Depression and Suicide Literacy among Canadian Sexual and Gender Minorities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study was to examine and compare depression and suicide literacy among Canadian sexual and gender minorities (SGM). Online surveys comprised of the 22-item depression literacy scale (D-LIT) and the 12-item literacy of suicide scale (LOSS) were completed by 2,778 individuals identifying as SGM. Relationships between depression and suicide literacy and demographic characteristics were evaluated using multivariable linear regression. Overall, SGM correctly answered 71.3% of the questions from the D-LIT and 76.5% of the LOSS. D-LIT scores were significantly lower among cisgender men and D-LIT and LOSS scores were lower among transgender women when compared to cisgender women. LOSS and D-LIT scores were significantly lower among SGM without a university degree (compared to those with a university degree) and among SGM from ethnic minority groups (compared to White SGM). D-LIT scores, but not LOSS scores, were significantly lower among Indigenous SGM compared to White SGM. The findings provide evidence of differences in suicide and depression literacy between SGM subgroups along multiple social axes. Interventions to increase depression and suicide literacy should be prioritized as part of a mental health promotion strategy for SGM, targeting subgroups with lower literacy levels, including cisgender men, transgender women, Indigenous people, racialized minorities, and those without a university degree.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it