Patient Understanding of the Neuropsychiatric Risks Associated with Branded Bupropion Hydrochloride Products Used for Smoking Cessation
Bibliographic record
Abstract
BACKGROUND: Bupropion hydrochloride (Zyban) is an effective aid to smoking cessation; however, its use has previously been associated with neuropsychiatric adverse events. Here we report results of the patient Knowledge, Attitudes, and Behavior survey that forms part of the Year 7 Risk Evaluation and Mitigation Strategy (REMS) assessment for Zyban. OBJECTIVE: Assess participants' understanding of the neuropsychiatric risks associated with branded bupropion hydrochloride products that are used for smoking cessation, as described in the Medication Guides. METHODS: A cross-sectional study was conducted among patients ≥ 18 years of age, who had used or filled a prescription for branded bupropion hydrochloride for smoking cessation in the past 6 months. Participants were recruited through an online panel, pharmacy network, or by healthcare provider referral, and invited to complete a survey containing questions regarding the risks associated with the use of branded bupropion hydrochloride products, and whether they had received and read the Medication Guide. The study aimed for ≥ 80% of participants to respond correctly to each question regarding neuropsychiatric risks. RESULTS: From the 50,985 survey invitations distributed, 1017 participants responded, of whom 144 were eligible and 142 completed the survey. Over 80% of participants correctly responded to most neuropsychiatric risk questions. Approximately three-quarters of participants received the Medication Guide when they last filled their prescription, of whom over half read the Medication Guide at that time. CONCLUSIONS: Participants enrolled in this Year 7 REMS survey had good understanding of the neuropsychiatric risks associated with using branded bupropion hydrochloride products for smoking cessation.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".