Impact of Experimentally Induced Positive and Anxious Mood on Alcohol Expectancy Strength in Internally Motivated Drinkers
Bibliographic record
Abstract
The effects of musically-induced positive and anxious mood on explicit alcohol-related cognitions (alcohol expectancy strength) in 47 undergraduate students who consume alcohol either to enhance positive mood states (for enhancement motives) or to cope with anxiety (for anxiety-related coping motives) were investigated. Pre- and post-mood induction, participants completed the emotional reward and emotional relief subscales of the Alcohol Craving Questionnaire - Now. The hypothesis that anxiety-related coping motivated drinkers in the anxious mood condition (but not those in the positive mood condition) would exhibit increases in strength of explicit emotional relief alcohol expectancies after the mood induction was supported. An additional, unanticipated finding was that enhancement-motivated drinkers in the anxious condition also showed significant increases in strength of explicit emotional relief (but not emotional reward) alcohol expectancies. The hypothesis that enhancement-motivated (but not anxiety-related coping motivated) participants would exhibit increases in explicit emotional reward expectancies following exposure to the positive mood induction procedure was not supported. Taken together with past research findings, the current results highlight the importance of distinguishing between subtypes of negative affect (i.e., anxious and depressed affect) in exploring the affective antecedents of explicit alcohol outcome expectancies.
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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 | 0.002 |
| 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) | 0.001 | 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".