An ethnographic study of tobacco control in hospital settings
Bibliographic record
Abstract
BACKGROUND: Tobacco control in hospital settings is characterised by a focus on protection strategies and an increasing expectation that health practitioners provide cessation support to patients. While practitioners claim to have positive attitudes toward supporting patient cessation efforts, missed opportunities are the practice norm. OBJECTIVE: To study hospital workplace culture relevant to tobacco use and control as part of a mixed-methods research project that investigated hospital-based registered nurses' integration of cessation interventions. DESIGN: The study was conducted at two hospitals situated in British Columbia, Canada. Data collection included 135 hours of field work including observations of ward activities and designated smoking areas, 85 unstructured conversations with nurses, and the collection of patient-care documents on 16 adult in-patient wards. RESULTS: The findings demonstrate that protection strategies (for example, smoking restrictions) were relatively well integrated into organisational culture and practice activities but the same was not true for cessation strategies. An analysis of resources and documentation relevant to tobacco revealed an absence of support for addressing tobacco use and cessation. Nurses framed patients' tobacco use as a relational issue, a risk to patient safety, and a burden. Furthermore, conversations revealed that nurses tended to possess only a vague awareness of nicotine dependence. CONCLUSION: Overcoming challenges to extending tobacco control within hospitals could be enhanced by emphasising the value of addressing patients' tobacco use, raising awareness of nicotine dependence, and improving the availability of resources to address addiction issues.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".