Automated translation accurately translates recorded pediatric neurosurgery clinic conversations between Spanish and English.

OBJECTIVE: The purpose of this study is to analyze an automated voice to text translation device by reporting the translation accuracy for recorded pediatric neurosurgery clinic conversations, classifying errors in translation according to their impact on overall understanding, and comparing the incidence of these errors in English to Spanish vs. Spanish to English conversations. METHODS: English and Spanish speaking patients at a single academic health system's outpatient pediatric neurosurgery clinic had their conversations recorded. These recordings were played back to a Google Pixel handheld smartphone with Live Translate voice to text translation software. A certified medical interpreter evaluated recordings for incidence of minor errors, errors impacting understanding, and catastrophic errors affecting patient-provider relationship or care. Two proportion t-testing was used to compare these outcomes. RESULTS: 50 patient visits were recorded: 40 English recordings translated to Spanish and 10 Spanish recordings translated to English. The mean transcript length was 4244 ± 992 words. The overall accuracy was 98.2% ± 0.5%. On average, 46 words were missed in translation (1.09% error rate), 31 understanding-altering translation errors (0.73% error rate), and 0 catastrophic errors were made. There was no significant difference in English to Spanish or vice versa. CONCLUSION: Voice to text translation devices using automatic speech recognition accurately translate recorded clinic conversations between Spanish and English with high accuracy and low incidence of errors impacting medical care or understanding. Further study should investigate additional languages, assess patient preferences and potential concerns with respect to device use, and compare these devices directly to medical interpreters in live clinic settings.

Creation and evaluation of a self-directed, first-year intervention for pre-health undergraduates: setting students up for success.

University-established modalities to help undergraduate students navigate the path to medical school are often implemented toward the end of college or following graduation. This imposes cost and time burdens that may be contribute to the high rate of premedical attrition, especially for students who are members of a marginalized community. In the fall 2022 semester, an asynchronous, self-directed pre-health module was offered to biology majors at the University of North Carolina at Chapel Hill enrolled in a required introductory biology research skills course. The objective of the five-lesson intervention was to enhance student understanding of the path to becoming a successful applicant early in their college career. The module aimed to increase the accessibility of pre-health advising and was designed to be easily shared and adapted across various learning management systems. A pre- and post-module survey was administered to assess changes in students' perceived understanding of and confidence for success on the pre-health track following completion of the course.