Construction of Health Education Competency Model for Nurses Based on Fuzzy Comprehensive Evaluation Method and Fuzzy Cluster Analysis Method

Honghe Li, Nannan Jin, Limin Zhang and Zaoli Yang

Mathematical Problems in Engineering, 2022, vol. 2022, 1-6

Abstract: Health education competency is essential for nurses to engage in clinical nursing practice. Nurses with a high level of health education competency have a promising future. However, at the present stage, health education of nurses suffers from insufficient effective communication skills, poor skillfulness, and lack of health education knowledge. The above problems seriously affect the improvement of nurses’ health education level and restrict the development of health education in health industry. Therefore, it is very important to construct a health education competency model on how to improve health education. This paper, by taking nurses as the research object, constructed a health education competency model for nurses using the fuzzy comprehensive evaluation method and fuzzy cluster analysis method. In this paper, we first applied the fuzzy cluster analysis method to classify the relevant factors affecting nurses’ health education competency. Then, we investigated 10 experts from four tertiary general hospitals in Heilongjiang Province of China and asked them to rate nurses’ health education competency through the fuzzy comprehensive evaluation method. According to the results of this research, nurses’ knowledge and experience, nurse-patient communication competency, and health education implementation competency are the key factors affecting nurses’ health education competency. But the influence from overall quality is relatively minimal. Among the indicators of knowledge and experience, nurses’ health education knowledge is the most important indicator because it can provide objective basis and expand ideas for the hospital health education management and nursing personnel training.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3241844

DOI: 10.1155/2022/3241844

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