Smokers with financial stress are more likely to want to quit but less likely to try or succeed: findings from the International Tobacco Control (ITC) Four Country Survey
Bibliographic record
Abstract
OBJECTIVE: To examine the association of financial stress with interest in quitting smoking, making a quit attempt and quit success. DESIGN AND PARTICIPANTS: The analysis used data from 4984 smokers who participated in waves 4 and 5 (2005-07) of the International Tobacco Control (ITC) Four Country Survey, a prospective study of a cohort of smokers in the United States, Canada, the United Kingdom and Australia. MEASUREMENT: The outcomes were interest in quitting at wave 4, making a quit attempt and quit success at wave 5. The main predictor was financial stress at wave 4: '. . . because of a shortage of money, were you unable to pay any important bills on time, such as electricity, telephone or rent bills?'. Additional socio-demographic and smoking-related covariates were also examined. FINDINGS: Smokers with financial stress were more likely than others to have an interest in quitting at baseline [odds ratio (OR): 1.63; 95% confidence interval (CI): 1.22-2.19], but were less likely to have made a quit attempt at follow-up (OR: 0.74; 95% CI: 0.57-0.96). Among those who made a quit attempt, financial stress was associated with a lower probability of abstinence at follow-up (OR: 0.53; 95% CI: 0.33-0.87). CONCLUSIONS: Cessation treatment efforts should consider assessing routinely the financial stress of their clients and providing additional counseling and resources for smokers who experience financial stress. Social policies that provide a safety net for people who might otherwise face severe financial problems, such as not being able to pay for rent or food, may have a favorable impact on cessation rates.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".