Reported Emergency Department Avoidance, Use, and Experiences of Transgender Persons in Ontario, Canada: Results From a Respondent-Driven Sampling Survey
Bibliographic record
Abstract
STUDY OBJECTIVE: Transgender, transsexual, or transitioned (trans) people have reported avoiding medical care because of negative experiences or fear of such experiences. The extent of trans-specific negative emergency department (ED) experiences, and of ED avoidance, has not been documented. METHODS: The Trans PULSE Project conducted a survey of trans people in Ontario, Canada (n=433) in 2009 to 2010, using respondent-driven sampling, a tracked network-based method for studying hidden populations. Weighted frequencies and bootstrapped 95% confidence intervals (CIs) were estimated for the trans population in Ontario and for the subgroup (n=167) reporting ED use in their felt gender. RESULTS: Four hundred eight participants completed the ED experience items. Trans people were young (34% aged 16 to 24 years and only 10% >55 years); approximately half were female-to-male and half male-to-female. Medically supervised hormones were used by 37% (95% CI 30% to 46%), and 27% (95% CI 20% to 35%) had at least 1 transition-related surgery. Past-year ED need was reported by 33% (95% CI 26% to 40%) of trans Ontarians, though only 71% (95% CI 40% to 91%) of those with self-reported need indicated that they were able to obtain care. An estimated 21% (95% CI 14% to 25%) reported ever avoiding ED care because of a perception that their trans status would negatively affect such an encounter. Trans-specific negative ED experiences were reported by 52% (95% CI 34% to 72%) of users presenting in their felt gender. CONCLUSION: This first exploratory analysis of ED avoidance, utilization, and experiences by trans persons documented ED avoidance and possible unmet need for emergency care among trans Ontarians. Additional research, including validation of measures, is needed.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".