Autor: |
Centeno-Saenz, Gustavo I., Alvarado-Amador, Irlanda, Flores-Valadez, Mario A., Benítez-Pérez, Rosaura E., Meneses-Tamayo, Erika, González-Castellanos, Mabelle, Gochicoa-Rangel, Laura |
Předmět: |
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Zdroj: |
ATS Scholar; Sep2024, Vol. 5 Issue 3, p433-441, 9p |
Abstrakt: |
Background: Knowledge of respiratory physiology is essential for the diagnosis and treatment of respiratory diseases. During the coronavirus disease (COVID-19) pandemic, face-to-face education was inadequate, leading to the implementation of virtual programs for pulmonary fellows from Latin America. Objective: This study describes our experience with the implementation of a virtual education program involving pulmonary function tests (PFTs) for pulmonary fellows in Latin America. Methods: A learning program on PFTs was designed by the Department of Respiratory Physiology at the National Institute of Respiratory Diseases in Mexico City, and fellows in pulmonology were invited to participate in the program by their academic professors. The program was performed virtually on an online platform over 3 months. The topics covered included respiratory mechanics, gas exchange, and cardiopulmonary exercise tests. Students were asked to complete an evaluation before and after each lecture as well as before and after the entire course. Results: A total of 205 fellows from 12 countries participated in the course, and fewer than 50% completed assessments before and after the course. The results showed that fellows had relatively high initial knowledge of oxygen desaturation and cardiopulmonary exercise tests, whereas relative deficiencies were found in maximal respiratory pressure and bronchial challenge tests. The highest grade was in the spirometry test, whereas the lowest was in the bronchial challenge test. Overall, the fellows demonstrated improved performance in the post-course evaluations. Conclusion: Virtual education in PFTs is feasible and can have a positive impact on the training of pulmonary fellows from Latin America. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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