Brief smoking cessation advice from practice nurses during routine cervical smear tests appointments: a cluster randomised controlled trial assessing feasibility, acceptability and potential effectiveness
Bibliographic record
Abstract
The aim of this study is to assess the potential effectiveness, acceptability and feasibility of a brief smoking cessation intervention delivered as part of cervical screening. A cluster randomised controlled trial was conducted with clinic week as the unit of randomisation, comparing a group (n=121) receiving brief smoking cessation advice supplemented with written information given by practice nurses during cervical smear test appointments, with a group (n=121) not receiving this advice. Outcomes were intention to stop smoking (potential effectiveness); intention to attend for future cervical screening (acceptability); duration of intervention (feasibility). 172/242 (71%) and 153/242 (63%) participants completed 2-week and 10-week follow-ups, respectively. Compared to women in the control group, those in the intervention group had higher intentions to stop smoking at 2-weeks (adjusted mean difference 0.51, 95% CI: -0.02 to 1.03, P=0.06) and 10-weeks (adjusted mean difference 0.80, 95% CI 0.10 to 1.50, P=0.03). The two groups had similarly high intentions to attend for future screening. Consultations in the intervention arm took a mean of 4.98 min (95% CI: 3.69 to 6.27; P<0.001) longer than the control arm. In conclusion, brief smoking cessation advice given by practice nurses as part of cervical screening seems acceptable, feasible and potentially effective. Evidence is lacking on the effectiveness and cost effectiveness of this intervention in achieving biochemically validated smoking cessation.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".