Relationship between sociodemographics, loss of income, and mental health among two-spirit, gay, bisexual, and queer men in Manitoba during the COVID-19 pandemic
Bibliographic record
Abstract
This study examined the relationship between loss of income due to the COVID-19 pandemic and worsening mental health among a sample of 366 Two-Spirit, gay, bisexual, queer (2SGBQ+) men in Manitoba. Data were drawn from a cross-sectional online survey among 2SGBQ+ men in Manitoba. Logistic regression assessed the relationship between sociodemographics, loss of income due to COVID-19 (independent variable) and worsening of mental health (analytic outcome). Among all respondents in the sample (N = 366), 55% indicated worsening of their mental health. In logistic regression, compared to participants who did not experience any loss of income, those who experienced loss of income due to the COVID-19 pandemic were significantly more likely to report worsening mental health (Adjusted Odds Ratio [AOR] = 8.32, 95% Confidence Interval[CI] = 3.54-19.54). Compared to participants who self-identified as gay, bisexual-identifying participants were less likely to report worsening mental health (AOR = .35, 95%CI = 0.13-0.96). Finally, as compared to participants who were married or partnered, participants who were dating (AOR = 3.14, 95%CI = 1.60-6.17), single (AOR = 4.08, 95%CI = 1.75-9.52), and separated/divorced/widowed (AOR = 15.08, 95%CI = 2.22-102.51) were all significantly more likely to report experiencing a worsening of mental health due to the COVID-19 pandemic. This study highlights the need to develop robust public strategies for sub-populations of 2SGBQ+ men (non-gay identified sexual minorities and 2SGBQ+ men who may be more socially isolated). Specific targeted and tailored public health interventions designed with the unique needs of 2SGBQ+ men in Manitoba may be required to increase their access to socio-economic and mental health supports.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".