Attitudes of the public and medical professionals toward nurse prescribing: A text-mining study based on social medias

Abstract

Objectives: This study aimed to explore the public and medical professionals’ concerns and attitudes toward nurse prescribing using text-mining method to analyze social media data. Methods: Python was used to automatically mine data related to the keywords “nurse prescribing” and “prescription” that were posted on four Chinese internet platforms between January 1, 2017, and November 1, 2022. The four Chinese internet platforms included social media sites such as Zhihu and Weibo, as well as medical forums like Aiaiyi Medical Hotspot and Dingxiangyuan Medicine. We conducted personnel, topic, and sentiment analysis techniques using SnowNLP, Bayesian Latent Dirichlet Allocation (LDA), and BosonNLP. Finally, we conducted content analysis using Nvivo 11 based on the results of the topic and sentiment analysis to obtain comprehensive and insightful results. Results: We acquired 2,823 comments totaling 92,859 words on the four Internet platforms to conduct analysis. The analyze result showed that many public and medical professionals held a negative attitude toward nurse prescribing, and few had a prudent positive attitude. The public is concerned about the impact of nurse prescribing on medical professionals and the competency requirements for nurses. Medical professionals are concerned about the current and future status of nurse prescribing in China and the difficulties in implementing nurse prescribing. Conclusion: Nurses should gradually gain recognition for their expertise and win the acceptance of the public and medical professionals on their ability of nursing prescribing by striving to enhance their professional capacity and self-authorization capabilities. Nurse administrators and educators need to recognize the advantages of nurse prescribing and address the challenges and issues in its implementation through promoting legislation, education, and heightening public awareness of its benefits.

Keywords

• Natural language processing
• Non-medical prescribing
• Nurses
• Professional autonomy
• Sentiment analysis
• Social media