Functional Relationships of Binge Drinking and Alcohol-Related Problems With Posttraumatic Stress Symptoms in a Pilot Sample of Veterans
Bibliographic record
Abstract
OBJECTIVE: Posttraumatic stress (PTS) symptoms and problematic alcohol use (e.g., binge drinking and alcohol-related problems; ARP) commonly co-occur following stressors and traumatic events. Ecological momentary assessment methods can clarify the functional relationships between these conditions. METHODS: Twenty-five trauma-exposed combat veterans with pre-pandemic heavy drinking histories completed three daily smartphone surveys for four weeks, assessing binge drinking, ARP, PTS symptoms, and positive and negative affect. Within-person multi-level models assessed PTS and alcohol relationships, covarying for affect and demographics. RESULTS: Within-person variation in PTS was inversely associated with binge drinking but not associated with ARP after adjustment for interindividual heterogeneity. Within-person variation in ARP was not associated with PTS after adjustment for interindividual heterogeneity. The covariate of negative affect was positively associated with ARP and PTS. CONCLUSIONS: Findings suggest negative affect, rather than PTS, has the strongest association with variation in ARP symptoms in this at-risk sample. There was also evidence of individual differences in the strength and direction of effects.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".