Alcohol‐induced blackouts at age 20 predict the incidence, maintenance and severity of alcohol dependence at age 25: a prospective study in a sample of young Swiss men
Bibliographic record
Abstract
BACKGROUND AND AIMS: Alcohol-induced blackout (AIB) is a common alcohol-related adverse event occurring during teenage years. Although research provides evidence that AIB predicts acute negative consequences, less is known about the associations of AIB with chronic consequences, such as alcohol dependence (AD). This study estimated the associations between an experience of AIB at age 20 and the incidence, maintenance and severity of AD at age 25 among Swiss men. DESIGN: Prospective cohort study with 5.5 years separating baseline and follow-up. SETTING: Switzerland. PARTICIPANTS: Swiss male drinkers (n = 5469, age 20 at baseline) drawn from the Cohort Study on Substance Use Risk Factors (C-SURF). MEASUREMENTS: Self-report questionnaires assessing AIB, AD, alcohol (drinking volume, binge drinking), cigarette and cannabis use, several risk factors (sensation-seeking, family history of problematic alcohol use, age of first alcohol intoxication) and socio-demographic variables. FINDINGS: Generalized estimating equation models with and without adjustment for risk factors, including alcohol use and socio-demographics, showed that AIB at age 20 significantly predicted the incidence of AD at age 25 in men without AD at age 20 [odds ratio (OR) = 2.52, 95% confidence interval (CI), unadjusted = 2.04, 3.11, P < 0.001; fully adjusted, OR = 1.47, 95% CI = 1.13, 1.91, P = 0.004], maintenance of AD in men with AD at age 20 (unadjusted, OR = 1.82, 95% CI = 1.12, 2.95, P = 0.015; fully adjusted, OR = 1.66, 95% CI = 1.00, 2.76, P = 0.048] and AD severity [unadjusted incidence rate ratio (IRR) = 1.89, 95% CI = 1.69, 2.11, P < 0.001; fully adjusted, IRR = 1.20, 95% CI = 1.10, 1.31, P < 0.001]. CONCLUSIONS: Among Swiss men, alcohol-induced blackout at age 20 predicts the development, maintenance and severity of alcohol dependence at age 25.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".