Healing Health Care Disparities: Development and Pilot Testing of a Virtual Reality Implicit Bias Training Module for Physicians in the Context of Black Maternal Health.

Grounded in communication models of cultural competence, this study reports on the development and testing of the first module in a larger virtual reality (VR) implicit bias training for physicians to help them better: (a) recognize implicit bias and its effects on communication, patients, and patient care; (b) identify their own implicit biases and exercise strategies for managing them; and (c) learn and practice communicating with BIPOC patients in a culture-centered manner that demonstrates respect and builds trust. Led by communication faculty, a large, interdisciplinary team of researchers, clinicians, and engineers developed the first module tested herein focused on training goal (a). Within the module, participants observe five scenes between patient Marilyn Hayes (a Black woman) and Dr.

Reliability in performance assessment creates a potential application of artificial intelligence in veterinary education: evaluation of suturing skills at a single institution.

Objectives: To evaluate suturing skills of veterinary students using 3 common performance assessments (PAs) and to compare findings to data obtained by an electromyographic armband.

Sample: 16 second-year veterinary students.

Procedures: Students performed 4 suturing tasks on synthetic tissue models 1, 3, and 5 weeks after a surgical skills course.

Low-Cost UVBot Using SLAM to Mitigate the Spread of Noroviruses in Occupational Spaces.

Noroviruses (NoVs) cause over 90% of non-bacterial gastroenteritis outbreaks in adults and children in developed countries. Therefore, there is a need for approaches to mitigate the transmission of noroviruses in workplaces to reduce their substantial health burden. We developed and validated a low-cost, autonomous robot called the UVBot to disinfect occupational spaces using ultraviolet (UV) lamps.

Classification of Activities of Daily Living Based on Grasp Dynamics Obtained from a Leap Motion Controller.

Stroke is one of the leading causes of mortality and disability worldwide. Several evaluation methods have been used to assess the effects of stroke on the performance of activities of daily living (ADL). However, these methods are qualitative.