Health in All Education: A Transdisciplinary Learning Outcomes Framework.

Historical and recent population health issues necessitate the goal of educating and preparing a transdisciplinary workforce with population health knowledge and competence to be able to develop, implement, and evaluate innovative and feasible solutions that not only address multifaceted community health problems downstream but also to be able to predict and prevent those factors that contribute to an inequitable health burden upstream. To identify where population health education is already shared among multiple disciplines, the Centers for Disease Control and Prevention's Academic Partnerships to Improve Health program conceptualized the Health In All Education initiative that was implemented in partnership with the Association for Prevention Teaching and Research. The purpose of the initiative was to (1) show the importance of integrating population health principles into higher-education transdisciplinary practices; (2) discuss examples of Centers for Disease Control and Prevention collaboration with disciplines related to public health (i.

An Interactive Game with Virtual Reality Immersion to Improve Cultural Sensitivity in Health Care.

Purpose: Biased perceptions of individuals who are not part of one's in-groups tend to be negative and habitual. Because health care professionals are no less susceptible to biases than are others, the adverse impact of biases on marginalized populations in health care warrants continued attention and amelioration.

Method: Two characters, a Syrian refugee with limited English proficiency and a black pregnant woman with a history of opioid use disorder, were developed for an online training simulation that includes an interactive life course experience focused on social determinants of health, and a clinical encounter in a community health center utilizing virtual reality immersion.

Predicting second-generation antidepressant effectiveness in treating sadness using demographic and clinical information: A machine learning approach.

Introduction: Current guidelines for choosing antidepressant medications involve a trial-and-error process. Most patients try multiple antidepressants before finding an effective antidepressant. This study uses demographic and clinical information to create models predicting effectiveness of different antidepressants in treating sadness in a nationally representative sample of US adults.

The state of leadership education in US medical schools: results of a national survey.

Over the past two decades, there have been increasing calls for physicians to develop the capabilities to lead health care transformation. Many experts and authors have suggested that leadership education should begin during medical school; however, little information exists regarding the presence or nature of undergraduate medical education leadership curricula in the USA. This study sought to determine the prevalence of formal leadership education in US undergraduate medical schools, as well as the delivery methods and degree of student participation.

A high-throughput in vitro ring assay for vasoactivity using magnetic 3D bioprinting.

Vasoactive liabilities are typically assayed using wire myography, which is limited by its high cost and low throughput. To meet the demand for higher throughput in vitro alternatives, this study introduces a magnetic 3D bioprinting-based vasoactivity assay. The principle behind this assay is the magnetic printing of vascular smooth muscle cells into 3D rings that functionally represent blood vessel segments, whose contraction can be altered by vasodilators and vasoconstrictors.