The relationship between impaired control, impulsivity, and alcohol self-administration in nondependent drinkers.
Bibliographic record
Abstract
Impaired control over drinking is a significant marker of alcohol use disorder (AUD), and a potential target of intervention (Heather, Tebbutt, Mattick, & Zamir, 1993; Leeman, Toll, Taylor, & Volpicelli, 2009). Impaired control may be related to, but conceptually distinct from, impulsivity (Leeman, Patock-Peckham, & Potenza, 2012; Leeman, Ralevski, et al., 2014). However, the relationship between impaired control, impulsivity, and alcohol consumption, particularly in nondependent drinkers is less clear. This study aimed to characterize these relationships using a free-access intravenous alcohol self-administration (IV-ASA) paradigm in nondependent drinkers (N = 48). Results showed individuals with higher self-reported impaired control achieved higher blood alcohol concentrations (BAC) during the IV-ASA session and reported greater hedonic subjective responses to alcohol. Higher impaired control was also associated with greater positive urgency and reward sensitivity. Moderated-mediation analysis showed that the relationship between positive urgency and peak BAC was mediated by impaired control, and partially moderated by subjective alcohol response. These findings highlight the critical role of impaired control over drinking on alcohol consumption and subjective responses in nondependent drinkers. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".