Smoking Cessation Approaches for Persons With Mental Illness or Addictive Disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Persons with psychiatric illnesses are about twice as likely as the general population to smoke tobacco. They also tend to smoke more heavily than other smokers. This critical review of the literature identified 24 empirical studies of outcomes of smoking cessation approaches used with samples of persons with mental disorders. METHODS: The authors conducted searches of large health care and other databases for the years 1991 through 2001, using the key terms smoking, smoking cessation, nicotine, health/hospital/smoke-free policy, and psychiatry/ mental/substance abuse disorders. RESULTS AND CONCLUSIONS: The majority of interventions combined medication and psychoeducation. Although the studies were not uniform enough to allow a meta-analysis, the recorded quit rates of patients with psychiatric disorders were similar to those of the general population. Clinicians could usefully devote more effort to smoking cessation in populations with mental illness or addictions.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it