ABSTRACT
Introduction. The rapid shift to online learning due to the COVID-19 pandemic presented challenges for physical therapy (PT) education worldwide. This article aims to explore the factors influencing the well-being of the PT faculty and department chairs involved in delivering PT programs during the initial stages of the COVID-19 pandemic. Review of Literature. The literature has focused on the pedagogical impacts of the rapid shift to online learning. Little is known about the social and psychological impacts of this rapid transition on the well-being of the faculty involved in implementing PT programs. Subjects. Physical therapy faculty and department chairs at 3 universities in metropolitan Sydney, Australia who taught into or led PT programs in 2020. Methods. Focus group methodology was used to explore the experiences of PT faculty and department chairs during the initial stages of the COVID pandemic. The focus groups were digitally recorded and transcribed verbatim and the transcripts analyzed thematically. Results: The main finding of this study was the extent of stress experienced by PT program faculty and chairs during this period. Both work-related institutional and faculty factors and non-work-related personal factors contributed to perceived high levels of stress. Overall, there was a feeling that the stressors had not improved over the duration of the pandemic and that this had left the faculty and chairs feeling more fatigued, less collegiate, and may have ongoing impacts on their mental health. Discussion: The pandemic created stresses for faculty and program chairs over and above the usual stress of faculty and college work. The reality of taking steps to reduce the stressors in the current climate is very difficult. Conclusion. Moving forward, it is vital to secure increased institutional support, including the support for creating realistic boundaries without the risk of penalty, to address the psychological health and well-being of PT faculty and chairs to enable high-quality education in the future. Copyright © 2023 Academy of Physical Therapy Education, APTA.
ABSTRACT
We analyze JUNE: a detailed model of COVID-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial computational resources to evaluate, making model calibration and general uncertainty analysis extremely challenging. We describe and employ the uncertainty quantification approaches of Bayes linear emulation and history matching to mimic JUNE and to perform a global parameter search, hence identifying regions of parameter space that produce acceptable matches to observed data, and demonstrating the capability of such methods. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.