Login / Signup

Fighting COVID-19 Contagion among University Students of Healthcare Professions: An Italian Cross-Sectional Study.

Marco TofaniAnna BerardiMaurizio MarcecaDonatella ValenteAlfonso MazzaccaraAntonella PolimeniGiovanni Fabbrini
Published in: International journal of environmental research and public health (2021)
During the pandemic, most governments around the world temporarily closed educational institutions to contain the spread of the Coronavirus Disease 2019 (COVID-19). The objective of the present study is to evaluate the efficacy of an e-learning course on COVID-19 transmission for healthcare university students, in order to advance the preparedness of healthcare university students against contracting COVID-19 within the general university population. The e-learning course was run using a free web service for education. Access to the course was limited to participants enrolled in degree courses related to healthcare professions within the Italian university system. A specific and validated questionnaire was administered at two different times (pre-test and post-test). A paired sample t-test was then used to evaluate their knowledge on COVID-19. Furthermore, a questionnaire measuring their satisfaction was distributed. Data were analyzed from a qualitative point of view. The course was made available from March to July 2020. Over 25,000 students from different Italian universities and various backgrounds participated in the course. The analysis of final test scores revealed that approximately 97% of participants acquired new knowledge and skills on COVID-19, with a statistically significant improvement (p < 0.05). Therefore, it is possible to state that most students enrolled in degrees relating to healthcare at Italian universities are adequately trained with respect to COVID-19 knowledge. Furthermore, students declared a high satisfaction rate both with the course content, and with the management of the telematic platform used.
Keyphrases
  • coronavirus disease
  • healthcare
  • sars cov
  • respiratory syndrome coronavirus
  • machine learning
  • high throughput
  • mental health
  • artificial intelligence