Interprofessional education: an overview of six initiatives across the schools of health at a single university

The benefits of interprofessional education (IPE) amongst health professionals are well documented, however, the implementation of interprofessional initiatives across the USA is inconsistent. This report describes the development and content of a number of IPE initiatives that are in the early stages of development and implementation at the University of California, Davis, USA. The article describes several important factors that were found to be necessary for the initial implementation of these IPE initiatives. Evaluation data from these initiatives, which is providing a range of positive outcomes, are also presented and discussed in relation to the wider IPE literature

COVID-19's Still-Urgent Lessons of Structural Inequality and Child Health in the United States.

COVID-19's lessons on structural inequality should have been painful and embarrassing to all of us. These daily experiences of an unacceptable status quo among US children are still with us in a post-COVID America. Addressing the multi-sectoral factors that undermine the nation...s health should remain urgent priorities for all health professionals

Interprofessional education: an overview of six initiatives across the schools of health at a single university

The benefits of interprofessional education (IPE) amongst health professionals are well documented, however, the implementation of interprofessional initiatives across the USA is inconsistent. This report describes the development and content of a number of IPE initiatives that are in the early stages of development and implementation at the University of California, Davis, USA. The article describes several important factors that were found to be necessary for the initial implementation of these IPE initiatives. Evaluation data from these initiatives, which is providing a range of positive outcomes, are also presented and discussed in relation to the wider IPE literature

The past, present and future in scaffold-based tendon treatments

Tendon injuries represent a significant clinical burden on healthcare systems worldwide. As the human population ages and the life expectancy increases, tendon injuries will become more prevalent especially among young individuals with long life ahead of them. Advancements in engineering, chemistry and biology have made available an array of three-dimensional scaffold-based intervention strategies, natural or synthetic in origin. Further, functionalisation strategies, based on biophysical, biochemical and biological cues, offer control over cellular functions; localisation and sustained release of therapeutics/biologics; and the ability to positively interact with the host to promote repair and regeneration. Herein, we critically discuss current therapies and emerging technologies that aim to transform tendon treatments in the years to come. (C) 2014 Elsevier B.V. All rights reserved

Emotional processing in Parkinson's disease and anxiety: an EEG study of visual affective word processing

A general problem in the design of an EEG-BCI system is the poor quality and low robustness of the extracted features, affecting overall performance. However, BCI systems that are applicable in real-time and outside clinical settings require high performance. Therefore, we have to improve the current methods for feature extraction. In this work, we investigated EEG source reconstruction techniques to enhance the extracted features based on a linearly constrained minimum variance (LCMV) beamformer. Beamformers allow for easy incorporation of anatomical data and are applicable in real-time. A 32-channel EEG-BCI system was designed for a two-class motor imagery (MI) paradigm. We optimized a synchronous system for two untrained subjects and investigated two aspects. First, we investigated the effect of using beamformers calculated on the basis of three different head models: a template 3-layered boundary element method (BEM) head model, a 3-layered personalized BEM head model and a personalized 5-layered finite difference method (FDM) head model including white and gray matter, CSF, scalp and skull tissue. Second, we investigated the influence of how the regions of interest, areas of expected MI activity, were constructed. On the one hand, they were chosen around electrodes C3 and C4, as hand MI activity theoretically is expected here. On the other hand, they were constructed based on the actual activated regions identified by an fMRI scan. Subsequently, an asynchronous system was derived for one of the subjects and an optimal balance between speed and accuracy was found. Lastly, a real-time application was made. These systems were evaluated by their accuracy, defined as the percentage of correct left and right classifications. From the real-time application, the information transfer rate (ITR) was also determined. An accuracy of 86.60 ± 4.40% was achieved for subject 1 and 78.71 ± 0.73% for subject 2. This gives an average accuracy of 82.66 ± 2.57%. We found that the use of a personalized FDM model improved the accuracy of the system, on average 24.22% with respect to the template BEM model and on average 5.15% with respect to the personalized BEM model. Including fMRI spatial priors did not improve accuracy. Personal fine- tuning largely resolved the robustness problems arising due to the differences in head geometry and neurophysiology between subjects. A real-time average accuracy of 64.26% was reached and the maximum ITR was 6.71 bits/min. We conclude that beamformers calculated with a personalized FDM model have great potential to ameliorate feature extraction and, as a consequence, to improve the performance of real-time BCI systems

Analysis of Outcomes in Ischemic vs Nonischemic Cardiomyopathy in Patients With Atrial Fibrillation A Report From the GARFIELD-AF Registry

IMPORTANCE Congestive heart failure (CHF) is commonly associated with nonvalvular atrial fibrillation (AF), and their combination may affect treatment strategies and outcomes