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期刊名:International nursing review

缩写:INT NURS REV

ISSN:0020-8132

e-ISSN:1466-7657

IF/分区:3.7/Q1

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共收录本刊相关文章索引1523
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Ayla Güllü,Keriman Aytekin Kanadli Ayla Güllü
Aim: The aim of this study is to determine the attitudes of intensive care nurses towards health technologies and their attitudes' correlation with their professional self-efficacy. ...
Xiao-Chen Lyu,Cheng Chen,Thitinut Akkadechanunt et al. Xiao-Chen Lyu et al.
Background: Nurses spend their careers focused on caring for others. However, they may face the challenges of a serious illness and return to their professional roles, and their unique insights and experiences have not be...
Chieko Fujii,Yumi Iwasa Chieko Fujii
Aim: This integrative review aimed to clarify the nature of horizontal and lateral violence among nurses and assess how such violence affects patient safety. ...
Yunting Luo,Yanling Chen,Mei Feng Yunting Luo
Aim: To investigate the perception of career planning and development among senior clinical nurses and identify factors that facilitate or hinder their career development in a tertiary hospital setting in China. ...
Raiden Gaul,Audrey Snyder,Matti Smith Raiden Gaul
Aim: To analyze the contributions, challenges, and strategies for improving healthcare by past and present nursing leaders in St. Kitts and Nevis. Backgro...
Marco Sguanci,Stefano Mancin,Viviana Carù et al. Marco Sguanci et al.
Aim: To analyze the role of advanced practice nursing (APN) in the cardiology context in outpatient and inpatient settings, detailing their roles, competencies, and responsibilities. It also provides an overview of the ma...
Sara Shishehgar,Pauline Murray-Parahi,Ethar Alsharaydeh et al. Sara Shishehgar et al.
Background/objective: Artificial intelligence (AI) is embedded in healthcare education and practice. Pre-service training on AI technologies allows health professionals to identify the best use of AI. This systematic revi...
Maria Victoria Brunelli,Maria Maluenda Martinez,Valentina Sarco et al. Maria Victoria Brunelli et al.
Aim: To describe public perceptions of nurses in Argentina. Background: Nurses comprise more than 50% of the health workforce. Although...