The purpose of this study was to develop a fall risk assessment instrument for the inpatient psychiatric population. Nine risk factors were identified through a review of the literature. The instrument was applied retrospectively to patient records, and the percentage of those who fell who triggered each of the items in each domain was calculated. The expected value of the population and weighting system were established. The Morse Fall Scale and Edmonson Psychiatric Fall Risk Assessment Tool (EPFRAT) were administered simultaneously to inpatient psychiatric patients. Sensitivity of the EPFRAT was 0.63, compared with 0.49 for the Morse Fall Scale; specificity of the EPFRAT was 0.86, compared with 0.85 for the Morse Fall Scale. Initial psychometric testing of the EPFRAT indicates the instrument is more sensitive in assessing fall risk in the acutely ill psychiatric population than those currently available. Additional psychometric testing is needed to determine the reliability and validity of the EPFRAT.
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http://dx.doi.org/10.3928/02793695-20101202-03 | DOI Listing |
Geriatr Psychol Neuropsychiatr Vieil
December 2024
Faculté de santé, Université d'Angers, France, Département de médecine aiguë gériatrique, Centre de recherche sur l'autonomie et la longévité, hôpital universitaire d'Angers, France.
Older patients are at risk of falling, making fall prevention a critical component of training for future health professionals. To understand the expectations of health students regarding falls in the elderly, four consecutive focus groups were organized at the Angers hospital. The aim was to assess students' views on the effectiveness of using an educational or serious game to complement their traditional training.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Pathology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
Study Objectives: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.
Study Design: A cross-sectional design was employed using data from the DRYAD public database.
Research Methods: The study utilized data from the Fukushima Medical University Hospital Cohort Study, obtained from the DRYAD public database.
Sci Rep
January 2025
School of Nursing, Chengdu Medical College, Chengdu, China.
Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality of life. Early identification of at-risk individuals and timely intervention are essential. Nevertheless, current CF risk prediction models fall short in accuracy to adequately fulfill clinical requirements.
View Article and Find Full Text PDFNurs Open
January 2025
Nursing Administration and Education Department, College of Nursing, King Saud University, Riyadh, Saudi Arabia.
Aim: To assess the knowledge, attitudes and engagement of nursing interns regarding fall prevention activities during their internship within hospital settings.
Design: This study used a cross-sectional design.
Methods: This was a cross-sectional, descriptive, correlational study.
Crit Care Explor
January 2025
Division of Cardiovascular Critical Care Medicine, Department of Cardiology, Boston Children's Hospital, Boston, MA.
Background: Accurate assessment of oxygen delivery relative to oxygen demand is crucial in the care of a critically ill patient. The central venous oxygen saturation (Svo) enables an estimate of cardiac output yet obtaining these clinical data requires invasive procedures and repeated blood sampling. Interpretation remains subjective and vulnerable to error.
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