Young adult drinking during the COVID-19 pandemic: Examining the role of anxiety sensitivity, perceived stress, and drinking motives
Bibliographic record
Abstract
Studies have shown that those high in anxiety were at increased risk for alcohol use during the COVID-19 pandemic. Tension reduction theory points to anxiety sensitivity (AS) as a potential risk factor. Drinking to cope may further increase this risk. During the pandemic, those high in AS may have experienced increased stress and drank to cope, which may have put them at risk for misusing alcohol. Objective: The current study tested the association between AS and alcohol outcomes, mediated by perceived stress and drinking motives, among young adults during the COVID-19 pandemic. Participants and Methods: Young adults (N = 143) self-reported on AS, perceived stress, drinking motives, and alcohol outcomes (i.e., use and problems). Results: A mediation analysis revealed that AS positively predicted alcohol problems, via coping motives, and positively predicted alcohol use, via perceived stress and enhancement/sociability motives. Conclusion: These results confirm AS-risk for young adult alcohol use during the pandemic and highlight perceived stress and drinking motives as mechanisms of risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".