Assessing the Job Satisfaction of Registered Nurses Using Sentiment Analysis and Clustering Analysis

Matthew Jura, Joanne Spetz, Der Ming Liou

研究成果: 雜誌貢獻文章同行評審

摘要

Job satisfaction is a critical component of the professional work environment and is often ascertained through surveys that include structured or open-ended questions. Using data from 24,543 respondents to California Board of Registered Nursing biennial surveys, this study examines the job satisfaction of registered nurses (RNs) by applying clustering analysis to structured job satisfaction items and sentiment analysis to free-text comments. The clustering analysis identified three job satisfaction groups (low, medium, and high satisfaction). Sentiment analysis scores were significantly associated with the job satisfaction groups in both bivariate and multivariate analyses. Differences between the job satisfaction clusters were mostly driven by satisfaction with workload, adequacy of the clerical support services, adequacy of the number of RN staff, and skills of RN colleagues. In addition, there was dispersion in satisfaction related to involvement in management and policy decisions, recognition for a job well done, and opportunities for professional development.
原文英語
期刊Medical Care Research and Review
DOIs
出版狀態接受/付印 - 2021

ASJC Scopus subject areas

  • 健康政策

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