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Framework for virtual education of COVID-19 vaccines for Mandarin-speaking learners: An educational intervention module

Cite this dataset

Wang, JiCi et al. (2023). Framework for virtual education of COVID-19 vaccines for Mandarin-speaking learners: An educational intervention module [Dataset]. Dryad.


Background: In the United States, patients with limited English proficiency face significant barriers to comprehending and acting upon health-related information, particularly during the COVID-19 pandemic. The ability of health professionals to communicate COVID-19-related information to Mandarin-speaking patients has proved critical in discussions about vaccine efficacy, side effects, and post-vaccine protection.

Methods: The authors created a one-hour educational module to help Mandarin-speaking medical students better convey COVID-19 vaccine information to Mandarin-only speakers. The module is composed of an educational guide, which introduced key terminology and addressed commonly asked questions, and pre- and post-surveys. The authors recruited 59 Mandarin-speaking medical students from 31 U.S. academic medical centers, all of whom had previously completed a medical Mandarin elective. The module and surveys were distributed and completed in August 2021. Data analysis measured the change in aggregate mean for subjective five-point Likert-scale questions and change in percent accuracy for objective knowledge-based questions.

Results: The educational module significantly improved participants' subjective comfort level in discussing the COVID-19 vaccine in English and Mandarin. The largest improvement in both English and Mandarin was demonstrated in the participant's ability to explain differences between the COVID-19 vaccines, with an aggregate mean improvement of 0.39 for English and 1.48 for Mandarin. Survey respondents also demonstrated increased percent accuracy in knowledge-based objective questions in Mandarin.

Conclusions: This module provides Mandarin-learning medical students with skills to deliver reliable information to the general population and acts as a model for the continued development of educational modules for multilingual medical professionals.


The data was collected through surveys made on Qualtrics and distributed through email listservs. The data was downloaded on Microsoft Excel and analyzed through R Studio and GraphPad Prism.  


University of Michigan–Ann Arbor, Award: M1 Summer Accelerator Impact Grant