Emergency department care experiences among members of equity-deserving groups: quantitative results from a cross-sectional mixed methods study
Bibliographic record
Abstract
BACKGROUND: Emergency departments (EDs) serve an integral role in healthcare, particularly for vulnerable populations. However, marginalized groups often report negative ED experiences, including stigmatizing attitudes and behaviours. We engaged with historically marginalized patients to better understand their ED care experiences. METHOD: Participants were invited to complete an anonymous mixed-methods survey about a previous ED experience. We analysed quantitative data including controls and equity-deserving groups (EDGs) - those who self-identified as: (a) Indigenous; (b) having a disability; (c) experiencing mental health issues; (d) a person who uses substances; (e) a sexual and gender minority; (f) a visible minority; (g) experiencing violence; and/or (h) facing homelessness - to identify differences in their perspectives. Differences between EDGs and controls were calculated with chi squared tests, geometric means with confidence ellipses, and the Kruskal-Wallis H test. RESULTS: We collected a total of 2114 surveys from 1973 unique participants, 949 controls and 994 who identified as equity-deserving. Members of EDGs were more likely to attribute negative feelings to their ED experience (p < 0.001), to indicate that their identity impacted the care received (p < 0.001), and that they felt disrespected and/or judged while in the ED (p < 0.001). Members of EDGs were also more likely to indicate that they had little control over healthcare decisions (p < 0.001) and that it was more important to be treated with kindness/respect than to receive the best possible care (p < 0.001). CONCLUSION: Members of EDGs were more likely to report negative ED care experiences. Equity-deserving individuals felt judged and disrespected by ED staff and felt disempowered to make decisions about their care. Next steps will include contextualizing findings using participants' qualitative data and identifying how to improve ED care experiences among EDGs to make it more inclusive and better able to meet their healthcare needs.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".