Anxiety symptoms and alcohol abuse during the COVID‐19 pandemic: A cross‐sectional study with Brazilian dental undergraduate students
Bibliographic record
Abstract
AIM: The aim of this study is to assess whether anxiety symptoms are associated with alcohol abuse in Brazilian undergraduate dental students during the COVID-19 pandemic. METHOD: A cross-sectional study was conducted. A semi-structured questionnaire addressing the variables of interest was hosted on Google Forms and shared with dental undergraduate students from all Brazilian regions between July 8 and 27, 2020. Alcohol abuse was measured using the Cut down, Annoyed, Guilty, Eye opener (CAGE) questionnaire score of ≥2. All participants responded to the seven-item Generalized Anxiety Disorder Scale (GAD-7). Hierarchical logistic regression was also conducted. RESULTS: Among the 1050 students evaluated, 18.7% (n = 196) had a positive screening for alcohol abuse during the pandemic. The prevalence of mild (GAD-7 = 5-9), moderate (GAD-7 = 10-14), and severe (GAD-7 ≥15) anxiety among students were 31.3%, 29.6%, and 24.2%, respectively. The final hierarchical logistic regression model showed that during the COVID-19 pandemic, anxiety levels predict the likelihood of alcohol abuse among students with moderate (OR 10.05 [95% IC: 4.12-24.52]) or severe (OR 15.82 [95% IC: 6.46-38.73]) anxiety, especially for male students (moderate anxiety: OR 17.06 [95% CI: 8.36-34.78]; severe anxiety: OR 28.38 [95% CI: 8.62-38.24]). CONCLUSION: The prevalence of alcohol abuse and moderate or severe anxiety in Brazilian undergraduate dental students during the COVID-19 pandemic was high. Male students may be more sensitive to the presence of anxiety symptoms in this period, thus contributing to higher levels of alcohol consumption, in comparison to female students. Intervention strategies that promote the adoption of healthier lifestyles can enable the effective management of anxiety symptoms during the pandemic and thus, hold the potential to reduce exacerbated alcohol intake in this population.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".