Evaluating the Associations Between Exposure to Tobacco Interventions During Inpatient Treatment and Substance Use Outcomes: Findings From a Natural Experiment
Bibliographic record
Abstract
OBJECTIVE: In this study, we took advantage of a natural experiment that occurred within a substance use disorders (SUD) treatment setting which first saw the implementation of an evidence-based practice (EBP) for tobacco cessation, followed by the implementation of a tobacco-free policy (TFP) that included a campus-wide tobacco ban. We sought to examine how implementation of the EBP and TFP was associated with substances use outcomes, in addition to tobacco use, up to 3-months posttreatment. METHODS: Data were collected from patients in a substance use disorders treatment program at baseline, discharge, 1-, and 3-months posttreatment. Using a quasi-experimental design and generalized estimating equations, we modelled how patients' (N = 480) exposure to one of 3 interventions (1: treatment as usual [TAU], 2: EBP, and 3: EBP + TFP) was associated with overall abstinence from tobacco, alcohol, and other substances over time. Measures of tobacco use frequency, amount, and quit attempts were also modelled among a sub-sample of participants who self-reported using tobacco before treatment. RESULT: Exposure to the EBP + TFP was associated with increased tobacco abstinence (odds ratio [OR] = 1.93, 95% confidence interval [CI] [1.29, 2.90]) over time, including decreases in tobacco use frequency (OR = 0.78, 95% CI [0.68, 0.89]) and amount (OR = 0.80, 95% CI [0.67, 0.96]), and increased in likelihood of making a quit attempt (OR = 1.75, 95% CI [1.10, 2.80]) compared to TAU. Exposure was not associated with alcohol and/or other substance use. CONCLUSIONS: Comprehensive tobacco interventions that include EBP + TFP can promote tobacco cessation and reduced tobacco use following inpatient SUD treatment, without adversely affecting the use of other substances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".