Aims: This study aimed to analyse the evolution of the public image of nursing in the context of the constantly developing nursing profession.
Design: The Rodger's evolving concept analysis was applied.
Methods: PubMed, CINAHL, Web of Science, Scopus, and ProQuest databases were searched for articles published between 1 January 2001, and 30 April 2022, using the search terms; "NURS * AND image". The selected literature was screened using Rodgers' evolutionary method to explore the attributes, antecedents and consequences of the concept.
Results: The defining attributes were identified as nursing (nursing as the collective object), public (public as the collective subject) and information (the medium of interaction between the collective subject and the collective object). Nursing elements were classified into intrinsic elements (professional spirit, professional knowledge and professional skills) and extrinsic (appearance, language and behaviour) elements. Public elements were further subcategorized into public categories (internal organizational public and external organizational public) and public perceptions (cognition, emotion and behavioural intention). The information elements are mainly classified as information generation, dissemination, identification, processing and judgement. The antecedents and consequences of the public perception of nursing were also identified.
Conclusions: The public image of nursing is dynamic and has evolved over time. Its dynamism and malleability imply that the traditional public image of nursing can be improved through targeted interventions in nursing practice, management and education.
Implications For The Profession: Identifying the antecedents and consequences associated with the public image of nursing will help the healthcare organizations adopt effective strategies to alleviate the shortage of the nursing workforce and promote the development of the nursing profession. No Patient or Public Contribution.
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http://dx.doi.org/10.1002/nop2.70033 | DOI Listing |
Neuroradiol J
January 2025
Division of Diagnostic Radiology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.
Objective: Predicting treatment response in patients with vestibular schwannomas (VSs) remains challenging. This study aimed to evaluate the use of pre-treatment normalized apparent diffusion coefficient (nADC) values and magnetic resonance (MR) imaging characteristics in predicting treatment outcomes in patients with VSs undergoing radiosurgery.
Methods: The MR images of 44 patients with VSs who underwent radiosurgery at our institution were retrospectively reviewed, and the patients were categorized into tumor control ( = 28) and progression ( = 16) groups based on treatment response after treatment initiation, with a median follow-up duration of 29.
Acta Radiol
January 2025
R Madhavan Nayar Center for Comprehensive Epilepsy Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India.
Background: The role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.
Purpose: To evaluate whether MRI is a diagnostic and prognostic marker for AIE and assess its efficacy in distinguishing between various AIE subtypes.
Material And Methods: We analyzed data from 96 AIE patients from our prospective autoimmune registry.
World J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
View Article and Find Full Text PDFCureus
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Obstetrics and Gynecology, Al Thagher General Hospital, Jeddah, SAU.
Heterotopic pregnancy is defined as the concurrent presence of both an intrauterine pregnancy and an extrauterine (typically ectopic) pregnancy. This report presents the case of a 36-year-old female patient who presented to the emergency department with lower abdominal pain. A comprehensive evaluation, including transabdominal and transvaginal ultrasound imaging, revealed a heterotopic pregnancy at an estimated gestational age of six weeks and two days.
View Article and Find Full Text PDFBankart lesions, or anterior-inferior glenoid labral tears, are diagnostically challenging on standard MRIs due to their subtle imaging features-often necessitating invasive MRI arthrograms (MRAs). This study develops deep learning (DL) models to detect Bankart lesions on both standard MRIs and MRAs, aiming to improve diagnostic accuracy and reduce reliance on MRAs. We curated a dataset of 586 shoulder MRIs (335 standard, 251 MRAs) from 558 patients who underwent arthroscopy.
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