Changes in coping and social motives for drinking and alcohol consumption across the menstrual cycle
Bibliographic record
Abstract
BACKGROUND: Alcohol use has been reported to fluctuate over women's menstrual cycles (MCs), with increased intake occurring premenstrually/menstrually (phases characterized by heightened negative affect) and during the ovulatory phase (a phase characterized by positive affect). This suggests women may drink for particular emotion-focused reasons at specific points in their cycles. However, no research had yet examined MC variability in drinking motives, or links between cycle-related changes in drinking motives and alcohol consumption. METHODS: = 4.7) completed daily diary measures (via Smartphone surveys), with questions pertaining to state drinking motives and quantity of alcohol consumed for the course of a full MC. RESULTS: Drinking motives differed by cycle phase. Women reported a slight increase in drinking to self-medicate for negative affect premenstrually, with drinking to cope peaking in the menstrual phase and declining mid-cycle. Women reported a slight increasing trend across the cycle in social motives for drinking, while enhancement motives remained relatively stable across the cycle. Cycle-related changes in drinking motives predicted increases in the quantity of alcohol consumed. Drinking to cope with negative affect predicted a greater number of drinks menstrually (days 1-5). While social motives predicted a greater number of drinks during the follicular and ovulatory phases (days 5-16), enhancement motives were unrelated to drinking quantity across cycle phase. CONCLUSIONS: Clinicians should be attentive to cycle phase when treating reproductive-aged women with alcohol disorders (e.g., encouraging the use of healthier means of coping with negative affect during menses).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".