In its very early phases, COVID-19 shifts the associations between alcohol consumption and psychological symptoms in young adults
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has impacted various aspects of daily life, leading to increased psychological symptoms and changes in alcohol use, yet little is known about their specific interactions, particularly early stages during the pandemic. We examined the relationship between psychological symptoms and alcohol-related behaviors associated with COVID-19, and determined whether associations shifted already early during the pandemic and whether changes in psychological symptoms from the pre- to during COVID-19 impacted changes in alcohol consumption. METHODS: Participants were young adults from a longitudinal cohort (N=435, age: 22-25) from two time points. We applied paired samples t-tests, correlation analyses, SHapley Additive exPlanations, and classification models to examine the multiple associations between psychological symptoms and alcohol use directly pre- and early during COVID-19. RESULTS: We found significant associations between psychological symptoms and alcohol use pre- compared to during COVID-19. Anxiety was the strongest factor influencing alcohol use pre-pandemic, depression had the greatest impact during COVID-19. Changes in anxiety from pre- to during COVID-19 were the main factor associated with an increase in alcohol use, while changes in depression appeared to be most predictive for a decrease/persistence in alcohol use. CONCLUSION: These findings suggest a shift in the association between psychological symptoms and alcohol use following COVID-19, as well as a differential impact of psychological symptoms, depending on their changes related to the pandemic. Changes in anxiety may contribute to riskier alcohol use behaviors following the pandemic, while depression appears to be one of the most critical factors influencing alcohol use during such crisis situations.
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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 | 0.001 |
| 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".