The role of income and psychological distress in the relationshipbetween work loss and smoking cessation: Findings from threeInternational Tobacco Control (ITC) Europe countries
Bibliographic record
Abstract
INTRODUCTION: The relationship between work loss and smoking has not been studied extensively, and underlying factors are often not examined. The aim of this study was to test two hypotheses. First, work loss is associated with greater intention to quit and more likelihood of smoking cessation, and this relationship is moderated by a decrease in income. Second, work loss is associated with lower quit intention and lower rates of smoking cessation, and this relationship is moderated by an increase in psychological distress. METHODS: We used pooled data from three countries participating in the ITC Project: France, Germany and the Netherlands (n=2712). We measured unemployment, income and psychological distress at two consecutive survey waves, and calculated changes between survey waves. We first conducted multiple logistic regression analyses to examine the association between work loss and smoking cessation behavior. Next, we added income decrease and psychological distress increase to the models. Finally, we added interaction terms of work loss by income decrease and work loss by distress increase to the model. RESULTS: Work loss was not associated with quit intention, quit attempts, and quit success. When income decrease and psychological distress increase were added to the model, we found a positive association between distress increase and quit attempts. The interactions, however, were not statistically significant. CONCLUSIONS: Our results indicate that smokers who become unemployed and face a decrease in income are not less likely to quit smoking than smokers who are employed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".