Motives for Smoking Cessation are Associated with Stage of Readiness to Quit Smoking and Sociodemographics among German Industrial Employees
Bibliographic record
Abstract
PURPOSE: To test the relationships among particular motives for smoking cessation, stage of readiness to quit (preparation or contemplation), and sociodemographic characteristics. DESIGN: A cross-sectional study to examine attitudes toward and use of health promotion at the worksite, using a self-administered questionnaire. SETTING: Two German metal companies. SUBJECTS: Of 1641 responding employees (response rate 65% in company A and 44% in company B), 360 smokers who intended to quit immediately (n = 105) or in the near future (n = 255) were analyzed. MEASURES: The questionnaire comprised of sociodemographic characteristics, smoking behavior, smoking history, readiness to quit smoking, motives to quit, such as coworkers' complaints and health-related or financial concerns. Chi-squared tests and multiple logistic regression analyses were performed. RESULTS: Health-related reasons (94%) predominated financial (27%) or image-related (14%) reasons for smoking cessation. Participants in the cessation preparation group were more likely to report an awareness of being addicted (79.6% vs. 58.2%; p < .001) and the negative public image (22.5% vs. 11.6%; p < .01) as reasons for quitting compared with those in the contemplation group. In multivariable regression models, the motives for smoking cessation, including reduced performance, family's and coworkers' complaints, pregnancy/children, and negative public image, but not health-related and financial concerns, differed significantly by gender, age, marital status, education, and occupational status. CONCLUSIONS: Motives for smoking cessation vary according to the individual's level of readiness to quit and sociodemographic background.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".