The variation in the self-perceived quality of life and health care amongst smokers, passive smokers, ex-smokers and non-smokers in Canada
Bibliographic record
Abstract
In 2012 nearly 20% of Canadians aged 12 and above had stated they smoked tobacco frequently, costing the health care system over $4.4 billion in health related illnesses. The aim of this study was to assess degrees of tobacco inhalation of smokers, non-smokers, ex-smokers, passive smokers and current smokers and their perceived quality of life and health. The survey was conducted in the waiting room of two medical walk-in-clinics. The questionnaire comprised of four main aspects including age of the patient, identify themselves as a frequent smoker, a non-smoker (passive) who is regularly exposed to smoke, a past (ex-) smoker and a non-smoker who is not regularly exposed to tobacco smoke. Valid consent was obtained from the patients and patients under the age of 18 were not included in the study. A total of 387 patients completed the survey including 198 non-smokers, 83 passive smokers, 51 ex-smokers and 55 current smokers. The oldest group was the ex-smokers of a mean age of 52.6 years and the youngest was the smokers at 36.6 years (p < 0.001). In between were the passive smokers at 43.6 years and non-smokers at 48.2 years (p= 0.002). This research found that current smokers have a persistently lower self-reported quality of life and health care as compared with the other groups. It is also evident that patients who quit smoking do not suffer a loss in quality of life nor health compared to non-smokers. In addition, this research indicates that smoking not only impacts a patient's health, but their overall QoL as well.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".