Smoker interest in lower harm alternatives to cigarettes: National survey data
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to examine knowledge and attitudes to lower harm alternatives to cigarettes among New Zealand (NZ) smokers. METHODS: The NZ arm of the International Tobacco Control Policy Evaluation Survey (ITC Project) utilizes the NZ Health Survey (a national sample). From this sample, we surveyed adult smokers (N = 1,376). RESULTS: Knowledge about smokeless tobacco was poor, with only 16% regarding such products as less harmful than ordinary cigarettes. Only 7% considered such products to be "a lot less" harmful. When participants were asked to assume that these products were much less harmful than cigarettes, 34% of smokers stated that they would be interested in trying smokeless tobacco products, with another 11% saying "maybe" or "don't know." In the multivariate analysis, Māori smokers were significantly more interested in trying smokeless products than Europeans in all 3 models considered (e.g., Model 1: adjusted odds ratio [AOR] = 1.71, 95% CI = 1.23-2.37). There was also significantly increased interest for those concerned about the impact of smoking on health and quality of life in the future (AOR = 1.44, 95% CI = 1.17-1.78). But interest did not vary significantly by 2 measures of socioeconomic status and varied inconsistently by 2 measures of financial stress. DISCUSSION: The finding that one third of smokers said that they would be interested in trying smokeless products suggests that these products could have a role as part of a tobacco epidemic endgame that phases out smoked tobacco. Differences in interest level by ethnic group may be relevant to stimulating further work in this area (e.g., among those health workers concerned for smokers with the highest need to quit).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".