Increases in Alcohol and Cannabis Use Associated with Deteriorating Mental Health among LGBTQ2+ Adults in the Context of COVID-19: A Repeated Cross-Sectional Study in Canada, 2020–2021
Bibliographic record
Abstract
Lesbian, gay, bisexual, trans, other queer, and Two-Spirit (LGBTQ2+) people are particularly at risk for the psycho-social consequences of the COVID-19 pandemic, though population-tailored research within this context remains limited. This study examines the extent of, and associations between, increased alcohol and cannabis use and deteriorating mental health among LGBTQ2+ adults in Canada during the COVID-19 pandemic. Data are drawn from LGBTQ2+ respondents to a repeated, cross-sectional survey administered to adults living in Canada (May 2020-January 2021). Bivariate cross-tabulations and multivariable logistic regression models were utilized to examine associations between increased alcohol and cannabis use, and self-reported mental health, overall coping, and suicidal thoughts. Five-hundred and two LGBTQ2+ participants were included in this analysis. Of these, 24.5% reported increased alcohol use and 18.5% reported increased cannabis use due to the pandemic. In the adjusted analyses, increased alcohol use was associated with poor overall coping (OR = 2.28; 95% CI = 1.28-4.07) and worse self-reported mental health (OR = 1.98; 95% CI = 1.21-3.25), whereas increased cannabis use was associated with suicidal thoughts (OR = 2.30; 95% CI = 1.16-4.55). These findings underscore the need for population-tailored, integrated substance use and mental health supports to address interrelated increases in alcohol/cannabis use and worsening mental health among LGBTQ2+ adults, in the context of the COVID-19 pandemic and beyond.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".