Evidence map›Paper›PMID 40116165›Full record

ArticleAddiction (Abingdon, England)2025

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.

Sabina Ulbricht, Adrian Richter, Daniel Kotz, Sabrina Kastaun

Abstract read
In one paragraph

Article in Addiction (Abingdon, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sabina UlbrichtDepartment SHIP-KEF, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.ORCID https://orcid.org/0000-0001-7617-0266
Adrian RichterDepartment SHIP-KEF, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Daniel KotzInstitute of General Practice, Addiction Research and Clinical Epidemiology Unit, Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany.ORCID https://orcid.org/0000-0002-9454-023X
Sabrina KastaunInstitute of General Practice, Addiction Research and Clinical Epidemiology Unit, Centre for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany.ORCID https://orcid.org/0000-0002-5590-1135

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo 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

participantsCross-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 logistic regression (for QA) were used to evaluate whether age, sex, education, monthly net household income per person and the region of residence form intersections with relevant differences in the two outcomes.

findingsMTSS compared with the absence of MTSS was associated with middle [95% confidence interval (CI) = 1.02-1.39] and high education (95% CI = 1.37-1.98). Regarding MTSS, the highest probabilities were observed in participants aged 30 to 50 years from lower and middle (30-40 years) income groups. Regarding QA, the probability of at least one past-year QA was highest in females aged between 20 and 40 years and independent from educational level. Similar probabilities in males were seen only among those from the highest educated group. The predictive accuracy of the results was reduced by 3.1% for MTSS and 3.4% for QA when comparing learning with validation data.

conclusionsThis German study provides compelling evidence linking highest motivation to stop smoking to those aged 30 to 50 years with lower or middle household income. Regardless of educational level, females' probabilities of reporting at least one past-year quit attempt appears to be highest in those aged 20 to 40 years. These findings highlight the need for adopting an intersectional approach when studying predictors of smoking cessation.

Indexed as

MotivationSmoking CessationAdultCross-Sectional StudiesEducational StatusFemaleGermanyHumansLogistic ModelsMaleMiddle AgedSex FactorsYoung Adultcross‐sectional population surveyinteractionintersectionalitymotivation to stopquit attemptsmoking

Identifiers

PMID40116165
PMCPMC12319644

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.