[Smoking prevalence in A Mami hospital of Ariana: prospective study about 700 health professionals].
Bibliographic record
Abstract
BACKGROUND: smoking is one of the most serious threats to public health worldwide. Health structures are the cornerstone of each program against smoking , or some studies have shown a prevalence of smoking as high in hospitals than in the general population. Aim : To assess the prevalence of smoking, smoking behavior and attitudes of health professionals towards smoking within the A Mami Ariana Hospital METHODS: This is a cross-sectional survey conducted among 700 health professionals (doctors, nurses, workers, technicians and administrative staff) in the first quarter of 2010, based on a detailed questionnaire containing 15 closed-end items. RESULTS: The average age was 37 years and the sex ratio 0,5. Response rate to questionnaire was 81,4% and overall smoking prevalence 24,8%, five times higher in men (52,5% vs 9,8% p< 0,001). Smoking was greater among workers, night health professionals employees and employees of technical services, administration and intensive care services and only 13% among doctors. 50% of the surveyed have already tried at least once to quit, twice as many women than men. Former smokers accounted for 5,5% of all health professionals. CONCLUSION: Although our hospital has been declared non-smoking area since 2009, 75% of professionals continue to smoke at the scene of their work. Strengthening of existing measures against smoking as smoking bans in the hospital, and improving training of health professionals on the dangers of smoking and ways of weaning are needed now.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".