Sexual orientation and self-reported mood disorder diagnosis among Canadian adults
Bibliographic record
Abstract
BACKGROUND: The prevalence and correlates of mood disorders among people who self-identify as lesbian, gay or bisexual (LGB) are not well understood. Therefore, the current analysis was undertaken to estimate the prevalence and correlates of self-reported mood disorders among a nationally representative sample of Canadian adults (ages 18 to 59 years). Stratified analyses by age and sex were also performed. METHODS: Using data from the 2007-2008 Canadian Community Health Survey, logistic regression techniques were used to determine whether sexual orientation was associated with self-reported mood disorders. RESULTS: Among respondents who identified as LGB, 17.1% self-reported having a current mood disorder while 6.9% of heterosexuals reported having a current mood disorder. After adjusting for potential confounders, LGB-respondents remained more likely to report mood disorder as compared to heterosexual respondents (AOR: 2.93; 95% CI: 2.55-3.37). Gay and bisexual males were at elevated odds of reporting mood disorders (3.48; 95% CI: 2.81-4.31), compared to heterosexual males. Young LGB respondents (ages 18-29) had higher odds (3.75; 95% CI: 2.96-4.74), compared to same-age heterosexuals. CONCLUSIONS: These results demonstrate elevated prevalence of mood disorders among LGB survey respondents compared to heterosexual respondents. Interventions and programming are needed to promote the mental health and well being of people who identify as LGB, especially those who belong to particular subgroups (e.g., men who are gay or bisexual; young people who are LGB).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".