Enhancement motives moderate the relationship between high‐arousal positive moods and drinking quantity: Evidence from a 22‐day experience sampling study
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Individuals who consume alcohol may be distinguished by their drinking motives. Enhancement motives involve drinking to enhance positive moods. Research on the moderating effect of enhancement motives on the within-person relation between daily positive mood and drinking has not differentiated between high- (e.g. hyper) and low-arousal (e.g. cheerful) positive moods. The present study addressed this limitation. We hypothesised that enhancement motives would positively moderate the relationship between mid-afternoon high-arousal positive mood and evening drinking. DESIGN AND METHODS: Using a palm pilot-based experience sampling design, 143 undergraduate drinkers answered daily surveys assessing positive mood (mid-afternoon) and drinks (evening) for 22 consecutive days. RESULTS: As hypothesised, enhancement motives strengthened the relation between high-arousal positive moods and drinking. Upon closer examination, the mood-drinking slope for those high in enhancement motives was unexpectedly flat, whereas the mood-drinking slope for those low in enhancement motives was negative. DISCUSSION AND CONCLUSIONS: We demonstrated that high enhancement-motivated drinkers exhibit a high, stable drinking level, regardless of the intensity of their high-arousal positive mood. In contrast, low enhancement-motivated drinkers decrease their drinking when in a high-arousal positive mood state. Clinicians may be able to help reduce heavy alcohol consumption in enhancement-motivated drinkers by teaching them to reduce their drinking when in a high-arousal positive mood state.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".