Preliminary evaluation of a human laboratory model of impaired control over alcohol using intravenous alcohol self-administration
Bibliographic record
Abstract
Impaired control over alcohol is central to alcohol use disorder, but most research on impaired control is limited to self-report methods. This study applied intravenous alcohol self-administration to conduct a preliminary investigation of a novel human laboratory model of impaired control. Heavy episodic drinkers (ages 19-22 years) completed a two-hour intravenous alcohol self-administration session that involved an incentive to maintain breath alcohol concentration below 80 mg%. Impaired control was operationalized based on whether participants exceeded (impaired control positive; IC+) or adhered to (impaired control negative; IC-) the breath alcohol concentration limit, as well as the discrepancy between intended and actual peak breath alcohol concentration. Analyses of subjective processes revealed that IC+ participants tended to underestimate their peak breath alcohol concentration relative to IC- participants. Further, IC+ reported greater craving after an initial priming phase, and craving mediated the relationship between self-report impaired control and discrepancies between intended and actual breath alcohol concentration. IC+ participants also showed stronger within-person associations between state changes in stimulation and momentary alcohol self-administration throughout the session. Laboratory impaired control indices demonstrated convergent validity with an established self-report measure of impaired control. These findings provide preliminary validation of a novel human laboratory model of impaired control in a sample of young heavy episodic drinkers, and offer insight into the role of subjective responses (craving, stimulation) in impaired control.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".