Interpretation Performance in Chinese and Japanese Medical Consultation Scenarios

Fu Jen Catholic University42 enrolled

Overview

This study aims to compare the translation and interpretation performance of ChatGPT, Google Translate(GT),and UD Talk in cardiopulmonary consultations and analyze their effectiveness in addressing language barriers.The investigators hypothesize that ChatGPT and UD Talk will outperform GT in terms of accuracy and error rates.

Background： Language barriers in healthcare have a significant impact on patient safety, health outcomes, and the quality of healthcare services. With the increase in global migration, more patients are facing language challenges in foreign healthcare systems. Literature shows that providing professional interpretation services significantly improves patient satisfaction and communication quality. However, due to the high usage of ad-hoc interpreters and the shortage of professional interpreters, clinical communication quality has declined. Study Design： This is a one-year, single-center, prospective observational study. Methods： The study will be conducted in the cardiology and pulmonology outpatient clinics at Fu Jen University Hospital. A total of 20 cardiopulmonary disease patients will be enrolled, withtheir consultation sessions recorded and transcribed into Chinese. The study will compare the three tools' performance in terms of semantic accuracy, error types, and severity, and analyze their feasibility in clinical practice. Further analysis will involve satisfaction surveys from both professional interpreters and non-native speakers living in Taiwan. The translation results will be evaluated for accuracy and error rates by 8 professional medical interpreters, with a satisfaction survey completed by a total of 14 non-experts. The evaluation tool will be based on the assessment rubrics from the National Accreditation Authority for Translators and Interpreters. Effect： It is expected that ChatGPT and UD Talk will show better translation accuracy and interpretation quality compared to GT. UD Talk is anticipated to perform better than the other two tools in real-time interpretation. The study results will provide valuable insights for future medical interpretation training and clinical applications.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Outpatients Cardiology Pulmonology

Interventions

translation softwareOTHER

ChatGPT, Google Translate, and UD talk

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

First part Inclusion Criteria: * Age over 18 years * Patients visiting the Cardiology or Pulmonology Department at Fu Jen Catholic University Hospital from December 2024 to November 2025 Exclusion Criteria: * Patients unable to communicate effectively as assessed by the physician * Refusal to participate in the study Second part Inclusion Criteria: * Age over 18 years * Completed the Japanese-Chinese medical interpretation training course and has at least two years of clinical experience Exclusion Criteria: * Refusal to participate in the study Third part Inclusion Criteria: * Age over 18 years * Non-native Chinese-speaking Japanese residents who have lived in Taiwan for at least two years Exclusion Criteria: * Refusal to participate in the study

Locations (1)

Fu Jen Catholic University Hospital, Fu Jen Catholic University

New Taipei City, Taiwan

Outcomes

Primary Outcomes

Translation Assessment Scale Score

6-point Likert scale, with 5 representing the highest score and 0 representing the lowest.

Time frame: 4 months

Data from ClinicalTrials.gov

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