Attitude and Concerns of the Public about " Patient Navigators"：a Text Mining Study Based on Weibo Comments postprint

Abstract: Background　With the intensification of population aging and the increasing demand for out-of-place medical treatment，as well as the pursuit of a high-quality life，"companion services" have attracted considerable attention. Objective　This study aims to explore the public's emotional attitudes and concerns about "companion services" based on Weibo comment data using text mining techniques. Methods　We searched Weibo（up to April 1，2023）using keywords "companion services" "companion assistants" "companion staff" and collected comments. A "wordcloud" was created to analyze the frequency of keywords，the SnowNLP module was used to analyze the sentiment of the comments，and a Dirichlet distribution topic model was applied to identify latent topics in the comments. Results　A total of 2 376 comments were collected，with the public's average sentiment score towards "companion services" being 0.666 6. The topic model identified four latent topics：service recipients， remuneration for services，psychological healing，and future challenges. Conclusion　The public's overall sentiment towards "companion services" exhibits a weakly positive attitude. Therefore，it is recommended to incorporate "companion services" into a new professional category and to transform nursing personnel into professional companions through training and certification measures to ensure the professionalism and standardization of "companion services".