The impact of bupropion on psychomotor performance.
Bibliographic record
Abstract
INTRODUCTION: The NDRI (noradrenalin-dopamine re-uptake inhibitor) bupropion SR (sustained-release) is marketed as Wellbutrin* for treatment of depression or Zyban as a smoking cessation aid. There has been considerable interest in the possibility of returning aircrew to restricted flying duties once stabilized on bupropion SR after resolution of depressive symptoms, or while taking bupropion SR for smoking cessation. This study was undertaken to determine whether bupropion SR affects psychomotor performance. METHOD: There were 24 subjects (18 men and 6 women) who were assessed for psychomotor performance during placebo and bupropion SR treatment in a double-blind cross-over in counter-balanced order. Each treatment arm lasted 5 wk. The daily bupropion SR dose was 150 mg during week 1, and 300 mg during weeks to 2 to 5. Subjects completed a drug side-effect questionnaire and were tested on two psychomotor test batteries once per week during each of the placebo and drug arms. RESULTS: There was no significant Impact of bupropion SR on serial reaction time, logical reasoning, serial subtraction, or multitask performance. With respect to drug side effects there was a main effect of drug on "number of awakenings" (p < 0.048), "difficulty returning to sleep" (p < 0.004), and "dry mouth" (p < 0.049). There was no impact of bupropion SR on dizziness. DISCUSSION: While we found some of the expected side effects due to bupropion SR, there was no effect on psychomotor performance. These findings support the possibility of returning aircrew to restricted flight duties (e.g., in non-fast jet aircraft) under close observation once stabilized on bupropion SR.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.006 | 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".