Smoking cessation interventions in Australian drug treatment agencies: a national survey of attitudes and practices
Bibliographic record
Abstract
A cross-sectional survey was mailed to all Australian drug and alcohol treatment agencies to assess their smoking cessation policies and practices and related staff attitudes. Barriers to smoking cessation interventions were also examined. Completed questionnaires were returned by 213 managers and 204 other staff representing 260 agencies (59.8% consent rate). Approximately one-quarter of agencies have smoking cessation intervention policies and one-third of clients receive adequate smoking advice. Of 12 intervention strategies, only the recording of smoking status on file occurs in a majority of cases. Concerns about the potential negative impact of smoking interventions and lack of client interest were endorsed as very important barriers by the highest percentage of respondents. 12.6% of managers and 16.5% of other staff agreed that it is occasionally useful for staff to smoke with a client. Smoking cessation receives little systematic attention from drug and alcohol agencies. Training and policy initiatives are needed urgently to address negative staff attitudes impeding progress in this area.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".