LGBTQ2S+ Youth Perspectives on Mental Healthcare Provider Bias, Standards of Care, and Accountability
Bibliographic record
Abstract
This study explores the experiences of LGBTQ2S+ youth while accessing mental health and substance use care services during the COVID-19 pandemic. Through a series of facilitated virtual meetings, 33 LGBTQ2S+ youth from across Ontario participated in collaborative activities to identify barriers they have experienced when accessing mental health services, as well as potential solutions to these barriers. Discussions were recorded, transcribed, and analyzed using thematic analysis. The study revealed that LGBTQ2S+ youth disproportionately experience bias, discrimination, and heteronormative assumptions when accessing mental health services, resulting in negative care experiences. Youth also reported insufficient availability of quality care, little continuity in care, and a lack of educated providers capable of effectively addressing the needs of the community. Potential solutions proposed by youth include training resources for providers, LGBTQ2S+ specific care centers, better continuity of care, and assessments to ensure care providers are culturally competent. These results show the COVID-19 pandemic has exacerbated the disparities LGBTQ2S+ youth experience when accessing mental health services and highlight the urgent need to implement policies and programs that will advance the standards of care for LGBTQ2S+ youth.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".