Medically hospitalized individuals have high rates of comorbid psychiatric, substance abuse, and behavioral disorders. Disruptive and sometimes aggressive behaviors may arise when mental health needs of patients go unrecognized or are inadequately addressed. Health care workers experience the most workplace violence compared with other professions, with nurses and nursing aides at highest risk. A Behavioral Emergency Support Team (BEST) model can be an effective approach to providing a customized response to a patient's agitation through identification of underlying clinical and environmental contributors to the onset of aggression as well as to provide behavioral education and support of nursing staff. Results from 2 years of BEST model use resulted in 124 events among 96 patients of whom 19 had repeated events. The most common reasons for codes were aggression (79%) and elopement threat/attempt (45%), and the most frequent patient diagnosis was cognitive impairment (54%). Development of a BEST model provides support to nurses that is not otherwise available for events that are disruptive to care in inpatient medical settings and help minimize the occurrence of workplace violence.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/NAQ.0000000000000501 | DOI Listing |
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou North Road, Guangzhou, China.
Purpose: To explore the dynamic and parametric characteristics of [F]F-FAPI-42 PET/CT in lung cancers.
Methods: Nineteen participants with newly diagnosed lung cancer underwent 60-min dynamic [F]F-FAPI-42 PET/CT. Time-activity curves (TAC) were generated for tumors and normal organs, with kinetic parameters (K, K, K, K, K) calculated.
Eur J Psychotraumatol
December 2025
Psychology and Psychological Therapies Directorate, Cardiff & Vale University Health Board, Cardiff, UK.
The International Trauma Interview (ITI) is a clinician-administered assessment that has been newly developed for the International Classification of Diseases (ICD-11) diagnoses of posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD). The current study evaluated the psychometric properties of the ITI for treatment-seeking people with adverse childhood experiences (ACE) in South Korea, with the aims of verifying the validity and reliability of ITI as well as examining the differentiation of ICD-11 CPTSD and borderline personality disorder (BPD). In total, data of 103 people were analysed.
View Article and Find Full Text PDFAndes Pediatr
August 2024
Facultad de Ciencias de la Empresa, Universidad Politécnica de Cartagena, Cartagena, Spain.
Unlabelled: The use of latent construct measurement scales is widespread in the medical literature. An essential condition is that the instrument be validated, in addition to being highly reliable.
Objective: To evaluate the level of compliance with various methodological and statistical premises of validation studies of psychometric instruments in pediatrics, which are necessary to ensure adequate interpretation of the results, in order to offer recommendations for future research.
Andes Pediatr
August 2024
Departamento de Ciencias de la Actividad Física, Universidad Católica del Maule, Talca, Chile.
Unlabelled: Cardiorespiratory fitness can be assessed by direct, indirect, maximal, and moderate effort, running, cycling, or walking methods.
Objective: To predict maximum oxygen consumption (V O2max) from the six-minute walk test in schoolchildren.
Patients And Method: 459 students were included, 215 were male and 244 were female, aged 11.
Endocrinol Diabetes Metab
January 2025
Noncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
Introduction: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptiometry poses significant challenges due to their high costs and limited availability, particularly in small cities and rural areas. Our objective was to employ a variety of machine learning (ML) techniques to evaluate the accuracy and precision of each method, with the aim of identifying the most accurate pattern for diagnosing the osteoporosis risks.
Methods: We analysed the data related to osteoporosis risk factors obtained from the Fasa Adults Cohort Study in eight ML methods, including logistic regression (LR), baseline LR, decision tree classifiers (DT), support vector classifiers (SVC), random forest classifiers (RF), linear discriminant analysis (LDA), K nearest neighbour classifiers (KNN) and extreme gradient boosting (XGB).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!