Are Occasional Smokers a Heterogeneous Group? An Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Occasional smokers represent an important segment of all smokers and have been described to be a heterogeneous group in terms of past experience and likelihood of maintaining nondaily smoking behavior. METHODS: In the prospective Ontario Tobacco Survey, 408 occasional smokers were followed for a year. Characteristics of subgroups of occasional smokers, as suggested by previous literature, were studied for personal and smoking behavior group differences. Agglomerative hierarchical clustering was also used to empirically identify subgroups of occasional smokers using average linkage. Smoking status at 1-year follow-up was examined overall and by the identified subgroups to determine if any were useful predictors of persistent status as nondaily smoking and likelihood of smoking cessation. RESULTS: Significant differences were seen among the subgroups of occasional smokers suggested in previous studies including the number of quit attempts, setting a firm quit date, and whether or not participants cared others knew they smoked in descriptive analyses. Exploratory cluster analysis suggested 4 clusters of occasional smokers based on differences in age, perceived addiction, and history of daily smoking. Subgroups based on participants' history of smoking, self-reported addiction level, and empirically identified cluster subgroups resulted in significant differences of smoking status at 1-year follow-up. CONCLUSIONS: This study suggests that occasional smokers may be a heterogeneous group with different subgroups characterized by age, accumulated smoking experience and smoking pattern, as well as factors associated with the likelihood of quitting altogether, over time, and perceived addiction.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".