Managing Comorbid Tobacco Use Disorder for Individuals With Schizophrenia: Challenges and Opportunities
Bibliographic record
Abstract
ABSTRACT Smoking and tobacco use disorder (TUD) is highly prevalent among individuals with serious and persistent mental illness, particularly those with schizophrenia spectrum disorders. In this clinical case column, we highlight an encounter involving a successful initiation of bupropion for smoking cessation in an individual with schizophrenia. We also review the relevant literature around the epidemiology of TUD among people with schizophrenia, highlight the increased complications and mortality secondary to TUD, and discuss relevant strategies for clinicians to support individuals with serious and persistent mental illness aiming to reduce or stop their tobacco consumption. Le tabagisme et le trouble de l’usage du tabac (TUT) sont très répandus chez les personnes souffrant de maladies mentales graves et persistantes (MMGP), en particulier celles atteintes de troubles du spectre de la schizophrénie. Dans cette chronique de cas cliniques, nous mettons en évidence une rencontre impliquant une initiation réussie du bupropion pour le sevrage tabagique chez une personne atteinte de schizophrénie. Nous passons également en revue la littérature pertinente concernant l'épidémiologie du TUT chez les personnes atteintes de schizophrénie, soulignons l’augmentation des complications et de la mortalité secondaires au TUT, et discutons des stratégies pertinentes pour les cliniciens afin de soutenir les personnes atteintes de MMGP visant à réduire ou à arrêter leur consommation de tabac.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".