Medical students' self-reported preparedness and attitudes in providing care to ethnic minorities.
Bibliographic record
Abstract
BACKGROUND: To assess medical students' self-reported preparedness to provide care to ethnic minorities, factors that influence preparedness, and attitudes toward cultural competency training. METHODS: A cross-sectional study, which invited University of British Columbia medical students to participate in a survey on student demographics, knowledge and awareness, preparedness and willingness, and personal attitudes. Of 1024, eligible, 301 students consented to study. RESULTS: Students across all year levels felt significantly less ready to provide care for non-English speaking Chinese patients compared to "any" patients. Proficiency in working with interpreters was correlated with readiness, OR 4.447 (1.606-12.315) along with 3rd and 4th year level in medical school, OR 3.550 (1.378-9.141) and 4.424 (1.577-12.415), respectively. Over 80% of respondents reported interest in learning more about the barriers and possible ways of overcoming them. CONCLUSIONS: More opportunities for cultural competency training in the medical curriculum are warranted and would be welcomed by the students.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".