Contributing Factors to Delays in COVID-19-Related Hospitalization Among Latinx and Spanish-Speaking Patients/Factores Que Contribuyen a Retrasos en Hospitalizaciones Relacionadas con COVID-19 Entre Pacientes Latinos e Hispano-Hablantes.

Background: Latinx populations have been more heavily impacted by the COVID-19 pandemic than the general population of the US, including higher rates of hospitalization due to COVID-19 in eastern Massachusetts. We conducted a qualitative study to better understand the experiences of Latinx and Spanish-speaking patients who had clinically significant COVID-19 in the early months of the pandemic.

Methods: Thirteen qualitative, semistructured, phone interviews were conducted between December 2020 and April 2021 with Latinx and Spanish-speaking patients who had experienced clinically significant COVID-19 in the metro-north Boston area.

Risk Factors for Hospitalization Among Patients with COVID-19 at a Community Ambulatory Clinic in Massachusetts During the Initial Pandemic Surge.

Among patients with COVID-19 evaluated in outpatient settings, factors associated with hospitalization remain poorly understood. Multivariable regressions were used to assess sociodemographic and clinical factors associated with increased odds of hospitalization among patients with confirmed COVID-19 between March 18, 2020 through April 25, 2020 at a community-based outpatient clinic in Massachusetts. Older age, BMI ≥ 25, self-reported dizziness/lightheadedness, temperature ≥ 99.

Coaching skills for medical education in a VUCA world.

The world is in the midst of the COVID-19 pandemic. Healthcare professionals and students globally are experiencing an increasingly 'VUCA' (volatile, uncertain, complex and ambiguous) healthcare and educational climate. Our future medical workforce needs skillsets to manage the personal and emotional challenges of work, uncertainty and change.

Instance-Based Genre-Specific Music Emotion Prediction with An EEG Setup.

This paper explores a novel direction in music-induced emotion (music emotion) analysis - the effects of different genres on the prediction of music emotion. We aim to compare the performance of various classifiers in the prediction of the emotion induced by music, as well as to investigate the adaptation of advanced features (such as asymmetries) in improving classification accuracy. The study is supported by real-world experiments where 10 subjects listened to 20 musical pieces from 5 genres- classical, heavy metal, electronic dance music, pop and rap, during which electroencephalogram (EEG) data were collected.