Alcohol Affects Executive Cognitive Functioning Differentially on the Ascending Versus Descending Limb of the Blood Alcohol Concentration Curve
Bibliographic record
Abstract
BACKGROUND: Executive cognitive functioning (ECF), a construct that includes cognitive abilities such as planning, abstract reasoning, and the capacity to govern self-directed behavior, has been recently researched as an antecedent to many forms of psychopathology and has been implicated in alcohol-related aggression. This study was designed to examine whether differential ECF impairments can be noted on the ascending versus the descending limbs of the blood alcohol concentration curve. METHODS: Forty-one male university students participated in this study. Twenty-one subjects were given 1.32 ml of 95% alcohol per kilogram of body weight, mixed with orange juice, and the remaining 20 were given a placebo. Participants were randomly assigned to either an ascending or descending blood alcohol group and were tested on six tests of ECF on their assigned limb. Subjective mood data were also collected. RESULTS: Intoxicated participants on both limbs demonstrated ECF impairment; the descending-limb group showed greater impairment than their ascending-limb counterparts. Intoxicated subjects were significantly more anxious at baseline than placebo subjects. The introduction of this covariate nullified any significant differences in subjective mood found on either limb of the blood alcohol concentration curve, but ECF impairments remained robust. CONCLUSIONS: Our results support the conclusion that alcohol negatively affects cognitive performance and has a differential effect on the descending versus the ascending limb of the blood alcohol concentration curve. The latter finding may have important ramifications relating to the detrimental consequences of alcohol intoxication.
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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 | 0.001 |
| 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".