Smokers who seek help in specialized cessation clinics: How special are they compared to smokers in general population?
Bibliographic record
Abstract
Introduction: Patients of specialized nicotine dependence clinics are hypothesized to form a distinct subpopulation of smokers due to the features associated with treatment seeking. The aim of the study was to describe this subpopulation of smokers and compare it to smokers in general population. Material and methods: A chart review of 796 outpatients attending a specialized nicotine dependence clinic, located in Toronto, Ontario, Canada was performed. Client smoking patterns and sociodemographic characteristics were compared to smokers in the general population using two Ontario surveys – the Ontario Tobacco Survey (n = 898) and the Centre for Addiction and Mental Health Monitor (n = 457). Results: Smokers who seek treatment tend to smoke more and be more heavily addicted. They were older, had longer history of smoking and greater number of unsuccessful quit attempts, both assisted and unassisted. They reported lower education and income, had less social support and were likely to live with other smokers. Conclusions: Smokers who seek treatment in specialized centers differ from the smokers in general population on several important characteristics. These same characteristics are associated with lower chances for successful smoking cessation and sustained abstinence and should be taken into consideration during clinical assessment and treatment planning.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".