Best practice for tobacco smoking policies within an acute substance use disorder care facility: considerations from a withdrawal management setting in British Columbia, Canada
Bibliographic record
Abstract
Smoking-related illness has historically been a major cause of death in persons with substance use disorders. Smoking cessation has the potential to support improved substance use disorder outcomes, as well as improved physical and mental health outcomes in persons receiving other substance use disorder treatment. However, tobacco abstinence-oriented policies within substance use disorder care settings may create barriers to clients who are uninterested in quitting smoking being able to access other potentially lifesaving substance use disorder treatment. In British Columbia, where the drug toxicity crisis has become the leading cause of unnatural death, reducing barriers to accessing substance use disorder treatment is a key public health priority. We present areflection on considerations from a withdrawal management settingof a smoking policy change within that facility and review the potential benefits and harms of permissive smoking policies within substance use disorder care environments. Benefits include the elimination of a barrier to accessing other substance use treatment, patient autonomy over participation in smoking cessation treatment and the potential for less covert smoking and associated risks. Risks include ongoing physical and mental health harms of smoking, potentially poorer other substance use treatment outcomes, risks of tobacco relapse to other clients and secondhand smoke exposure to staff and other clients. Further research will be needed to explore the impacts of this policy change and evaluate the potential role for other smoking cessation innovations, including expansion of nicotine replacement options such as provision of nicotine electronic cigarette devices.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.022 | 0.022 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".