) and logist

SUBMITTER: Ulbricht S 

PROVIDER: S-EPMC12319644 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature