Sexual orientation as a social determinant of suicidal ideation: A study of the adult life span
Bibliographic record
Abstract
OBJECTIVE: Rates of suicide attempts are highest among younger ages and women, and especially elevated among sexual minorities (lesbian, gay, and bisexual [LGB] people). We examined the prevalence of lifetime suicide ideation among sexual minorities and sought to determine whether this relationship depended on age and gender. METHOD: Using data from the Annual Component of the 2015-2016 Canadian Community Health Survey (CCHS), participants were asked whether they had seriously contemplated suicide (lifetime suicidal ideation: yes/no). In adjusted multiple logistic regression analyses, we entered a sexual orientation by gender and age (three-way) interaction. RESULTS: : p = 0.009); the strength of the relationship between sexual orientation and suicidal ideation varied by gender and age. Lesbian/gay and bisexual respondents of both genders were more likely to report suicidal ideation across the life span, when compared to heterosexuals. This finding was strongest for bisexual respondents. CONCLUSION: The results highlight the relevance of sexual orientation as a social determinant of lifetime suicidal ideation. Suicide prevention and surveillance efforts should take into consideration that sexual minorities, especially bisexual persons, disproportionately consider harming themselves when compared to the heterosexual 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 | 0.000 | 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 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".