Does how you quit affect success? A comparison between abrupt and gradual methods using data from the International Tobacco Control Policy Evaluation Study
Bibliographic record
Abstract
Two recommended quit methods in standard cessation programs involve either gradual reduction of smoking prior to complete abstinence ("cut down") or abrupt abstinence from cigarettes ("cold turkey"). This study examined the reported use, characteristics of users, and the impact of self-selected strategy choice on quitting success and relapse of adult smokers who reported quitting on their own. Data came from the first three waves of the International Tobacco Control Policy Evaluation 4-Country Survey (ITC-4). The ITC-4 is a random-digit-dialed telephone survey of a cohort of more than 8,000 adult smokers from the United Kingdom, the United States, Canada, and Australia, with a 75% follow-up rate. The results indicated that 68.5% of the smokers who had made a quit attempt between waves reported using the cold-turkey method. Of those who used the cold turkey method, 22% and 27% succeeded at Waves 2 and 3, respectively, compared with the 12% and 16%, respectively, who used the cut-down method. Multivariate analyses revealed that cold-turkey users were more likely to be aged 25-39 years, male, from the United Kingdom, and smoking heavily, and had lower perceived dependence. Controlling for sociodemographic and known predictors of quitting including use of medications, we found that smokers who used the cold-turkey method to quit were almost twice as likely to abstain for a month or more in their attempt. Overall, we cautiously conclude that cold turkey should be the recommended strategy for smokers who want to quit on their own.
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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 | 0.022 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".