Clarifying the Anxiety Sensitivity and Alcohol Use Relation: Considering Alcohol Expectancies as Moderators
Bibliographic record
Abstract
OBJECTIVE: Empirical examinations of the relation between anxiety sensitivity (AS) and alcohol use have yielded inconsistent results, with some studies finding a positive association and other studies finding no association. The present study sought to clarify this relation by examining the moderational effects of alcohol expectancies (i.e., tension reduction, cognitive and behavioral impairment) on the AS-alcohol use association. Gender-specific pathways were also examined. METHOD: Participants (N=158, 82 women) were alcohol nonabstaining college freshmen who completed a questionnaire battery including assessments of alcohol expectancies (four positive subscales: sociability, tension reduction, liquid courage, and sexuality; three negative subscales: cognitive and behavioral impairment, risk and aggression, and self-perception), AS, and alcohol use (past month). RESULTS: Regression analysis was used to test three-way AS x Gender x Alcohol Expectancy interaction terms predicting alcohol use. Only the tension reduction and cognitive and behavioral impairment subscales entered into significant (p< .05) and marginally significant (p= .05) interaction terms, respectively. The simple slopes suggested that, for men only, high AS was associated with heavy drinking but only when tension reduction expectancies were high and that high AS was associated with low levels of drinking when cognitive and behavioral impairment expectancies were high, but this was true only for women. CONCLUSIONS: These findings provide an explanation for why AS has been inconsistently linked to alcohol use in prior research and suggest that models of alcohol use incorporating AS should consider the role of moderators.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".