Prevalence and Correlates of Receiving Cigarettes as Gifts and Selecting Preferred Brand Because It Was Gifted: Findings from the ITC China Survey
Bibliographic record
Abstract
Background: Giving cigarettes as gifts is a common practice in China, but there have been few systematic studies of this practice. The present study was designed to estimate the incidence of receiving cigarettes as gifts, correlates of this practice, and its impact on brand selection in a representative sample of urban adult smokers in China. Methods: Data were analyzed from Wave 2 of the International Tobacco Control (ITC) China Survey, where 4843 adult urban smokers were interviewed in six major Chinese cities between October 2007 and January 2008. The incidence of most recent cigarette acquisition due to gifting and the prevalence of preferred brand selection due to having received it as a gift were estimated. Bivariate and adjusted logistic regression models were estimated to identify factors associated with these two outcomes. Results: The incidence of receiving cigarettes as a gift at most recent cigarette acquisition was 3.5%. Smokers who received these gifted cigarettes were more likely to be female, older, have higher educational attainment, live in Beijing, and smoke fewer cigarettes per day. The prevalence of choosing one’s preferred brand due to having received it as a gift was 7.0%, and this was more likely among smokers who lived in Beijing and Guangzhou, had lower educational attainment, smoked less frequently, and had smoked their preferred brand for less than one year. Conclusions: The 3.5% incidence of one’s most recent cigarette acquisition due to gifting is consistent with prevalence estimates based on longer reference periods and translates into the average smoker receiving a gift of cigarettes approximately five times a year. Gifting also appears to have a significant influence on brand preference. Tobacco control interventions in China may need to denormalize the practice of giving cigarettes as gifts in order to decrease the social acceptability of smoking
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".