In recent years, there has been growing interest in examining the relationship between personality characteristics and nursing service. Nurses' personality characteristics affect nursing quality and contribute toward success in the field of nursing, but little is known about excellent nurses' personality characteristics that promote the quality of nursing care. The purpose of this study was to identify excellent nurses' personality characteristics through comparison and examination of the characteristics between excellent and average nurses. A cross-sectional survey research was conducted with the 16PF. Data were collected from three hospitals in the People's Republic of China. The participants were comprised of a total of 159 excellent (N = 78) and average (N = 81) qualified nurses. Excellent nurses possess higher social boldness, openness to change, self-reliance, perfectionism, and lower dominance, vigilance, shrewdness than average nurses. The study revealed the personality profile of excellent nurses. Nurses may be selected, employed and trained according to the personality characteristics of excellent nurses. Thus nursing strategies should be developed and adjusted to get the right person in the right job the first time.
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http://dx.doi.org/10.5172/conu.2013.43.2.219 | DOI Listing |
Front Psychol
January 2025
Department for Clinical Psychology and Psychotherapy, Philipps University Marburg, Marburg, Germany.
Background: Several studies identified affect-regulatory qualities of deceptive placebos within negative and positive affect. However, which specific characteristics of an affect-regulatory framing impacts the placebo effect has not yet been subject to empirical investigations. In particular, it is unclear whether placebo- induced expectations of direct emotion inhibition or emotion regulation after emotion induction elicit stronger effects in affect regulation.
View Article and Find Full Text PDFJ Clin Exp Hepatol
December 2024
Biochemistry and Molecular Biology Department, Theodor Bilharz Research Institute, Giza, Egypt.
Background: Liver fibrosis is a serious global health issue, but current treatment options are limited due to a lack of approved therapies capable of preventing or reversing established fibrosis.
Aim: This study investigated the antifibrotic effects of a synthetic peptide derived from α-lactalbumin in a mouse model of thioacetamide (TAA)-induced liver fibrosis.
Methods: analyses were conducted to assess the physicochemical properties, pharmacophore features, and docking interactions of the peptide.
Int J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
J Inflamm Res
January 2025
Department of Rheumatism and Immunity, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People's Republic of China.
Background: Ankylosing spondylitis (AS) is a chronic autoimmune disease characterized by inflammation of the sacroiliac joints and spine. Cuproptosis is a newly recognized copper-induced cell death mechanism. Our study explored the novel role of cuproptosis-related genes (CRGs) in AS, focusing on immune cell infiltration and molecular clustering.
View Article and Find Full Text PDFJ Inflamm Res
January 2025
Department of Pharmacology, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.
Background: Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis.
Methods: We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs).
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