Assessment of Smoking Habits Among Patients with Chronic Disease at Hospitals
Bibliographic record
Abstract
Smoking is well-known risk factor for the development and progression of chronic diseases. Patients with chronic diseases are particularly vulnerable to the harmful effects of smoking, yet many continue to smoke despite their condition. This study aims to assess the smoking habits among patients with chronic diseases at hospitals and explore potential interventions to help them quit smoking. A comprehensive review of the literature was conducted to examine the prevalence of smoking among patients with chronic diseases, the impact of smoking on their health outcomes, and the effectiveness of smoking cessation interventions in this population. The results indicate that a significant proportion of patients with chronic diseases continue to smoke, despite the known risks. Various factors contribute to this behavior including nicotine addiction, lack of awareness about the impact of smoking on their condition, and limited access to smoking cessation resources. Healthcare providers play a crucial role in addressing smoking habits among patients with chronic diseases and should incorporate smoking cessation interventions into their routine care. The findings from this study highlight the importance of implementing tailored strategies to help patients with chronic diseases quit smoking and improve their overall health outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".