Socio‐economic disadvantage at the area level poses few direct barriers to smoking cessation for Australian smokers: Findings from the International Tobacco Control Australian cohort survey
Bibliographic record
Abstract
INTRODUCTION: Area-level indicators of socio-economic variation are frequently included in models of individual health outcomes. Area disadvantage is linearly related to smoking prevalence, but its relation to cessation outcomes is less well understood. AIMS: To explore the relationship between area-level disadvantage and prospective data on smoking cessation. DESIGN AND METHODS: The Australian cohort of the International Tobacco Control Four-Country Survey (N = 3503) was used to prospectively examine the contribution of area-level socio-economic disadvantage to predicting three important smoking-cessation outcomes: making a quit attempt, achieving 1 month abstinence and achieving 6 month abstinence from smoking, while controlling for individual-level socio-economic indicators and other individual-level covariates related to smoking cessation. RESULTS: Only two independent associations were observed between socio-economic disadvantage and cessation outcomes. Area-level disadvantage was related to 1 month abstinence in a non-linear fashion, and the individual experience of smoking-induced deprivation was associated with a lower likelihood of making quit attempts. DISCUSSION: Despite the documented higher prevalence of smoking among the more disadvantaged and in more disadvantaged areas, socio-economic disadvantage was not consistently related to making quit attempts, nor to medium-term success. Nevertheless, indirect effects of disadvantage, like its impact on psychological distress, cannot be ruled out, and considering smokers' individual psychosocial circumstances is likely to aid cessation efforts. CONCLUSION: Socio-economic disadvantage, particularly at the area level, poses few direct barriers to smoking cessation.
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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 | 0.002 | 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) | 0.001 | 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 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".