Developing professional values among undergraduate nursing students is important since such values are a significant predictor of quality care, clients' recognition, and therefore nurses' job satisfaction. This study explored South Korean nursing students' perception of nursing professional values (NPV) and compared the NPV scores between groups according to participants' demographic characteristics. The study participants comprised of 529 students, mostly female (96.4%), with a mean age of 22.29years, sampled from six universities throughout the country. The NPV scores, measured with the 29-item Likert scale developed by Yeun et al. (2005), were significantly higher in students who entered nursing schools following their aptitude or desire for professional job than in those who entered the schools just because their entrance exam scores were sufficient. The NPV scores were also higher in students who were planning to pursue graduate study than in those who had not yet decided. The NPV scores were significantly different between the six regions, suggesting needs of in-depth studies to understand the underlying reasons. The NPV scores were not correlated, at the .05 level of significance, with academic year, gender, or academic performance.
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http://dx.doi.org/10.1016/j.nedt.2010.03.019 | DOI Listing |
Niger Med J
January 2025
Department of Radiology, Usmanu Danfodiyo University Teaching Hospital Sokoto, Nigeria.
Background: Stroke remains one of the major non-communicable public health disease conditions with resultant high morbidity and mortality. Neuroimaging in the form of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) is adjudged to be the most reliable and efficient method of accurately diagnosing stroke and ruling out differentials. However, in view of cost implication and non-availability, a clinical scoring system known as the Siriraj Stroke Score (SSS) was developed to clinically differentiate stroke types, especially in resource-limited settings.
View Article and Find Full Text PDFNuklearmedizin
January 2025
Department of Nuclear Medicine, Başakşehir Cam and Sakura City Hospital, University of Health Sciences, Istanbul, Turkey.
To determine the value of radiomics data extraction from baseline 18F FDG PET/CT in the prediction of tumor-infiltrating lymphocytes (TILs) among patients with primary breast cancer (BC).We retrospectively evaluated 74 patients who underwent baseline 18F FDG PET/CT scans for BC evaluation between October 2020 and April 2022. Radiomics data extraction resulted in a total of 131 radiomic features from primary tumors.
View Article and Find Full Text PDFBackground And Objective: Serum protein electrophoresis (SPEP) plays a critical role in diagnosing diseases associated with M-proteins. However, its clinical application is limited by a heavy reliance on experienced experts.
Methods: A dataset comprising 85,026 SPEP outcomes was utilized to develop artificial intelligence diagnostic models for the classification and localization of M-proteins.
J Adv Nurs
January 2025
College of Nursing, Guangzhou Medical University, Guangzhou, Guangdong, China.
Aims: To translate the Supportive and Palliative Care Indicators Tool (SPICT) into Chinese and conduct preliminarily tests of its performance in hospitalized patients with cancer.
Design: A cross-sectional validation study conducted from January to March 2024.
Methods: SPICT 2022 was translated in both directions, following the Brislin translation model, and the Chinese version culturally debugged through expert consultation and pre-testing.
Front Oncol
January 2025
School of Nursing, Chengdu Medical College, Chengdu, China.
Objective: Presentation delay of cancer patients prevents the patient from timely diagnosis and treatment leading to poor prognosis. Predicting the risk of presentation delay is crucial to improve the treatment outcomes. This study aimed to develop and validate prediction models of presentation delay risk in gastric cancer patients by using various machine learning models.
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