Background: Nursing staff need to be constantly exposed to information systems at work and encounter patients who share medical data obtained from the internet; this was widely observed during the coronavirus disease 2019 (COVID-19) pandemic. Hence, nursing staff should have the necessary skills and education that can help them develop nursing students' informatics competencies. However, research on assessing and improving nursing students' informatics competencies remains scarce.
Objective: This study aimed to provide nursing educators with a refined evaluation model and targeted improvement strategies tailored to enhance undergraduate students' informatics competencies.
Design: A cross-sectional study.
Methods: This study constructed a hybrid multiple-criteria decision-making model. The analytical hierarchical process was applied to obtain criteria weights; thereafter, the Visekriterijumska Optimizacija I Kompromisno Resenje with Aspiration-level (VIKOR-AS) method was used to assess undergraduate nursing students' informatics competencies of in the case hospital.
Participants: Data were obtained from 22 clinically experienced nurses with experience in supervising undergraduate nursing students at a secondary public hospital in Zhejiang Province, China.
Results: According to the weighted results, "Skill (C)" is an important dimension with the highest weight ranking. The corresponding highest-ranking criteria for each dimension are "Knowing how to explain the information management strategies to ensure patient safety (C)," "Applying information technology tools to support patient safety management (wristband scanning to identify patients, patients' electronic orders, etc.) (C)," and "Paying attention to the importance of information technology in clinical decision-making and preventing errors or facilitating patient care coordination (C)." In the case of the undergraduate nursing students' performance assessment, Student E was the best overall performer from the perspective of overall utility value. The remaining students ranked as follows: Student C Student D Student F Student A Student B.
Conclusions: This study model remedies the shortcomings of previous studies on evaluating undergraduate students' informatics competency dimensions, provides a reference for nursing colleges to develop nursing informatics-related curriculum content, and helps train nursing instructors to assess and train specific students. The results indicate that information skills are an important factor in the development of nursing students' informatics competencies; hence, nursing educators should prioritize the development of nursing students' informatics competencies, followed by information knowledge and attitudes.
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http://dx.doi.org/10.1186/s12909-024-06444-5 | DOI Listing |
Sci Data
December 2024
Biology Centre of the Czech Academy of Sciences, Institute of Entomology, Department of Ecology, Ceske Budejovice, Czech Republic.
Pathogens significantly influence natural and agricultural ecosystems, playing a crucial role in the regulation of species populations and maintaining biodiversity. Entomopathogenic fungi (EF), particularly within the Hypocreales order, exemplify understudied pathogens that infect insects and other arthropods globally. Despite their ecological importance, comprehensive data on EF host specificity and geographical distribution are lacking.
View Article and Find Full Text PDFBMC Med Educ
December 2024
School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Background: Nursing staff need to be constantly exposed to information systems at work and encounter patients who share medical data obtained from the internet; this was widely observed during the coronavirus disease 2019 (COVID-19) pandemic. Hence, nursing staff should have the necessary skills and education that can help them develop nursing students' informatics competencies. However, research on assessing and improving nursing students' informatics competencies remains scarce.
View Article and Find Full Text PDFIran Biomed J
December 2024
Department of Health Information Technology, Sorkheh School of Allied Medical Sciences, Semnan University of Medical Sciences, Semnan, Iran.
J Cardiothorac Surg
December 2024
Department of Medical Informatics, Medical School of Nantong University, Nantong, 226001, China.
Background: The classification of major adverse cardiovascular event (MACE) endpoints in patients with type 2 diabetes mellitus (T2DM) and either confirmed coronary artery disease (CAD) or high CAD risk, as well as the extent of the association between T2DM and coronary plaque characteristics, remains uncertain.
Purpose: This meta-analysis aims to compare MACE endpoints between patients with diabetes and patients without diabetes based on coronary artery plaques.
Methods: We searched studies from Web of Science, PubMed, Embase, and the Cochrane Library up until September 1, 2023.
BMC Med Imaging
December 2024
Department of Anatomy, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Introduction: Gadolinium-based T1-weighted MRI sequence is the gold standard for the detection of active multiple sclerosis (MS) lesions. The performance of machine learning (ML) and deep learning (DL) models in the classification of active and non-active MS lesions from the T2-weighted MRI images has been investigated in this study.
Methods: 107 Features of 75 active and 100 non-active MS lesions were extracted by using SegmentEditor and Radiomics modules of 3D slicer software.
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