Clinical judgment development is critical to preparing students to safely meet the needs of an aging population. Evidence linking manikin-based simulation and clinical judgment is sparse.The purpose of this quasi-experimental international study was to determine the effect of expert role modeling on nursing students' clinical judgment in the care of a simulated geriatric hip fracture client. Students from five diverse schools (n = 275) participated in an unfolding simulation. Students were assigned to treatment or control groups.Treatment groups viewed an expert role model video.Trained observers rated student clinical judgment from selected video recordings using the Lasater Clinical Judgment Rubric (n = 94). Significant group differences (p = .000) were found for the clinical judgment dimensions of noticing, interpreting, and responding. Findings provide support for combining expert role modeling with clinical simulation to improve students' clinical judgment in the care of older adults.
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http://dx.doi.org/10.5480/1536-5026-33.3.176 | DOI Listing |
PLoS One
January 2025
Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Introduction: Insight in psychosis, defined as a patient's awareness and judgment of their mental illness, is a complex and evolving concept. Historically, the absence of insight was considered a defining characteristic of psychosis, but recent decades have seen the development of structured tools for its assessment. This systematic review aims to critically appraise the measurement properties of instruments used to assess insight in individuals with schizophrenia spectrum, bridging the gap between theoretical conceptualization and clinical practice.
View Article and Find Full Text PDFIntensive Care Med Exp
January 2025
Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA.
Background: The discharge practices from the intensive care unit exhibit heterogeneity and the recognition of eligible patients for discharge is often delayed. Recognizing the importance of safe discharge, which aims to minimize readmission and mortality, we developed a dynamic machine-learning model. The model aims to accurately identify patients ready for discharge, offering a comparison of its effectiveness with physician decisions in terms of safety and discrepancies in discharge readiness assessment.
View Article and Find Full Text PDFJ Pers Med
January 2025
Summit Neuropsychology, Reno, NV 89521, USA.
A significant proportion of patients who sustain a concussion/mild traumatic brain injury endorse persisting, lingering symptoms. The symptoms associated with concussion are nonspecific, and many other medical conditions present with similar symptoms. Medical conditions that overlap symptomatically with concussion include anxiety, depression, insomnia, chronic pain, chronic fatigue, fibromyalgia, and cervical strain injuries.
View Article and Find Full Text PDFDent J (Basel)
December 2024
Faculty of Dental Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Oral cancer ranks among the top ten cancers globally, with a five-year survival rate below 50%. This study aimed to evaluate the effectiveness of autofluorescence-guided surgery compared to standard surgical methods in identifying tumor-free margins and ensuring complete excision. A prospective cohort of 80 patients was randomized into two groups: the control group underwent excision with a 10 mm margin based on clinical judgment, while the experimental group used autofluorescence guidance with a 5 mm margin beyond fluorescence visualization loss.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
College of Liberal Arts Faculty of Basic Liberal Art, Hansung University, Seoul 02876, Republic of Korea.
The large language model (LLM) has the potential to be applied to clinical practice. However, there has been scarce study on this in the field of gastroenterology. Aim: This study explores the potential clinical utility of two LLMs in the field of gastroenterology: a customized GPT model and a conventional GPT-4o, an advanced LLM capable of retrieval-augmented generation (RAG).
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