Alcohol selectively impairs negative self-relevant associations in young drinkers
Bibliographic record
Abstract
The stress-dampening effects of alcohol have been attributed to 'appraisal disruption'- decreased ability of stimuli to evoke threatening associations in memory. Appraisal disruption could apply to oneself as well as situational stimuli. This question was investigated in undergraduate drinkers (n=90/Gender) with low or high anxiety sensitivity (AS; n=90/AS Group), a trait linked with hyper-vigilance to threat. Subjects received alcohol (0.7 g/kg males; 0.63 g/kg females), placebo or soft drink and performed a speech about their appearance. Sequence of drink administration and speech advisory (threat) was manipulated between subjects: Threat before Drink, Threat after Drink, No-Threat Control. The Implicit Association Test measured self-relevant associations based upon time to classify positive and negative attribute words (e.g. Cute, Ugly) paired with self-relevant or non-self-relevant object words (e.g. Me, Them). Alcohol selectively slowed negative self-relevant decisions, regardless of other factors. Relative fluency of negative versus positive decisions (D) correlated inversely with state anxiety and systolic blood pressure immediately before speech performance, and correlated directly with severity of alcohol problems. These findings are consistent with the Appraisal Disruption hypothesis. Preferential impairment of negative self-relevant associations may decrease perceived vulnerability under alcohol and increase risk for alcohol problems in young drinkers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".