Providing Tobacco Treatment in a Community Mental Health Setting
Bibliographic record
Abstract
OBJECTIVE: Individuals with mental illnesses (MIs) are disproportionately affected by tobacco-related disease burden because of higher tobacco use prevalence and poor tobacco treatment outcomes. This pilot study examines the outcomes of delivering an evidence-based tobacco treatment program (the Cooper-Clayton program) in a community mental health setting. DESIGN: A prospective nonequivalent group design was used to assess outcomes. SAMPLE: This study included 47 participants, of which 19 were in a community mental health setting and 28 were from two non-mental-health settings. MEASUREMENTS: Information on sociodemographic (gender, age, educational level, and current life stressors) and medical, MI, substance use, and tobacco use and cessation histories were obtained. Program completion and smoking cessation at the end of treatment (verified with expired carbon monoxide monitoring) were assessed. INTERVENTION: The program consists of combining behavioral counseling with nicotine replacement therapy for 12 weeks. RESULTS: Participants from the mental health setting were significantly less educated, had greater medical comorbidities, had greater psychiatric and mental health histories, and had greater perceived secondhand tobacco smoke exposure as compared with those from the non-mental-health settings. Thirty-two percent of the participants (6/19) completed the program in the mental health site as compared with 68% (19/28) from the non-mental-health site. None of those from the mental health site achieved cessation as compared with 68% of those from non-mental-health sites. CONCLUSIONS: The differential outcomes of evidence-based tobacco treatment programs in non-mental-health versus mental health settings may suggest the need to modify existing tobacco treatment approaches for those with MIs in community settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".