公众对"陪诊服务"的态度和关注点:基于微博评论的文本挖掘OA

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,"patient navigators"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".