Understanding early experiences of Chinese frontline nurses during the COVID‐19 pandemic: A text mining and thematic analysis of social media information

Abstract

AbstractThis study aims to explore the early experiences of frontline nurses at the beginning of the COVID‐19 pandemic in China as expressed through social media posts. This study used an explanatory sequential mixed‐method design. Text mining was used for sentiment analysis. The chi‐square test was used to compare the differences in the composition ratio of sentiment classification of posts in different months. Word frequency was statistically analyzed. Further thematic analysis was also performed. The primary sentiments of the posts were discovered to be positive and neutral. The number of posts containing positive emotions was the lowest in January, peaked in March, and gradually declined in April 2020. The following nurse‐oriented narrative themes were developed: “To see and be seen,” “Moving forward amid adversity and support,” and “Returning to everyday life and constructing meaning.” The sentiments of Chinese nurses in response to the pandemic fluctuated, with positive emotions in the early stage, but it could not be sustained. This study recommends nurses could be encouraged to engage in expressive writing while adhering to ethical guidelines.