HELPING HOSPITALISED CLIENTS QUIT SMOKING: A STUDY OF RURAL NURSING PRACTICE and BARRIERS
Bibliographic record
Abstract
Brief interventions have been identified as a useful tool for facilitating smoking cessation, particularly in the acute care setting and in areas where access to specialist staff is limited, such as rural Australia. A self-administered survey was used to determine current rural nursing staff practices in relation to brief intervention for smoking cessation, and to ascertain the perceived level of support, skills, needs and barriers amongst these staff to conducting brief interventions. The major findings include that while the majority of respondents were aware of their patients' smoking status, most were not very confident about assisting smoking patients to quit. Casually employed nurses were much less likely to be aware of patient smoking status than nurses employed full-time or permanent part-time. Only one-quarter to one-third of nurses did not believe assisting patients to quit was part of their role, and the vast majority of nurses reported that they were non-smokers. Future programs incorporating the routine use of brief interventions will need to consider these findings.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".