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捕捉新护士的经验并支持批判性思维:批判性反思期刊的文本网络分析。

Capturing New Nurses' Experiences and Supporting Critical Thinking: Text Network Analysis of Critical Reflective Journals.

机构信息

Author Affiliations: Chonnam National University Hospital (Mrs Seon, Ju, Lee, and Ms Ahn); and Chonnam National University Hospital, Chonnam National University (Dr Jeong), Gwangju, Republic of Korea.

出版信息

Comput Inform Nurs. 2023 Jun 1;41(6):434-441. doi: 10.1097/CIN.0000000000000971.

DOI:10.1097/CIN.0000000000000971
PMID:36730075
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10241415/
Abstract

This study analyzed the contents of critical reflective journals written by new nurses during their orientations using a text network. This study aimed to find ways to reduce turnover and improve clinical field adaptability among new nurses. The authors analyzed the content of reflective journals written by 143 new nurses from March 2020 to January 2021. Text network analysis was performed using the NetMiner 4.4.3 program. After data preprocessing, frequency of occurrence, degree centrality, closeness centrality, betweenness centrality, and eigenvector community were analyzed. In total, 453 words were extracted and refined, and words with high simple frequency and centrality were "incompetence," "preparation," "explanation," "injection," "time," "examination," and "first try." "Medication" had the highest frequency of occurrence, and "incompetence" was the most important keyword in the centrality analysis. In addition, component analysis and eigenvector community analysis revealed three sub-theme groups: (1) basic nursing skills required for new nurses, (2) insufficient competency, and (3) explanation of nursing work. Significantly, this study is the first to use the text network method to analyze the subjective experiences of the critical reflective journals of new nurses. In conclusion, changes are needed to improve the education system for new nurses and promote efficient sharing of nursing tasks.

摘要

本研究采用文本网络分析方法,对新护士在入职培训期间撰写的批判性反思日志的内容进行了分析。本研究旨在寻找降低新护士离职率、提高其临床适应能力的方法。作者分析了 2020 年 3 月至 2021 年 1 月期间 143 名新护士撰写的反思日志的内容。使用 NetMiner 4.4.3 程序进行文本网络分析。在数据预处理后,分析了频率、度数中心性、接近中心性、中介中心性和特征向量社区。共提取和精炼了 453 个词,高频和中心度高的词有“无能”、“准备”、“解释”、“注射”、“时间”、“检查”和“第一次尝试”。“药物”出现的频率最高,在中心性分析中“无能”是最重要的关键词。此外,成分分析和特征向量社区分析揭示了三个子主题群:(1)新护士所需的基本护理技能,(2)能力不足,(3)护理工作的解释。值得注意的是,本研究首次采用文本网络方法分析新护士批判性反思日志的主观体验。总之,需要对新护士的教育体系进行改革,促进护理任务的高效共享。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7859/10241415/09f5e9e6c709/cin-41-434-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7859/10241415/92e74f94fda2/cin-41-434-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7859/10241415/09f5e9e6c709/cin-41-434-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7859/10241415/92e74f94fda2/cin-41-434-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7859/10241415/09f5e9e6c709/cin-41-434-g002.jpg

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