Experiences of trans patients in primary care settings: findings from The OutLook Study
Bibliographic record
Abstract
BACKGROUND: Relationships between primary care providers (PCP) and trans patients remain important, necessitating discussions about gender identity, health and their intersections. METHODS: Using an online survey, we explored socio-demographic and psycho-social factors associated with: (1) disclosing gender identity; (2) discussing gender identity-related health issues; and (3) comfort sharing gender identity with PCPs, among trans people (n =112) over 16years of age, sampled in Waterloo, Ontario, Canada. Bivariate and multivariate methods using modified Poisson regression generated effect estimates. RESULTS: Age, birth presumed gender, employment status, family support, and transphobia were significantly associated with disclosing gender identity, discussing gender identity-related health issues, and comfortability sharing gender identity with PCPs. CONCLUSION: Increasing PCPs' knowledge of trans-related health issues is stressed to improve access and quality for trans patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| 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".