Registered Nurses’ smoking behaviours and their attitudes to personal cessation
Bibliographic record
Abstract
AIM: The aim of the study was to assess smoking behaviour of nurses including; (1) smoking prevalence and nicotine dependence; (2) demographic characteristics according to smoking status and (3) attitudes to cessation amongst current smokers. BACKGROUND: Smoking amongst nurses is a barrier to the delivery of patient smoking cessation interventions. Studies on the smoking behaviour of nurses have lagged behind government surveys on smoking prevalence in the general population. METHOD: A descriptive, comparative study using a self-administered questionnaire was distributed to 3200 nurses over July and August of 2007 across one major metropolitan health service network in Victoria, Australia. RESULTS: The questionnaire was completed by 1029 nurses, a response rate of 32%. Eleven per cent of nurses (n=113) were current smokers. Nurses who smoked were more likely to be divorced/separated and report smoking amongst family and friends. Smoking was more common amongst nurses who work in psychiatry and the emergency departments. Amongst the nurses who smoked, 45% desired to stop smoking and while 89% had experienced previous quit attempts, only half had ever received help or advice about smoking cessation. The most common factors preventing smoking cessation included fear of withdrawal symptoms including stress, weight gain and anxiety. CONCLUSION: Smoking rates amongst nurses in this sample have declined below smoking rates amongst the general population. Considering the low uptake of smoking cessation support reported in this study, targeted strategies must be developed sensitive to the potential intrapersonal-professional struggle related to personal smoking which is at odds with nurses' health promotion role.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".