Unplanned Sexual Activity as a Consequence of Alcohol Use: A Prospective Study of Risk Perceptions and Alcohol Use Among College Freshmen
Bibliographic record
Abstract
OBJECTIVE: The authors' goal was to show how risk perceptions regarding unplanned sexual activity following alcohol use are prospectively related to subsequent alcohol consumption. PARTICIPANTS: Undergraduate students (N = 380) completed questionnaires at 2 time points during their freshman year. METHODS: In the middle of the academic year (T1), students estimated their risk of engaging in unplanned sex and reported their alcohol use during the previous term. Four months later (T2), they again reported alcohol use and indicated whether they had engaged in unplanned sex since T1. RESULTS: Students who consumed more alcohol at T1 rated their risk of unplanned sex more highly, suggesting relative accuracy. Those with higher risk perceptions consumed more alcohol at T2 (controlling for T1 use), suggesting that they maintained the high-risk behavior. Last, those who were unrealistically optimistic (ie, estimated low risk at T1 yet had unplanned sex by T2) reported greater alcohol use at T2. CONCLUSIONS: These findings highlight the role that risk perceptions regarding sexual activity may play in college students' alcohol use.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".