Acute effects of nicotine on alcohol cue-reactivity in nondependent and dependent smokers.
Bibliographic record
Abstract
Evidence from alcohol self-administration studies suggests that nicotine replacement therapy may influence subjective and behavioral responses to alcohol. However, its effect on alcohol cue-reactivity is unknown. The present study examined the impact of acutely administered nicotine on subjective responses to alcohol-focused pictorial stimuli. In a mixed within/between-subjects design, nondependent smokers (n = 51) and dependent smokers (n = 45) who socially drink were assigned to either a nicotine (4 mg) or placebo lozenge condition following overnight tobacco abstinence. Following lozenge absorption, participants viewed neutral images followed by alcohol-focused pictures. Craving measures for alcohol and tobacco were completed at baseline, following lozenge absorption, following neutral cues, and following alcohol cues. The presentation of alcohol cues increased alcohol-related craving relative to neutral cues, especially among men, but the administration of nicotine did not influence the magnitude of these effects. Nicotine lozenges were found to decrease intentions to smoke and withdrawal-related craving in dependent but not in nondependent smokers. Finally, the presentation of alcohol cues was found to increase intentions to smoke relative to neutral cues across participants regardless of lozenge condition. Findings suggest that although the presentation of alcohol cues can increase alcohol- and tobacco-related cravings in smokers, such effects do not appear to be affected by acute nicotine administration.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".