Smoking Habit among the Relatives of Patients with Serious Smoking-Related Disorders
Bibliographic record
Abstract
OBJECTIVE: To assess smoking habit and awareness of smoking as a potential cause of disease among relatives of patients with serious smoking-related disorders. DESIGN AND SETTING: A survey using a face-to-face interview-assisted questionnaire at the Ege University Hospital between October 1998 and March 1999. SUBJECTS: We interviewed 242 relatives of patients with serious smoking-related disorders, of whom 56.6% were female and 43.4% male. The mean age was 41.2 +/- 13.2 years (15-75). One relative per patient completed the questionnaire and the chosen relative took care of the patient during his illness and accompanied him during hospital visits. MAIN OUTCOME MEASURES: We assessed the relationship between smoking habit and the perception of smoking as a potential cause of illness by the relatives. Statistical analysis was performed by chi(2) test. RESULTS: The prevalence of smoking among relatives was 37.6% [49.5% males (n = 105) and 28.5% females (n = 137), p = 0.0003] and an additional 20.2% were ex-smokers. Of the relatives, 86.4% knew that the diseases were directly related to smoking, and 37.8% of these people were smokers and 21.5% ex-smokers. Only 7.2% reported that they had quit smoking after being influenced by the diseases of the patients. The decision to quit was statistically unrelated to the awareness of smoking as the cause of disease. Of all the relatives, 69.2% had tried to quit at least once, 86.8% considered quitting, and 89.0% considered using professional help for smoking cessation. CONCLUSION: The findings show that even though this group of smokers is aware of the harmful effects of smoking they cannot successfully quit smoking; however, the majority reconsider quitting and receiving professional help.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".