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Differential Item Functioning Analysis of Likert Scales: An Overview and Demonstration of Rating Scale Tree Model.
Psychol Rep
January 2025
Department of Statistics, TU Dortmund University, Dortmund, Germany.
An important psychometric property in educational and psychological testing is differential item functioning (DIF), assessing whether different subgroups respond differently to particular items within a scale, despite having the same overall ability level. In fact, DIF occurs when respondents with the same underlying trait level have different probabilities of selecting specific response categories, depending on their subgroup membership. This study aims to demonstrate the usefulness of rating scale tree (RStree) model in detecting DIF of Likert-type scales across age and gender in social sciences.
View Article and Find Full Text PDFReal-world evaluation of physiotherapist-led exercise prehabilitation and rehabilitation during autologous stem cell transplantation in myeloma: a single-centre experience.
BMJ Open Qual
January 2025
UCL Cancer Institute, University College London, London, UK
Background: There is emerging evidence for the role of exercise in optimising function, quality of life (QoL) and reducing hospital length-of-stay if commenced prior to undergoing autologous stem cell transplantation (ASCT). A local pilot study of a prehabilitation and rehabilitation intervention during ASCT for myeloma patients indicated promising results and was adapted to translate into local clinical care. The aim of this report is to describe an overview of a newly implemented physiotherapist-led exercise prehabilitation and rehabilitation service delivered as part of the myeloma ASCT pathway, and present real-world findings related to changes in function and QoL.
View Article and Find Full Text PDFRoles, Skills, and Knowledge Requirements of Clinical Pharmacists in Disaster or Emergency Response Teams: A Scoping Review.
Disaster Med Public Health Prep
January 2025
Medical University of South Carolina, Charleston, SC, USA.
Objective: The scoping review aims to provide an overview of the existing literature to inform an understanding of pharmacists' roles, skills, and knowledge requirements for Emergency Medical Teams responding to disasters or humanitarian crises.
Methods: The methodology utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines, with methodology adapted by the Joanna Briggs Institute. Six databases were searched for sources published after 2000: PubMed, Mednar, Scopus, Defense Technical Information Centre, LILACS, and CINAHL.
Navigating trends in research related to vestibular function tests through scientometrics.
Eur Arch Otorhinolaryngol
January 2025
Librarian, Vidyavardhaka Law College, Mysore, Karnataka, 570 001, India.
Purpose: Research on vestibular function tests has advanced significantly over the past century. This study aims to evaluate research productivity, identify top contributors, and assess global collaboration to provide a comprehensive overview of trends and advancements in the field.
Method: A scientometric analysis was conducted using publications from the Scopus database, retrieved on January 5, 2024.
Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.
BMC Musculoskelet Disord
January 2025
Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
Background: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.
Methods: Three online databases (PubMed, MEDLINE, EMBASE) were searched from database inception to February 6, 2024, to identify literature on the use of machine learning to predict revision, secondary knee injury (e.g.
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