Untangling global mental health disparities in the Canadian population: Exploring the intersection of sexual orientation, stress, and social support
Bibliographic record
Abstract
This study examined, in a nationally representative sample, if the global mental health disparities associated with self-identified and behavioural sexual orientation (SO) are mediated by stress and social support. Mediation analyses were performed separately for men and women in a population sample ( n = 80,985) from two waves of Statistics Canada’s Canadian Community Health Survey (2015/2016 and 2019/2020). Two-step hierarchical linear regressions were used to assess the effect of adding the mediators to the model on the coefficient of the SO variables. Then, a formal test of the mediation of the relation between SO and global mental health via perceived daily stress, perceived social support, and their interaction was conducted based on Preacher and Hayes’s methodology. Stress, social support, and their interaction partially mediated the relationship between SO and global mental health. However, only two of the five minority SO categories were statistically mediated. Specifically, for self-identified bisexual respondents and those who did not have sex in the last 12 months, higher levels of stress, and lower levels of social support partially explained their lower global mental health. The interaction between mediators proved relevant only for respondents who did not have sex in the last 12 months, revealing a lesser mediating role for this variable in the relationship between SO and global mental health. Thus, the fact that sexual minority populations have lower levels of global mental health was partially explained by perceived daily stress and social support, particularly for those who identify as bisexual.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".