Understandings of the component causes of harm from cigarette smoking in Australia
Bibliographic record
Abstract
INTRODUCTION AND AIMS: To investigate relationships between smoking-related behaviours and knowledge of the disease risks of smoking and the causes of smoking harms, using a four-way division of 'component causes': nicotine, other substances found in unburned tobacco, combustion products of tobacco and additives. DESIGN AND METHODS: The data were collected using an on-line survey in Australia with 1047 participants in three groups; young non-smokers (18 to 25), young smokers (18 to 25) and older smokers (26 and above). RESULTS: Most participants agreed that cancer and heart disease are major risks of smoking but only a quarter accurately quantified the mortality risk of lifetime daily smoking. Very few (two of 1047) correctly estimated the relative contributions of all four component causes. Post-hoc analyses reinterpreting responses as expressions of relative concern about combustion products and nicotine showed that 29% of participants rated combustion products above nicotine. We delineated six relative concern segments, most of which had distinctive patterns of beliefs and actions. However, higher levels of concern about combustion products were only weakly positively associated with harm reducing beliefs and actions. DISCUSSION AND CONCLUSIONS: Most smokers do not appear to understand the risks of smoking and their causes well enough to be able to think systematically about the courses of action open to them to reduce their health risk. To facilitate informed decision-making, tobacco control communicators may need to better balance the dual aims of creating fear/negative affect about smoking and imparting knowledge about the health harms and their mechanisms.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".