The design and pilot of a translation aid to help ED clinicians enhance communication with the Portuguese-speaking patient
Bibliographic record
Abstract
BACKGROUND: Language barriers hinder health care delivery in settings with culturally diverse populations. Interventions to accommodate non-English-speaking patients have been shown to shorten length of stay and reduce non-urgent visits. AIMS: Our aim was to design and do a pilot study on an instrument to facilitate history taking with Portuguese-speaking patients in the emergency department (ED). METHODS: An instrument was designed to facilitate history taking with Portuguese-speaking patients (PSPs). A pocket-sized document incorporated, bilingual, problem-oriented, closed-ended questions for common ED presentations as well as numbers, measurements of time, and anatomy. A paired audio tutorial on a compact disk (CD) demonstrated correct pronunciation of each phrase. A 3-month pilot was undertaken in a downtown teaching hospital on a convenience sample of PSPs who indicated the need for a translator at triage. A trained Portuguese-speaking observer monitored clinician/patient pairs using the instrument and scored differential patient comprehension in a standardized manner. Qualitative patient and clinician impressions were assessed. A follow-up survey assessed emergency physician (EP) impressions of the instrument. RESULTS: Eight of nine eligible clinician/patient pairs were enrolled. The average proportions of questions answered appropriately in English and then using the instrument were 16.7% and 85.5%, respectively, with mean improvement of 68.8% (confidence interval: 45.6-92.1). Most (7/8) patients agreed that the instrument had helped in communication. Half (4/8) of the clinicians indicated that the tool had helped them communicate, and most (7/8) indicated that they would use the instrument in the future. Few (2/17) physicians utilized the audio guide. Suggested modifications included incorporation of phonetics. CONCLUSIONS: The pilot of the instrument was well received by patients and resulted in improved communication.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".