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1. 西南医科大学附属医院内分泌科,泸州,646000
2. 西南医科大学护理学院,泸州,646000
纸质出版日期:2022,
网络出版日期:2022-3-20,
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朱世琴, 邓波, 罗欢, 等. 护理预测研究文献热点与发展趋势[J]. 西南医科大学学报, 2022,45(2):151-156.
ZHU Shiqin, DENG Bo, LUO Huan, et al. Hot spots and development trend of nursing prediction research literature[J]. Journal of Southwest Medical University, 2022,45(2):151-156.
朱世琴, 邓波, 罗欢, 等. 护理预测研究文献热点与发展趋势[J]. 西南医科大学学报, 2022,45(2):151-156. DOI: 10.3969/j.issn.2096-3351.2022.02.013.
ZHU Shiqin, DENG Bo, LUO Huan, et al. Hot spots and development trend of nursing prediction research literature[J]. Journal of Southwest Medical University, 2022,45(2):151-156. DOI: 10.3969/j.issn.2096-3351.2022.02.013.
目的通过文献计量分析护理领域预测研究文献,探索护理预测研究的现状、趋势和潜在热点,以提升护理相关研究的创新性与深度。方法以中国知网(CNKI)为本次数据来源,检索建库至2020 年的文献,使用Citespace5.7R2 与VOSviewer 对最终纳入文献进行计量可视化分析。结果经去重、整理后最终纳入文献676 篇,发文量呈逐年上升趋势,发文最多的作者为吴疆,发文8 篇,占比1.16%;发文最多的机构为协和医学院,发文20篇,占比1.96%;刊文最多的期刊为“护士进修杂志”,刊文30篇,占比4.43%;压力性损伤、风险/影响因素、护理干预、老年人、产后出血、卫生人力资源、长期护理需求/保险是高频关键词;护理预测研究主题由卫生人力资源管理、压力性损伤、精神病患者行为和护士工作量等向护理绩效、妊娠期高血压、失能老人、脑卒中、谵妄患者、心血管疾病和产后出血等转变;预测模型由Logistic 回归、决策树与灰色预测模型向结构方程模型、人工神经网络、机器学习与大数据等复杂网络模型构建转变。结论国内护理预测研究整体发文较低,但近3 年处于快速发展期,国内护理研究者应抓住发展机遇,拓展该领域研究的丰度,提升护理研究的创新性与深度。
Objective To use bibliometric analysis to analyze the current status,trends,and potential hot spots of nursing predic-tion research,and to provide a reference for further research. Methods We retrieved relevant literature from Chinese National Knowl-edge Infrastructure from database establishment to 2020,and used CiteSpace 5.7.R2 and VOSviewer to perform a quantitative and visu-al analysis of the included literature. Results After de-duplication and sorting,676 articles were finally included. The number of the ar-ticles was increasing year by year. The author with the largest number of articles was Wu Xinjiang,with 8 articles accounting for 1.16%. The institution with the largest number of articles was Peking Union Medical College,with 20 articles accounting for 1.96%. The journal with the largest number of articles was Journal of Nurses Training,with 30 articles accounting for 4.43%. The high-frequency keywords included stress injury,risk/influencing factor,nursing intervention,elderly,postpartum hemorrhage,health human resources,long-term care need/insurance. The topics of nursing prediction research changed from health human resource management,stress injury,psycho-path’s behavior,and nurse’s workload to nursing performance,gestational hypertension,disabled elderly,stroke,delirium,cardiovascu-lar disease,and postpartum hemorrhage. The prediction model transformed from logistic regression,decision tree,and grey prediction model to structural equation model,artificial neural network,machine learning,big data analysis,and other complex network models. Conclusion Domestic literature on nursing prediction is relatively small in quantity,but it has been in a period of rapid development in the past three years. Domestic nursing researchers should seize the development opportunities to increase research abundance and inno-vation in this field.
护理预测模型热点CiteSpaceVOSviewer
NursingPrediction modelHot spotsCiteSpaceVOSviewer
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