A Text Mining-Based Survey of Pre-Impressions of Medical Staff toward COVID-19 Vaccination in a Designated Medical Institution for Class II Infectious Diseases

Vaccines (Basel). 2021 Nov 5;9(11):1282. doi: 10.3390/vaccines9111282.

Abstract

The present study investigated the pre-impressions of medical staff toward coronavirus disease 2019 (COVID-19) vaccination in a designated medical institution for class II infectious diseases in Sakaide, Japan using a text mining analysis. A total of 387 medical staff were surveyed on their pre-vaccination impressions toward the COVID-19 vaccine using an open-ended questionnaire from March 1st to 7th (the first survey) and from March 22nd to 28th (the second survey) at Sakaide City Hospital, Sakaide, Japan. A total of 296 people answered the question for the first time and 234 people answered for the second time among the 387 people. The vaccination rate was slightly lower for the younger generation than for the older generation. Before the first vaccination, the younger generation expressed concerns about side effects as well as a negative impact on pregnancy. However, before the second vaccination, there were fewer concerns regarding side effects and words of reassurance were also noted. Nurses expressed more opinions about side effects in both the first and second vaccinations than other medical staff. Concerns regarding side effects among medical staff decreased with the progression of COVID-19 vaccination. These data may provide useful information about the promotion of COVID-19 vaccination to the public, particularly in the young generation and women.

Keywords: COVID-19; impression; text mining; vaccination.